prompts.chat Community

You are a senior competitive programmer proficient in writing time and space optimized programs in C++, Java and Python.
1. Understand the problem without keeping any bias for a particular topic.
2. Try to find out the pattern of the problem.
3. Formulate an approach around the pattern to solve the question.
4. Generate 20 edge cases and evaluate your code on these test cases.
5. Look for optimization possibilities in terms of time and space.
6. Return the final code.

I need to make a social website designed for robinhood chain users to use, 

Teach me module 2 properly and sequentially in proper flow, compare both document and include every numerical and theory sequentially from both documents

Design and creation of a marketing plan on Social Media platforms to market Hayek Travel services and bicycles in Britain. The target segment is Gulf students and Arab tourists.

---
name: herdr-multiagent
description: "Playbook for running several coding agents in parallel under Herdr: stage decomposition, one git worktree + isolated env + pane per agent, file-based briefs, state monitoring, review and merge. Agent-agnostic: the child kind comes from `herdr pane current` (.result.pane.agent) and matches the orchestrator (omp, opencode, claude, codex, kimi, ...). Use for multi-agent parallel work in separate worktrees. Requires HERDR_ENV=1."
---

# Multi-agent work through Herdr

Playbook: split the project's remaining work into independent stages, put each stage
on its own agent in its own git worktree and Herdr pane, hand it a file-based brief,
monitor it, and accept the result.

This skill is agent-agnostic: the kind of the children equals the kind of the
orchestrator. Launched from opencode, the children are opencode; from omp, they are
omp; from claude, they are claude. Never hardcode the orchestrator's kind from
memory and never pick a "popular" kind.

## 0. Preconditions

```bash
test "-" = 1   # if this fails, stop - we are not inside Herdr
```

If the check fails, tell the user the session is not running under Herdr and stop.
Do not drive someone else's Herdr from outside it.

The basic pane/agent commands live in Herdr's own skill (`herdr --skill`).
The installed binary is the authority on syntax; when unsure read
`herdr agent`, `herdr pane`, `herdr integration` instead of guessing.

## 1. Determine your own kind - before anything else

```bash
herdr pane current --current
```

The `.result.pane.agent` field IS the orchestrator's kind, and the same value goes
to `--kind` for the children:

```bash
KIND=$(herdr pane current --current | jq -r '.result.pane.agent')
# without jq:
KIND=$(herdr pane current --current | sed -E 's/.*"agent":"([^"]+)".*/\1/' | head -1)
echo "$KIND"
```

Empty or `unknown` - ask the user which kind to start the children with.
Below, `$KIND` always means this resolved value, never a literal.

Check the Herdr integration for this kind (it provides `agent list/wait/prompt`):

```bash
herdr integration status | grep -i "$KIND"
```

- `current` - good.
- `not installed` - run `herdr integration install "$KIND"`. Only **new** sessions
  pick the integration up, so install it BEFORE starting children; the orchestrator
  itself stays invisible to `agent list`, which is fine - it needs no monitoring.
- The kind is absent from `herdr integration install` (e.g. `amp`, `cline`, `kiro`,
  `maki`) - there will be no structural monitoring, use the §7 fallback
  (`pane read` + git). Not a blocker.

State it explicitly to the user: "children kind = $KIND".

## 2. Decomposition - the main step, do not rush

- Read the project plan/spec and the current state (`git log`, tests,
  `git worktree list`).
- Split the remaining work into stages with **non-overlapping file areas**.
  Two agents on one package - only deliberately and with an explicit order
  (afterwards, not in parallel).
- Additive edits to shared files (config, lock) are acceptable - record in the briefs
  "additive only, no signature changes"; the orchestrator resolves merge conflicts.
- Write down the matrix "stage -> files it MAY / MUST NOT touch".

Before launch: everything finished in main is committed, the tree is clean.

## 3. Worktree + isolated environment per agent

```bash
git worktree add ../<proj>-s<N> -b stage-<N>-<name>
```

Python trap: a shared venv imports SOMEONE ELSE's code (editable install of the main
repo). Give each worktree its own venv:

```bash
cd ../<proj>-s<N> && python -m venv .venv \
  && ./.venv/Scripts/python.exe -m pip install -q -e "./api[dev]"
```

Install several venvs sequentially in one background command (the pip cache is shared).
JS stack: its own `node_modules` per worktree (`npm ci`).

If the orchestrator has a command-wrapper hook (rtk and similar): a relative
interpreter path (`../.venv/Scripts/python.exe`) in briefs does not resolve through
such a hook ("command not found"). In briefs and prompts use only ABSOLUTE paths to
the python/npm of that worktree.

## 4. Briefs - as files, not on the command line

`<repo>/.briefs/stage-<N>.md` (untracked). Brief structure:

- **context**: what to read first (spec, contract, key files), what is already done;
- **task**: concrete requirements referencing spec items;
- **boundaries**: files allowed/forbidden, "do not leave the worktree", "do NOT push";
- **acceptance**: exact test/linter commands (with the absolute interpreter path of
  the worktree), "pre-existing tests stay green", commit to its own branch, final report.

A brief must not assume a particular agent kind: do not write "run omp/skill/..."
into it - write the goal, the boundaries and the acceptance commands. The child
decides which of its own tools to use.

The prompt to the agent is short: "Read the file <brief> and complete it fully".

## 5. Panes: create them, name them IMMEDIATELY

Recommended layout - main-left: the orchestrator pane on the left at full height, all
children in a column on the right, one under another. If the user has layout plugins
built around main-left, any other scheme breaks their view.
If the user explicitly asks for a different layout, follow the user.

First child - `split --current --direction right`, the rest -
`split --pane <previous child> --direction down` INSIDE the right column.
Do NOT split the orchestrator pane, and do not split agent panes to the right - only
the down-chain inside the right column.

```bash
herdr pane split --current --direction right --cwd "<worktree1>" --no-focus
herdr pane split --pane <agent1-pane> --direction down --cwd "<worktree2>" --no-focus
```

The new pane ID comes from JSON `.result.pane.pane_id`. Do not touch the user's focus
(`--no-focus`). The child gets its name in step 6 via `agent start`; additionally
`herdr pane rename <pane_id> "s<N>-<name>"` for clarity.

## 6. Starting a child of your own kind

The standard path is `agent start`, which also validates that the expected agent
actually came up in the pane:

```bash
herdr agent start s1-<name> --kind "$KIND" --pane <pane_id> -- <autonomy-flags>
```

The name must match `[a-z][a-z0-9_-]{0,31}` and be unique among live agents.

### Autonomy flags

A child works unattended, otherwise it stops at an approval. The flag belongs to the
CLI, not to Herdr. Confirmed ones:

| kind | launch |
|---|---|
| `omp` | `-- --yolo` |
| `claude` | `-- --dangerously-skip-permissions` (or `--permission-mode bypassPermissions`) |
| `opencode` | `-- --auto` |

For any other kind (codex, gemini, kimi, cursor, copilot, droid, kilo, grok, hermes,
qodercli, mastracode, pi, ...) do NOT invent a flag. Resolve the canonical executable
and read its help:

```bash
herdr agent start --help        # the --kind help text names the canonical executable
<executable> --help | grep -iE "permission|approve|yolo|auto|dangerous|allow"
```

No flag found - check whether the CLI has an autonomy mode in its config
(e.g. `~/.omp/agent/config.yml: tools.approvalMode: yolo`,
`~/.claude/settings.json: permissions`, `opencode.json: permission`), and warn the
user that the child may stop at approvals - those surface as the `blocked` state (§7).

### If `agent start` timed out

Known bug on Windows in PowerShell panes: `agent start` sends a mangled
`Start-Process` -> timeout. Workaround - launch the CLI in the pane directly:

```bash
herdr pane run <pane_id> "<executable> <autonomy-flags>"
sleep 3 && herdr pane read <pane_id> --lines 15   # expect the CLI prompt
herdr agent rename <pane_id> s1-<name>            # if herdr recognized the agent
```

If `herdr agent explain <pane_id>` still reports no recognized agent afterwards,
structural monitoring is unavailable for that pane - use the §7 fallback.

### Handing over the brief

NOT via `pane run`: Enter gets swallowed while the TUI renders the paste. Two steps
with a pause:

```bash
herdr pane send-text <pane_id> "Read the file <absolute path to the brief> - that is your brief. Complete it fully (code, tests, linter, commit to your own branch), then give a final report."
sleep 5 && herdr pane send-keys <pane_id> Enter
```

Standard alternative once the integration is installed and `agent start` succeeded:

```bash
herdr agent prompt s1-<name> "Read the file <brief> and complete it fully" --wait --timeout 300000
```

Verify with `pane read` that the brief actually WENT IN: input empty, agent working.

## 7. Monitoring - through the integration, NOT cron

```bash
herdr agent list                       # states of all children
herdr agent wait s1-<name> --until idle --timeout 1800000
herdr agent prompt s1-<name> "<text>"  # push an instruction to a working child
herdr agent read s1-<name> --lines 40
```

State semantics: `idle` - ready for input and its tab has been seen in the UI;
`done` - the same idle state after unseen background work (reading through the CLI
does not mark the tab seen); `blocked` - Herdr recognized an approval/question UI,
the child is WAITING for a human; `unknown` - an agent is present but cannot be
classified, which is NOT evidence of completion.

Orchestrator loop: `agent wait` in turn or on an event -> acceptance (§8).
`blocked` -> `agent read`, understand the question, answer via `agent prompt` or ask
the user. Suspicious silence -> `pane read <pane_id>`.

Keep the `wait` timeout moderate (~30 min) and re-arm it on each return: very large
values end up as "timed out".

Fallback when the integration for `$KIND` is unavailable or `agent explain` did not
recognize the child: periodic `herdr pane read <pane_id> --lines 60` plus
`git log/status` in the worktree. Cron only as a last resort, and always remove it
when done.

Child session dropped: the work in the worktree survives. Restart with the same CLI
and its continue flag (check `--help`): `omp --resume`, `claude --continue`,
`opencode --continue`. Then prompt: "Your session was interrupted. Check git status
and finish the brief <file>".

## 8. Acceptance and merge

- Each branch: tests + linter in its own worktree, review `git diff main...<branch> --stat`.
- Do not take the child's final report on faith - run the acceptance commands yourself.
- Merge into main only with the user's confirmation; resolve additive overlaps manually.
- After the merge: `git worktree remove`; branches as agreed with the user.
- Release the children's panes without touching the user's pane.

FILE:README.md
# herdr-multiagent

An agent skill (playbook) for driving a project with **several coding agents in
parallel** through [Herdr](https://herdr.dev), a terminal multiplexer for coding
agents — one git worktree and one pane per stage, file-based briefs, state
monitoring and acceptance.

The skill is **agent-agnostic**: the kind of the children is resolved from Herdr and
matches the kind of the orchestrator. Launched from `opencode`, the children are
`opencode`; from `omp`, they are `omp`; from `claude`, they are `claude`. Any kind
listed by `herdr agent start --help` works (pi, claude, codex, gemini, cursor, devin,
agy, cline, omp, mastracode, opencode, copilot, kimi, kiro, droid, amp, grok, hermes,
kilo, qodercli, maki).

## What it covers

- §1 resolve your own kind, verify the Herdr integration for it;
- §2 decompose into stages with non-overlapping file areas;
- §3 worktree + isolated environment (own venv / node_modules — otherwise agents
  import someone else's code through the main repo's editable install);
- §4 briefs as files, not on the command line;
- §5 main-left pane layout, `--no-focus` (the user's focus is never taken);
- §6 starting a child, autonomy flags per kind, the Windows `agent start` timeout
  workaround, correct brief hand-over (Enter gets swallowed by `pane run`);
- §7 monitoring via `herdr agent list/wait/prompt/read`, the semantics of
  `idle/done/blocked/unknown`, fallback to `pane read` + git, recovering a dropped
  child session;
- §8 acceptance and merge only with the user's confirmation.

## Requirements

- Herdr, with the session running inside one of its panes (`HERDR_ENV=1`). Outside
  Herdr the skill stops.
- Git (worktrees).
- One supported agent CLI on `PATH`.
- For structural monitoring: `herdr integration install <kind>`. Kinds without an
  integration fall back to `pane read` + git — not a blocker.
- Verified on Windows (Git Bash + PowerShell panes); the commands are POSIX, with an
  explicit note where Windows venv paths differ.

## Installation

A skill is a directory containing `SKILL.md`. Put it into your agent's skills root:

| Agent | path (verified on the author's machine) |
|---|---|
| omp, pi | `~/.agents/skills/herdr-multiagent/SKILL.md` |
| Claude Code | `~/.claude/skills/herdr-multiagent/SKILL.md` |
| opencode | `~/.config/opencode/skills/herdr-multiagent/SKILL.md` |
| project-local | `<repo>/.agents/skills/herdr-multiagent/SKILL.md` |

The layout is non-recursive: `<skills-root>/<skill-name>/SKILL.md`. A nested path
like `skills/team/herdr-multiagent/SKILL.md` is not discovered.

Check your own CLI's docs for the exact skills root — the directories differ per
agent, while `SKILL.md` with `name` + `description` frontmatter is read the same way.

## Usage

Explicitly: ask the agent to "work according to the herdr-multiagent skill", or
invoke `/skill:herdr-multiagent` (in omp, when skill commands are enabled).

Automatically: the skill is picked up when the task reads like "build this with
several agents in parallel" and the agent runs inside Herdr.

The first thing the agent does is check `HERDR_ENV=1` and resolve its own kind; then
it proposes a decomposition and asks for confirmation before starting any child.

## Layout

```
herdr-multiagent/
├─ SKILL.md      # the skill body: frontmatter (name, description) + §0–§8
└─ README.md     # this file, for humans; the agent does not need it
```

Extra assets (scripts, brief templates, `references/*.md`) go into the same directory
and are read by the agent via `skill://herdr-multiagent/<path>`. There are none here:
the playbook fits in a single file, and the brief template is described in prose in §4.

## Safety

Children run in an autonomy mode (`omp --yolo`, `claude
--dangerously-skip-permissions`, `opencode --auto`) — without approval prompts. That
means full filesystem and shell access inside their worktree. The skill constrains
them through the brief ("do not leave the worktree", "do NOT push"), but that is an
instruction, not isolation. Merging into main happens only on the user's explicit
confirmation.

## License

Free to use.

Analyze the current website's design system by reviewing its key pages: homepage, 
a product or pricing page, an interior content page, a form or contact page, and 
any page with unique UI patterns (testimonials, pricing tables, etc.).

Where possible, inspect actual computed CSS values (via element inspection) rather 
than estimating visually, so colors, sizes, and spacing are accurate rather than 
approximate.

Document the following:

- Color palette: primary, secondary, accent, and neutral colors with hex/rgb 
  values and where each is used
- Typography: font families, weights, sizes, and line-heights for H1-H6, body 
  text, and captions/labels
- Spacing and layout: spacing scale, container widths, grid structure, and 
  responsive breakpoints
- Buttons and CTAs: primary/secondary/tertiary button styles, including hover 
  and active states if visible
- Forms and inputs: field styling, borders, focus states
- Navigation: header/nav structure and styling, footer structure
- Cards and containers: border-radius, shadows, borders
- Iconography and imagery style

Flag any inconsistencies across pages (e.g., different button styles in 
different places) instead of picking one and ignoring the rest.

Output the result as a single markdown (.md) file with H2 headers for each 
category, tables for color palettes and typography scales, and code blocks for 
CSS values. Structure it so a developer or designer could use it directly. 
Save it as [site-name]-design-system.md so I can export it from this thread.

Maktaba shamela and turath app etc cross checked 5 times verification Master research prompt 100/100 rating regarding (on Genspark Deep AI research agent research)
73 sects and 72 will be in fire who are the 72 sects in fire what scholars say that these are the 72 sects etc

Give me note book to learn Spanish with Myanmar translation 

You are a senior software architect and pharmacy management systems specialist.

Design and build a private pharmacy CRM for my pharmacy in Mosul, Iraq.

The system is for managing patients, chronic medications, follow-ups, sales insights, inventory, and customer relationships.

Main goal

Create a simple, fast, private CRM that helps me remember patients, understand their medication history, follow up with chronic patients, identify sales opportunities, and improve pharmacy service without encouraging unsafe or unnecessary medication use.

Users

The system will initially have one administrator user.

The pharmacist must control access to patient information.

Patient data must not be publicly accessible.

Core patient profile

Each patient should have:

- Unique patient ID
- QR code
- Full name
- Age or date of birth
- Sex
- Phone number
- Address or area
- Notes
- Date added
- Last visit
- Next follow-up date
- Patient status

Medication profile

For each patient store:

- Medication name
- Active ingredient
- Strength
- Dosage form
- Dose
- Frequency
- Duration
- Start date
- End date
- Prescriber
- Reason for use
- Current or discontinued status
- Notes

Medication history must remain available so I can see previous medications.

Chronic medication management

Allow me to mark patients as chronic-care patients.

For chronic patients show:

- Active medications
- Previous medications
- Expected refill date
- Last purchase date
- Days since last purchase
- Follow-up date
- Missed refill
- Pharmacist notes

The system should help identify patients who may need follow-up.

Do not automatically recommend changing treatment or stopping medication.

Dashboard

Create a dashboard showing:

- Total patients
- Active chronic patients
- Patients due for follow-up
- Missed follow-ups
- Patients due for medication refill
- New patients
- Returning patients
- Today's follow-ups
- Recent purchases
- Sales
- Profit
- Low-stock products
- Products approaching expiry

CRM features

Allow me to:

- Search patients by name
- Search by phone number
- Search by patient ID
- Scan a QR code
- Open the patient profile quickly
- Add a visit
- Add medication
- Edit medication
- Record a purchase
- Record pharmacist notes
- Set a follow-up date
- Mark a follow-up as completed
- View patient history

QR system

Every patient should have a unique QR code.

Scanning the QR code should open the patient's profile inside the authenticated CRM.

The QR code must not expose sensitive patient information directly.

Inventory integration

If pharmacy inventory data is available, connect the CRM to it.

Show:

- Product
- Category
- Stock
- Purchase cost
- Selling price
- Profit
- Profit margin
- Daily consumption
- Estimated days until stockout
- Expiry date

Marketing and CRM analytics

Create useful customer segments such as:

- Chronic patients
- Frequent customers
- Inactive customers
- Patients due for refill
- Patients due for follow-up
- High-value customers
- OTC customers
- Supplement customers

Use these segments to suggest ethical pharmacy actions.

Examples:

- Reminder to refill a chronic medication
- Follow-up reminder
- Blood pressure monitoring service
- Medication adherence follow-up
- Relevant OTC product suggestion when clinically appropriate
- Personal-care recommendation based on customer needs

Never recommend unnecessary medication or supplements simply to increase sales.

Sales analytics

Track:

- Daily sales
- Weekly sales
- Monthly sales
- Gross profit
- Profit margin
- Number of transactions
- Average transaction value
- Sales by category
- Sales by product
- OTC sales
- Supplement sales
- Chronic medication sales

Show trends and identify changes in customer behavior.

Alerts

Create alerts for:

- Follow-up due
- Missed follow-up
- Expected refill
- Missed refill
- Low stock
- Near expiry
- Expired product
- Unusual sales changes

Privacy and security

Patient information is sensitive.

Use:

- Authentication
- Secure local storage or encrypted database
- Role-based access if multiple users are added later
- Automatic session timeout
- Database backup
- Restore function
- Audit log for important changes

The system should work locally whenever possible.

Avoid sending patient information to external AI services unless I explicitly enable it.

Interface

Design the interface for a pharmacist working quickly during busy hours.

Prioritize:

- Fast search
- Few clicks
- Large buttons
- Clear patient timeline
- Simple forms
- Mobile-friendly interface
- Arabic and English support
- Iraqi pharmacy terminology where appropriate

Main screens

Create:

1. Dashboard
2. Patients
3. Patient profile
4. Medication history
5. Visits
6. Follow-ups
7. Inventory
8. Sales analytics
9. Alerts
10. Reports
11. Settings
12. Backup and restore

Patient timeline

Every patient should have a chronological timeline containing:

- Registration
- Visits
- Medication additions
- Medication changes
- Purchases
- Follow-ups
- Notes

Analytics

The CRM should generate actionable insights rather than only displaying numbers.

For example:

"23 chronic patients are expected to refill within 7 days."

"11 patients have not returned within their expected refill period."

"OTC sales increased 14% this month."

"Category X has high sales but low profit margin."

"17 products may expire before expected stock depletion."

Explain why each insight matters and what action I should consider.

AI assistant

Include an optional AI assistant that can answer questions about CRM data.

Examples:

- Which chronic patients are due for refill this week?
- Which patients have missed their expected refill?
- What are my top 20 profitable products?
- Which categories have high sales but low margins?
- Which products are at risk of expiry?
- Which days have the highest sales?
- What changed compared with last month?
- Which patients need follow-up today?

The AI must distinguish between:

- Facts directly available in the database
- Calculations
- Predictions
- Suggestions

Never invent patient information or sales data.

Architecture

Recommend a production-ready architecture that is simple enough for a small pharmacy.

Prefer a local-first architecture.

Explain:

- Frontend
- Backend
- Database
- Authentication
- QR generation
- Backup system
- API structure
- AI integration
- Deployment
- Security

Design the database schema before implementation.

Include relationships between:

- Patients
- Medications
- Visits
- Purchases
- Products
- Follow-ups
- Users
- Alerts
- Audit logs

Important constraints

The system must remain simple.

Do not add features just because they sound impressive.

Every feature should answer one of these questions:

- Does it save pharmacist time?
- Does it improve patient follow-up?
- Does it reduce stock problems?
- Does it improve business visibility?
- Does it improve patient service?
- Does it protect patient data?

Before writing implementation code:

1. Define the complete requirements.
2. Identify missing requirements.
3. Design the database.
4. Design the user workflow.
5. Design the API.
6. Define the security model.
7. Define the MVP.
8. Then propose the implementation plan.

Build the MVP first.

Do not overengineer the system.

(Portrait of a beautiful young woman:1.3), (Middle Eastern ethnicity:1.2), (age 20:1.1), (intricate facial features:1.3), (soft natural expression:1.2), wearing a (vibrant red headscarf:1.2) wrapped around wavy dark hair, dressed in a (detailed blue floral blouse:1.2) over a (yellow textured top:1.1), adorned with (ornate turquoise beaded necklace:1.2), (large vintage drop earrings:1.1), and gold bangles. The subject is positioned slightly to the left, (facing the viewer:1.2), resting her arms on a surface. Background features a (distressed turquoise wall:1.2), a (large rustic ceramic vase:1.1) containing yellow wildflowers, and a small painted bowl. (Fine art oil painting style:1.3), rich color palette of teal, gold, and crimson, (soft cinematic lighting:1.2), painterly textures, elegant composition, high detail, masterpiece, 8k resolution, volumetric atmosphere, sophisticated classic portraiture style.

Scenic alpine village on the edge of a serene turquoise lake, (charming European architecture:1.2) with terracotta-tiled roofs, classic Swiss-style buildings, a prominent clock tower spire reaching towards the sky, lush green trees lining the water's edge, majestic snow-capped mountains (Alps:1.3) towering in the background under a clear blue sky with fluffy white clouds, a small wooden motorboat (detailed textures:1.1) navigating the gentle ripples in the foreground, bright natural daylight, crisp atmosphere, (vivid colors:1.2), photorealistic, high-resolution photography, travel magazine aesthetic, wide-angle lens, sharp focus, serene summer day, detailed landscape, depth of field, cinematic lighting.

# Technical Whitepaper Writer

## Why this skill exists

Most AI-generated whitepapers read like marketing documents: vague claims, excessive adjectives, feature lists presented as innovation, unsupported performance numbers, generic architecture diagrams, and roadmaps used as substitutes for technical evidence.

A strong whitepaper instead explains **why a problem exists, what the proposed system does, how it works, why the design is structured that way, what assumptions it makes, how it behaves under normal and failure conditions, and where the design remains limited.**

The goal is a document that reads like **engineering and technical research**, not a sales brochure.

The whitepaper should let a technically capable reader answer:

1. What problem is being solved?
2. Why do existing approaches fail or become insufficient?
3. What is being proposed?
4. How does the proposed system actually work?
5. What are the major components, and how do they interact?
6. What assumptions does the design make?
7. What happens during normal operation?
8. What happens when something goes wrong?
9. What evidence supports the technical claims?
10. What are the limitations and unresolved risks?
11. How is this different from existing approaches?
12. What would someone need to implement, evaluate, or deploy it?

Writing should prioritize **clarity, technical precision, traceability, and intellectual honesty** over impressive-sounding language.

---

## Step 1 — Gather inputs before writing

Do not begin drafting the full whitepaper until the core information is available. If critical information is missing, ask for it (see Step 20) rather than inventing it.

**1. The problem.** State it in one clear sentence, then describe a concrete scenario showing what fails without the proposed solution.

- Avoid: *"The industry needs a revolutionary new approach."*
- Prefer: *"Current systems require each application to independently integrate multiple model providers, resulting in duplicated integration logic, inconsistent observability, and difficult provider switching."*

**2. The project type.** Identify the primary category (and any important secondary categories) without forcing the project into an inappropriate one. Examples: AI/ML system, LLM application, AI infrastructure, data platform, developer tool, cloud/distributed system, cybersecurity system, networking system, database/storage system, hardware/embedded system, robotics system, scientific/research system, enterprise architecture, SaaS platform, API/middleware, agentic system, FinTech, healthcare tech, industrial or energy tech, protocol/standards system, or other.

**3. The core mechanism.** Describe what actually happens inside the system — inputs, processing, state, transformations, decisions, outputs, feedback loops, external dependencies, failure paths, system boundaries. Not a feature list.

- Avoid: *"The platform provides intelligent routing, security, observability, and scalability."*
- Prefer: *"An incoming request is classified according to model, latency, cost, and policy requirements. The routing layer selects an eligible provider, executes the request, records telemetry, and applies retry or fallback logic when the selected provider fails."*

**4. System boundaries.** What's inside the system vs. external? Which components are controlled vs. dependencies? Where does data enter and leave? Where does trust begin and end?

**5. Actors and stakeholders.** Only include actors relevant to the system (e.g., end users, developers, administrators, operators, services, models, agents, data/infrastructure providers, validators, attackers, external systems). For each important actor: what they do, need, control, can observe, and what incentives or constraints shape their behavior.

**6. Resources, economics, or tokens — only when applicable.** If the system has a token, credits, usage units, subscriptions, fees, incentives, rewards, penalties, compute allocation, or quotas, explain their *mechanical* purpose. Never introduce tokenomics or financial mechanisms just because a whitepaper is "expected" to have them. Omit this section if no economic mechanism exists.

**7. Known limitations and risks.** What might fail, degrade, or remain unresolved — scalability limits, latency constraints, dependency risks, model limitations, data quality issues, security assumptions, operational complexity, cost constraints, hardware limitations, privacy concerns, regulatory uncertainty, availability dependencies, integration complexity. State these explicitly; do not hide them.

---

## Step 2 — Choose the whitepaper structure

Do not force every project into an identical template. The default technical spine:

1. Abstract
2. Introduction
3. Problem and Motivation
4. Existing Approaches
5. Design Goals and Non-Goals
6. Proposed Architecture
7. Core Mechanism
8. System Workflow
9. Technical Design
10. Security / Safety / Reliability Model
11. Performance and Scalability
12. Implementation Considerations
13. Worked Example
14. Evaluation / Evidence
15. Limitations and Open Problems
16. Future Work
17. Conclusion
18. References

Not every section is mandatory — use only what materially improves understanding:

- A simple software architecture may skip heavy mathematical analysis.
- An AI research system may need experiments and evaluation methodology.
- A cybersecurity system may need a detailed threat model.
- A hardware system may need physical constraints and benchmarking.
- A distributed system may need consistency, fault tolerance, and failure analysis.
- A commercial SaaS platform may need deployment/operational architecture rather than formal proofs.

---

## Step 3 — Establish the technical delta

If the project builds on or extends existing technology, explicitly trace:

> What existed before → What limitation remained → What this design changes → Why that change matters.

- Avoid: *"This is the world's first revolutionary architecture."*
- Prefer: *"Existing approach A provides X but requires Y. Approach B removes Y but introduces Z. The proposed architecture combines X with a different execution model that removes Y while accepting an explicit trade-off in Z."*

---

## Step 4 — Build the mechanism from a minimal model

Introduce complexity progressively rather than presenting the full architecture at once:

1. **Intuition** — the idea in simple language.
2. **Minimal model** — the smallest system that could solve the problem.
3. **Architecture** — the major components.
4. **Data / request flow** — how information moves through the system.
5. **Technical mechanisms** — algorithms, protocols, models, APIs, state transitions, policies.
6. **Failure behavior** — what happens when components fail or assumptions break.
7. **Optimization** — performance, scalability, caching, batching, routing, parallelism.

---

## Step 5 — Apply evidence discipline

Claims like *faster, cheaper, more secure, scalable, reliable, accurate, lower latency, higher throughput, reduced hallucination, improved efficiency* must never be asserted without support.

Where possible, provide: benchmark results, measurements, formulas, thresholds, experimental results, architectural reasoning, citations, assumptions, or comparison methodology.

- Avoid: *"The architecture provides extremely low latency."*
- Prefer: *"In the evaluated configuration, the routing layer adds a median of X ms of processing overhead under Y workload."*

If a number is unavailable, say so. **Never fabricate measurements.**

---

## Step 6 — Analyze each important actor

For each actor: responsibility, inputs, outputs, permissions, dependencies, incentives, constraints, failure modes, and consequences of incorrect behavior. Example set (adapt to the actual project):

- **User** — submits a request and receives a response.
- **Application** — authenticates the request and invokes the platform API.
- **Model Provider** — processes the inference request.
- **Gateway** — applies routing, policy, retry, and observability logic.
- **Operator** — configures policies and monitors system health.

---

## Step 7 — Define the threat, failure, or risk model

Depending on the project, analyze relevant risks: malicious users, compromised components, unauthorized access, data leakage, model manipulation, prompt injection, supply-chain attacks, denial of service, corrupted data, incorrect outputs, infrastructure/dependency failure, network partitions, hardware failure, operator error, configuration errors, adversarial inputs, economic attacks, privacy violations.

For every significant threat:

> Threat → Attack/Failure Mechanism → Impact → Mitigation → Remaining Risk

- Avoid: *"The system is highly secure."*
- Prefer: explaining secure **against what**, **under which assumptions**, and **with what controls**.

---

## Step 8 — Include a worked example

Every substantive whitepaper needs at least one concrete, end-to-end example — a transaction lifecycle, API request, inference request, data pipeline, user workflow, state transition, attack scenario, failure scenario, or numerical calculation. Include real numbers where useful.

Example shape:

> 1. Client submits request.
> 2. Gateway validates policy.
> 3. Router selects provider.
> 4. Provider executes inference.
> 5. Response passes through validation.
> 6. Telemetry is recorded.
> 7. Client receives response.

---

## Step 9 — Explain architecture clearly

Architecture descriptions should answer: What are the major components? What does each do? How are they connected? What protocols/interfaces link them? Where is state stored? Where does computation happen? Where are decisions made? Where are the security boundaries? Where can failures occur?

Use layered structure only where it reflects reality, e.g.:

```text
User / Client Layer
        ↓
API / Interface Layer
        ↓
Application / Orchestration Layer
        ↓
Core Processing Layer
        ↓
Data / Model / Storage Layer
        ↓
Infrastructure Layer
```

Do not add layers for visual symmetry alone.

---

## Step 10 — Handle mathematics appropriately

Use equations when they clarify the mechanism: optimization objectives, probability models, scoring functions, cost/latency/throughput calculations, capacity planning, cryptographic formulas, ML objectives, resource allocation, economic models, reliability calculations. Always explain each equation in plain language. Never add math purely for appearance.

---

## Step 11 — Handle AI/ML systems appropriately

Distinguish clearly between model architecture, training, fine-tuning, inference, retrieval, orchestration, evaluation, safety, monitoring, data pipelines, and human-in-the-loop processes.

Frame the pipeline explicitly:

> Input → Processing → Model / Retrieval / Tool Use → Validation → Output

Where relevant, cover: model selection, training methodology, dataset assumptions, context management, retrieval strategy, evaluation methodology, hallucination mitigation, guardrails, latency, inference cost, observability, and model failure modes.

Avoid vague terms like "intelligent," "cognitive," or "human-like" unless technically defined.

---

## Step 12 — Compare against existing approaches

Where relevant, compare on concrete dimensions:

| Dimension | Existing Approach | Proposed Approach |
|---|---|---|
| Architecture | ... | ... |
| Latency | ... | ... |
| Scalability | ... | ... |
| Cost | ... | ... |
| Security | ... | ... |
| Flexibility | ... | ... |
| Operational Complexity | ... | ... |

Every row needs a defensible basis — don't build the table just to look complete.

---

## Step 13 — Discuss trade-offs

Every meaningful architecture has trade-offs. Discuss the relevant ones explicitly: performance vs. cost, flexibility vs. complexity, security vs. usability, consistency vs. availability, latency vs. accuracy, centralization vs. decentralization, automation vs. human control, compute vs. memory, precision vs. recall, privacy vs. observability.

Never claim the design eliminates trade-offs — explain **which were chosen, and why**.

---

## Step 14 — Separate current capability from future work

Do not present roadmap items as evidence the system currently works. Distinguish:

- **Current design** — what exists or is technically specified today.
- **Experimental / validated** — what has been implemented and tested.
- **Proposed extensions** — what could be built later.
- **Open research problems** — what remains unresolved.

A roadmap is not proof of technical viability.

---

## Step 15 — Anti-pattern filter

Before presenting a draft, scan for and rewrite:

**Marketing language** — revolutionary, groundbreaking, game-changing, next-generation, world-class, unprecedented, highly intelligent, infinitely scalable, military-grade, enterprise-grade — unless technically defined and supported.

**Unsupported claims** — "10x faster," "99.99% reliable," "100% secure," "zero hallucinations," "fully autonomous," "unlimited scalability" — unless evidence exists.

**Feature dumping** — a list of features is not an architecture.

**Buzzword substitution** — "AI + blockchain + cloud + quantum + autonomous agents" is not a mechanism.

**Roadmap-as-proof** — future plans don't demonstrate present viability.

**Tokenomics without purpose** — don't invent economic mechanisms.

**Novelty without comparison** — don't claim innovation without explaining what came before.

**Security without threat modeling** — don't claim security without naming threats and mitigations.

**Architecture without data flow** — components alone don't explain a system.

**Missing limitations** — every serious design has them; state them.

---

## Step 16 — External research and citations

When using external information: cite every external technical claim, prefer primary and authoritative sources, cite research papers for scientific claims, official documentation for technical specs, standards bodies for standards, and vendor docs for vendor-specific behavior.

Use inline numbered citations:

> Transformer architectures use self-attention to model relationships between tokens [1].

```markdown
## References
[1] Vaswani et al., "Attention Is All You Need," 2017.
```

**Never fabricate references. Never cite a source that doesn't actually support the statement.**

---

## Step 17 — Writing style

Write as an experienced engineer or researcher explaining a complex system to another technically capable person.

**Prefer:** precise language, short-to-medium paragraphs, clear explanations, explicit assumptions, concrete examples, technical depth where useful, structured-text diagrams where appropriate, meaningful section titles.

**Avoid:** excessive adjectives, startup-style hype, repetitive conclusions, generic mission statements, unnecessary jargon, artificial complexity, fake certainty.

The tone: *"Here is the problem. Here is why existing approaches struggle. Here is the mechanism we propose. Here is how it works. Here is the evidence. Here is where it can fail."*

Not: *"We are revolutionizing the future of technology."*

---

## Step 18 — Output structure

Produce the whitepaper in Markdown, adapting section numbers to the actual project (omit irrelevant sections):

```markdown
# Title

## Abstract
## 1. Introduction
## 2. Problem and Motivation
## 3. Existing Approaches
## 4. Design Goals and Non-Goals
## 5. Proposed Architecture
## 6. Core Mechanism
## 7. System Workflow
## 8. Technical Design
## 9. Security, Safety, and Reliability
## 10. Performance and Scalability
## 11. Worked Example
## 12. Evaluation
## 13. Limitations and Open Problems
## 14. Future Work
## 15. Conclusion
## References
```

**Length should follow technical complexity, not an arbitrary page count.** A simple system gets a concise paper; a complex one gets deeper treatment.

---

## Step 19 — Pre-publish self-check

Before declaring the whitepaper complete, verify each item:

| Check | Status |
|---|---|
| Problem is concrete | PASS / FAIL |
| Failure scenario is explained | PASS / FAIL |
| Project type is correctly identified | PASS / FAIL |
| Core mechanism is clearly explained | PASS / FAIL |
| System boundaries are defined | PASS / FAIL |
| Architecture is understandable | PASS / FAIL |
| Data / request flow is explained | PASS / FAIL |
| Existing approaches are discussed | PASS / FAIL |
| Technical delta is clear | PASS / FAIL |
| Important actors are analyzed | PASS / FAIL |
| Threat / failure model exists | PASS / FAIL |
| Major claims have evidence | PASS / FAIL |
| At least one worked example exists | PASS / FAIL |
| Trade-offs are acknowledged | PASS / FAIL |
| Limitations are explicitly stated | PASS / FAIL |
| Future work is separated from current capability | PASS / FAIL |
| External claims are cited | PASS / FAIL |
| No fabricated numbers or references | PASS / FAIL |
| No marketing hype substitutes for technical explanation | PASS / FAIL |

Report a short **Whitepaper Quality Check** summarizing these results. If important information is missing, say so explicitly rather than inventing it.

---

## Step 20 — Missing information policy

If critical information is missing, ask for it before drafting that portion. **Never fabricate:** technical specifications, benchmark results, customer numbers, adoption statistics, revenue, market size, team credentials, partnerships, security guarantees, performance measurements, token economics, implementation details, or research results.

When something is unknown, mark it clearly:

> **Not specified** / **Requires validation** / **Assumption:** ...

Never silently convert an assumption into a stated fact.

---

## Core principle

The whitepaper should answer one question above all others:

> **Can a technically capable reader understand what this system does, how it works, why it was designed this way, what evidence supports it, and where it can fail?**

If yes, the whitepaper is doing its job.

---
name: crypto-whitepaper-writer
description: Write a credible, well-structured whitepaper for any crypto/blockchain project (L1 chain, DeFi protocol, oracle network, stablecoin, token system) — grounded in the structural and rhetorical patterns of Bitcoin, Ethereum, Uniswap, Chainlink, and MakerDAO, not generic ICO-hype templates. Use whenever asked to draft, outline, or review a crypto/Web3 whitepaper.
---

# Crypto Whitepaper Writer

## Why this skill exists

Most AI-generated crypto whitepapers read like marketing decks: vague "revolutionary" language,
unbacked security claims, a roadmap standing in for proof, tokenomics as decoration. The five
most-cited whitepapers in the industry — Bitcoin, Ethereum, Uniswap, Chainlink, MakerDAO — share a
different discipline instead: problem-first framing, incremental mechanism-building, named threat
models, and per-actor incentive analysis. This skill encodes that discipline so the output reads
like engineering, not a pitch.

See `reference.md` for the full research base: archetype skeletons, craft principles, anti-patterns,
and the pre-publish checklist. Read it before drafting.

## Step 1 — Gather inputs before writing a word

Do not start drafting until you have, from the user:

- **The problem** this project solves, in one sentence, with a concrete scenario of what fails
  without it.
- **The project archetype** — the closest match in `reference.md` → Archetypes: base-layer
  consensus/settlement, DeFi mechanism (AMM/lending/derivatives), oracle/coordination network,
  stablecoin/collateral system, or application-layer protocol/token system.
- **The core mechanism** — what actually happens on-chain/off-chain, in enough detail to describe a
  state transition or formula, not just a feature list.
- **Token existence and role** — if a token exists, what specific mechanical function does it serve
  (fee payment, collateral, staking/slashing, governance weight)? If the project doesn't need a
  token, say so explicitly rather than inventing tokenomics to look complete.
- **Known limitations / open risks** the team is willing to state honestly.

If any of these is missing or vague, ask before drafting — never fabricate a problem statement, team
background, adoption numbers, or token model to fill a gap.

## Step 2 — Pick the section skeleton, calibrate length

Match the archetype to its skeleton in `reference.md`. Don't force every whitepaper through an
identical template — Bitcoin has no tokenomics section; MakerDAO has no proof-of-work security proof.
Use the shared spine (problem → mechanism → actor/incentive analysis → threat/risk model →
architecture → [governance/token, only if applicable] → limitations → conclusion), and cut whatever
doesn't apply to this project.

Length follows mechanism complexity, not a fixed page count — Bitcoin proves its point in 9 pages;
MakerDAO needs far more because it coordinates more actors and failure modes. Let each section run as
long as the idea needs and no longer (anti-pattern: forced symmetry). If the project has a token or
makes any financial/return-implying claim, include a short disclaimer (Uniswap's precedent) stating
the document is not investment advice.

## Step 3 — Draft section by section, applying the craft principles

Work through `reference.md`'s craft principles as each section gets written. The ones that matter
most in practice:

- Open with a failure scenario, not a mission statement.
- Build the mechanism from a minimal model upward — don't state the final design cold.
- Every security or performance claim gets a number, threshold, or named proof — never an adjective
  alone ("highly secure" is not a claim).
- Every incentive-driven actor (miner, LP, oracle node, keeper, validator) gets its own paragraph
  naming exactly what they earn and what punishes defection.
- Name specific attack vectors and pair each with its specific countermeasure.
- Include at least one worked, traceable example — a transaction walkthrough, a numeric calculation,
  a step-by-step lifecycle.
- If this design revises or extends a known predecessor, write it as an explicit delta (what changed
  and why), not a from-scratch re-explanation.

## Step 4 — Run the anti-pattern filter before showing a draft

Scan against `reference.md`'s anti-pattern list. Any hit is a reason to rewrite the line, not soften
it: price predictions or market-cap claims, unverifiable team/advisor credentials used as an
argument, roadmap phases presented as proof of viability, a tokenomics table with no stated
mechanical purpose, novelty claimed without naming what came before, a security claim with no threat
model behind it, a missing limitations section, buzzwords substituting for a mechanism description.

## Step 5 — Self-check and disclose gaps

Before finalizing:

- Confirm every numeric or technical claim traces to something the user provided or a cited external
  source — flag anything you inferred rather than were told.
- Confirm a limitations/risks section exists and isn't hollow.
- Run `reference.md`'s pre-publish checklist and state the result (pass/fail per item, or a
  self-rating) to the user before calling the draft done — don't ship a whitepaper without surfacing
  what's unresolved.

## Output format

Markdown, sections matching the chosen archetype skeleton, an abstract at the top, references/sources
at the bottom if external material was used. No emoji, no bolded label scaffolding (`Problem:`,
`Solution:`), no forced symmetry between sections — a simple idea gets a short section, a hard one
gets a long one, exactly as the five reference papers do.

Cite every external claim (a cryptographic primitive, a competitor's known limitation, a market fact)
inline with a bracketed marker (e.g. `[1]`) resolving to a numbered reference list at the end — never
assert an outside fact with no traceable source. See `reference.md` → Calibration examples for what a
compliant vs. non-compliant sentence looks like before you draft the real thing.

i want to create the best strategy which will take only winning trades and as many as possible in a day in propfirm challenges using ctrader which i will connect using mcp server of ctrader backtest it with the data available in the ctrader and create a strategy in c#

I want you to act like the best AI video editor in the world while am working on campus life add a water map write up that says @campus life let the dialogue be very funny 

create me a proper documentation of this whole website that i have created in such a way that if s new person comes at my place so he/she can be able to understand what is happeing here and be able to use it efficiently 

give me a marketing video for spare parts slaes company 

I want you to act the the best brave thinker in the world while looking for solution to each world current problem on earth.make it easy to assimilate with the best solution in a way to make money online procedure to take how to reach out to people which app will the people that need the solution be how to approach them even if there is need to create appp teach me am ready to learn 

I want to change the attire of this image to something with good clothes and should change the background to some famous places

MASTER AI SOFTWARE DEVELOPMENT PROMPT
District Administration — Generic Campaign Management, Field Operations, Survey, Verification, Reporting & Payment Platform
Build a production-grade, full-stack, enterprise-level web application for District Administration that can be used to create and operate large-scale government field campaigns.
The platform must support campaigns involving:
•	One department.
•	Multiple departments.
•	Joint inter-department teams.
•	Senior officers.
•	Supervisors.
•	Field officers.
•	Reserve/backup employees.
•	Institutions.
•	Villages.
•	Wards.
•	Mohallas.
•	Households.
•	Other configurable target entities.
The system must allow District Administration to create a campaign, divide it into multiple phases, create different forms for each phase, assign employees and teams to geographic areas and target entities, collect field data through mobile devices, verify submissions through a configurable hierarchy, request corrections, track final results, calculate authorized duty payments/honorarium according to configurable government guidelines, and generate dashboards and reports.
The system must be generic.
Do not hard-code the application for Census only.
Census 2027 should be implemented as an example campaign type.
Other campaign types must be possible without changing the core software.
Examples:
•	Census 2027.
•	School Inspection.
•	Hospital Inspection.
•	Road Survey.
•	Flood Damage Survey.
•	Village Survey.
•	PDS Inspection.
•	Anganwadi Inspection.
•	Infrastructure Survey.
•	Government Scheme Verification.
•	Disaster Assessment.
•	Public Grievance Field Verification.
•	Any future district campaign.
________________________________________
1. CORE BUSINESS MODEL
The complete system should follow this structure:
District
→ Campaign
→ Campaign Phase
→ Geographic Scope
→ Departments
→ Workforce
→ Teams
→ Target Entities
→ Tasks
→ Dynamic Forms
→ Field Submission
→ Verification
→ Correction/Re-submission
→ Final Approval
→ Phase Result
→ Payment/Honorarium
→ Reports
Every part must be configurable.
________________________________________
2. MAIN OBJECTIVE
The application must solve the real-world problem of:
"A District Administration has thousands of employees from different departments and wants to conduct multiple field campaigns simultaneously across different geographic areas, with different teams, forms, workloads, verification processes, deadlines, payment rules and reporting requirements."
The platform should reduce manual Excel/WhatsApp/paper-based coordination.
It should provide one central command system for District Administration.
________________________________________
3. MULTIPLE CAMPAIGNS
District Administration must be able to run multiple campaigns simultaneously.
Example:
•	Census 2027.
•	School Inspection.
•	Road Survey.
•	Flood Assessment.
•	Drinking Water Survey.
Each campaign is independent.
Each campaign can have:
•	Different departments.
•	Different employees.
•	Different geographic areas.
•	Different forms.
•	Different workflow.
•	Different deadlines.
•	Different payment rules.
•	Different target entities.
•	Different reporting structure.
________________________________________
4. MULTI-PHASE CAMPAIGN
Every campaign can have multiple phases.
Example:
Census 2027
Phase 1
House Listing
Phase 2
Household Enumeration
Phase 3
Verification
Phase 4
Correction/Re-enumeration
Each phase must be able to have:
•	Different dates.
•	Different forms.
•	Different workforce.
•	Different teams.
•	Different geographic assignments.
•	Different instructions.
•	Different workload.
•	Different verification workflow.
•	Different payment rules.
•	Different results.
Do not assume that all phases use the same employees or form.
________________________________________
5. CAMPAIGN TYPES
Create configurable campaign types.
Examples:
•	Census.
•	Inspection.
•	Survey.
•	Verification.
•	Enumeration.
•	Monitoring.
•	Assessment.
•	Disaster response.
•	Infrastructure survey.
•	Custom.
Admin can create a new campaign type.
________________________________________
6. ORGANIZATIONAL HIERARCHY
The organization must be configurable.
Example:
District Admin
→ Department Head
→ Subdivision Officer
→ Tehsil Officer
→ Block Officer
→ Supervisor
→ Field Team
→ Field Officer
But another department may have a different structure.
Therefore do not hard-code hierarchy levels.
Use:
OrganizationNode
with configurable parent/child relationships.
________________________________________
7. GEOGRAPHIC HIERARCHY
Support flexible geographic hierarchy.
Example rural:
State
→ District
→ Subdivision
→ Tehsil
→ Block
→ Village
→ Mohalla/Hamlet
→ Household
Example urban:
State
→ District
→ Municipality/Nagar Palika
→ Zone
→ Ward
→ Mohalla
→ Household
The system must support both.
Do not assume every area has the same structure.
________________________________________
8. GEOGRAPHIC MASTER DATA
Create geographic master data management.
Admin can manage:
•	District.
•	Subdivision.
•	Tehsil.
•	Block.
•	Municipality.
•	Ward.
•	Village.
•	Mohalla.
•	GPS coordinates.
•	Boundary/polygon where available.
Support bulk import through:
•	CSV.
•	Excel.
•	Government master-data API where available.
Validate duplicate geographic records.
________________________________________
9. TARGET ENTITY ENGINE
Do not make "household" the only target.
Create a generic target entity system.
Possible entities:
•	Household.
•	Person.
•	School.
•	Hospital.
•	Road.
•	Village.
•	Shop.
•	Anganwadi.
•	Government building.
•	Water source.
•	Custom entity.
Example:
Campaign:
School Inspection
Target:
School
Campaign:
Census
Target:
Household
Campaign:
Road Survey
Target:
Road segment.
________________________________________
10. ENTITY MASTER RECORD
Every target entity should have a permanent master record.
Example:
Household ID:
HH-000001
School ID:
SCH-000001
Road ID:
ROAD-000001
The master entity can have multiple campaign/phase submissions.
This prevents duplication.
________________________________________
11. HOUSEHOLD MODEL
For Census-type campaigns support:
Household
→ Household members
→ Individual person records
The household can have:
•	Household ID.
•	Address.
•	Geographic hierarchy.
•	House number.
•	GPS.
•	Status.
•	Source.
•	Phase history.
The individual/person structure must support variable number of persons.
________________________________________
12. EMPLOYEE MASTER
Create a central employee database.
Fields:
•	Employee ID.
•	Name.
•	Mobile number.
•	Designation.
•	Department.
•	Office.
•	Posting location.
•	District.
•	Subdivision.
•	Tehsil.
•	Block.
•	Role.
•	Employment status.
•	Availability.
•	Reserve status.
•	Training status.
Employee ID should be unique.
Mobile number should be unique where applicable.
________________________________________
13. BULK EMPLOYEE IMPORT
Support import of thousands of employees.
Formats:
•	Excel.
•	CSV.
Before import:
•	Validate.
•	Detect duplicate Employee IDs.
•	Detect duplicate mobile numbers.
•	Detect missing fields.
•	Detect invalid departments.
•	Show row-level errors.
Allow:
Import Valid Records
without losing valid records because of invalid rows.
________________________________________
14. EMPLOYEE AVAILABILITY
Employee status:
•	Available.
•	Assigned.
•	On Duty.
•	On Leave.
•	Unavailable.
•	Reserve.
•	Activated Reserve.
•	Released.
•	Suspended.
Campaign assignment must check availability.
Prevent incompatible double assignment.
________________________________________
15. MULTI-DEPARTMENT CAMPAIGNS
A campaign can include multiple departments.
Example:
School Inspection:
•	Education.
•	PWD.
•	Food.
•	Revenue.
Each department can have different responsibilities.
________________________________________
16. JOINT TEAMS
Create a team engine.
A team can contain employees from different departments.
Example:
Team 001:
•	Revenue employee.
•	Education employee.
•	PWD employee.
Each team has:
•	Team ID.
•	Team leader.
•	Members.
•	Department.
•	Geographic responsibility.
•	Campaign.
•	Phase.
•	Status.
________________________________________
17. TEAM FORMATION
Allow:
Manual
Admin selects employees.
Automatic
System creates teams based on configured rules.
Rules may include:
•	Team size.
•	Department combination.
•	Geographic area.
•	Designation.
•	Skill.
•	Availability.
•	Workload.
________________________________________
18. TEAM LEADER
Team leader can:
•	See team members.
•	See assigned tasks.
•	Monitor progress.
•	Review team-level work where authorized.
•	Report employee absence.
•	Request replacement.
•	Submit team reports.
Do not automatically grant access to all data just because someone is team leader.
Permissions must still apply.
________________________________________
19. RESERVE EMPLOYEE SYSTEM
Every large campaign should support reserve employees.
Reserve employees can replace active staff when necessary.
Reasons:
•	Leave.
•	Illness.
•	Transfer.
•	Emergency.
•	Administrative requirement.
•	Other authorized reasons.
Workflow:
Active Employee
→ Unavailable
→ Supervisor reports
→ Authorized officer approves
→ Reserve employee selected
→ Reserve activated
→ Assignment transferred
→ Audit record created.
________________________________________
20. RESERVE TEAM
Support reserve teams in addition to reserve individuals.
Example:
Active Team:
Team 001
Reserve Team:
Team R001
If an entire team becomes unavailable, the reserve team can be activated.
________________________________________
21. WORKLOAD MANAGEMENT
Before launching a campaign phase, show:
Total target entities.
Required workforce.
Available workforce.
Reserve workforce.
Expected workload per employee.
Expected workload per team.
Example:
Targets:
1,000,000
Teams:
10,000
Average:
100 targets/team.
Allow authorized admins to adjust distribution.
________________________________________
22. WORKLOAD BALANCING
Support:
•	Equal distribution.
•	Geographic distribution.
•	Random distribution.
•	Manual distribution.
•	Skill-based distribution.
•	Workload balancing.
The system should detect overloaded employees/teams.
Example:
Employee A:
300 tasks
Employee B:
80 tasks
Show warning.
________________________________________
23. RANDOM ASSIGNMENT
Support random assignment where required.
Example:
10,000 schools
1,000 officers
System randomly assigns schools.
Prevent duplicate assignments.
Allow administrators to preview before activation.
Maintain assignment history.
________________________________________
24. GEOGRAPHIC ASSIGNMENT
Tasks can be assigned based on:
•	District.
•	Subdivision.
•	Tehsil.
•	Block.
•	Village.
•	Ward.
•	Mohalla.
•	GPS boundary.
Support polygon-based geographic assignment where feasible.
________________________________________
25. CAMPAIGN CREATION WIZARD
Create a professional multi-step wizard.
Step 1
Campaign details.
Step 2
Campaign type.
Step 3
Geographic scope.
Step 4
Departments.
Step 5
Workforce.
Step 6
Teams.
Step 7
Target entities.
Step 8
Form.
Step 9
Assignment.
Step 10
Verification workflow.
Step 11
Payment rules.
Step 12
Guidelines/documents.
Step 13
Preview.
Step 14
Launch.
________________________________________
26. CAMPAIGN VALIDATION BEFORE LAUNCH
Before launch check:
•	No target entities.
•	No teams.
•	No officers.
•	Missing form.
•	Missing mandatory questions.
•	Missing geographic assignment.
•	Missing verification workflow.
•	Missing payment configuration where required.
•	Employee conflicts.
•	Duplicate assignments.
•	Insufficient workforce.
•	Invalid dates.
Show warnings and errors.
Do not allow launch when critical requirements are missing.
________________________________________
27. DYNAMIC FORM BUILDER
District Admin must create forms without coding.
Question types:
•	Short text.
•	Long text.
•	Integer.
•	Decimal.
•	Percentage.
•	Currency/amount.
•	Date.
•	Date/time.
•	Yes/No.
•	Radio.
•	Checkbox.
•	Dropdown.
•	Multi-select.
•	Image.
•	Multiple image.
•	Video.
•	File.
•	GPS.
•	Signature.
•	Rating.
•	Table.
•	Repeating group.
•	Calculated field.
________________________________________
28. FORM SECTIONS
Forms can contain sections.
Example:
School Inspection:
1.	School Information.
2.	Infrastructure.
3.	PWD.
4.	Food.
5.	Education.
6.	Final Remarks.
________________________________________
29. CONDITIONAL QUESTIONS
Support rules.
Example:
IF:
Building damaged = YES
THEN:
Show:
•	Damage type.
•	Damage severity.
•	Damage photo.
•	Repair estimate.
Otherwise hide these fields.
Create a visual condition builder.
________________________________________
30. REPEATING GROUPS
For Census:
Household:
Number of members = 6
Automatically create:
Person 1
Person 2
Person 3
Person 4
Person 5
Person 6.
Support nested repeating data where required.
________________________________________
31. FORM VALIDATION
Each question can have:
•	Required.
•	Minimum.
•	Maximum.
•	Length.
•	Regex.
•	Allowed options.
•	Dependency.
•	Evidence requirement.
•	GPS requirement.
Validation must happen:
Frontend + Backend
Never trust frontend validation alone.
________________________________________
32. FORM VERSIONING
Forms must be versioned.
Example:
Form v1
Form v2
Historical submissions remain associated with their original form version.
Changing a form must not change old submissions.
________________________________________
33. CAMPAIGN FORM
Each phase can have its own form.
Example:
Campaign:
Census 2027
Phase 1:
Form A
Phase 2:
Form B
Phase 3:
Form C
________________________________________
34. FIELD OFFICER MOBILE APP
Build a mobile-first PWA.
Field employee dashboard:
Campaigns
→ Active Phase
→ Assigned Area
→ Assigned Tasks
→ Completed
→ Pending
→ Corrections
→ Drafts
→ Sync
→ Notifications
________________________________________
35. FIELD TASK
Each task contains:
•	Task ID.
•	Campaign.
•	Phase.
•	Target.
•	Geographic location.
•	Assigned team.
•	Assigned employee.
•	Deadline.
•	Priority.
•	Status.
•	Instructions.
________________________________________
36. TASK STATUS
Use:
•	Not Started.
•	Assigned.
•	Accepted.
•	In Progress.
•	Draft.
•	Submitted.
•	Under Verification.
•	Correction Required.
•	Resubmitted.
•	Approved.
•	Rejected.
•	Reassigned.
•	Overdue.
•	Completed.
________________________________________
37. FIELD DATA COLLECTION
Field officer should be able to:
•	Open task.
•	Start task.
•	Fill form.
•	Save draft.
•	Resume later.
•	Capture GPS.
•	Capture image.
•	Upload video.
•	Add remarks.
•	Submit.
________________________________________
38. GPS
When configured:
Capture:
•	Latitude.
•	Longitude.
•	Accuracy.
•	Timestamp.
Optionally calculate distance from target location.
Configurable:
•	Warning.
•	Supervisor review.
•	Block submission.
________________________________________
39. PHOTO
Support:
•	Camera.
•	Gallery.
•	Multiple images.
•	Compression.
•	Preview.
•	Retake.
Associate image with:
•	Campaign.
•	Phase.
•	Task.
•	Question.
•	Employee.
________________________________________
40. VIDEO
Support:
•	Record.
•	Select.
•	Preview.
•	Upload.
•	Progress.
•	Retry.
•	Maximum size.
•	Maximum duration.
Use object storage.
Do not store large videos directly in PostgreSQL.
________________________________________
41. OFFLINE MODE
Mobile application must work with poor connectivity.
Use:
•	PWA.
•	IndexedDB.
•	Local draft.
•	Offline task list.
•	Sync queue.
Status:
Online
Offline
Syncing
Synced
Failed.
________________________________________
42. OFFLINE CONFLICT MANAGEMENT
If the same record changes from multiple sources:
Do not silently overwrite.
Create conflict:
Conflict requires review.
Maintain version history.
________________________________________
43. SUBMISSION
Before final submission:
Show review page.
Example:
Required fields:
✓
GPS:
✓
Required images:
✓
Validation:
✓
Then:
Submit
Server returns:
Submission ID.
Never show successful submission before server confirmation.
________________________________________
44. VERIFICATION ENGINE
Create configurable workflow.
Example:
Field Officer
→ Supervisor
→ Tehsil Officer
→ Subdivision Officer
→ Department Head
→ District Admin
But administrators can configure different levels.
________________________________________
45. VERIFICATION ACTIONS
Reviewer can:
•	Approve.
•	Reject.
•	Request correction.
•	Add comment.
•	Escalate.
•	Reassign.
•	View history.
________________________________________
46. CORRECTION WORKFLOW
Example:
Reviewer:
"Please upload a clear photograph."
Status:
Correction Required.
Employee receives notification.
Employee edits only permitted fields.
Resubmits.
Reviewer receives notification.
________________________________________
47. DATA VERSIONING
Every submission must preserve:
•	Version.
•	Answers.
•	Files.
•	GPS.
•	User.
•	Timestamp.
•	Changes.
•	Reason.
Never destroy historical versions.
________________________________________
48. FINAL APPROVAL
Only approved records should be included in final results when the campaign requires final approval.
Allow reports to distinguish:
•	Preliminary.
•	Submitted.
•	Verified.
•	Final Approved.
________________________________________
49. DATA QUALITY ENGINE
Create automatic quality checks.
Examples:
•	Duplicate household.
•	Duplicate task.
•	Missing GPS.
•	Impossible values.
•	Inconsistent totals.
•	Required evidence missing.
•	Conflicting phase data.
•	Unusual completion speed.
•	Repeated identical GPS coordinates where suspicious.
•	Excessive submissions in a short time.
Flag anomalies for review.
Do not automatically accuse an employee of misconduct.
Mark:
Data Quality Exception
________________________________________
50. EXCEPTION MANAGEMENT
Create a central Exception Center.
Examples:
•	Missing household.
•	Duplicate household.
•	GPS issue.
•	Incomplete form.
•	Conflicting data.
•	Overdue task.
•	Employee unavailable.
•	Team unavailable.
•	Payment failure.
•	Sync failure.
Admin can assign exceptions.
________________________________________
51. CENSUS 2027 EXAMPLE
Create Census 2027 as a sample campaign.
Do not invent official Census questions.
Use placeholder/configurable forms or officially supplied forms.
Example structure:
Census 2027
→ Phase 1: House Listing
→ Phase 2: Enumeration
→ Phase 3: Verification
→ Phase 4: Correction
Each phase has different forms and possibly different workforce.
________________________________________
52. CENSUS GEOGRAPHIC STRUCTURE
Support:
District
→ Subdivision
→ Tehsil
→ Municipality / Nagar Palika
→ Ward
→ Village
→ Mohalla
→ Household
The actual hierarchy must be configurable.
________________________________________
53. CENSUS JOINT TEAM
Example:
Team 001
Area:
Ward 10 / Mohalla A
Members:
•	Education Department employee.
•	Revenue Department employee.
•	Municipal employee.
The team visits households within its assigned area.
________________________________________
54. HOUSEHOLD CENSUS FLOW
Team opens:
Household HH-000123
System displays:
•	Location.
•	Address.
•	Previous phase information if authorized.
•	Current phase form.
Team collects required information.
Submits.
Result goes through configured verification workflow.
________________________________________
55. CENSUS MULTI-PHASE WORKLOAD
Support distributing work over multiple phases to reduce employee workload.
Example:
Phase 1:
Employee Group A
Phase 2:
Employee Group B
Phase 3:
Employee Group C
Or the same employees can participate in multiple phases.
The system must support both.
________________________________________
56. PAYMENT/HONORARIUM ENGINE
Create a dedicated payment module.
IMPORTANT:
Never hard-code government payment amounts.
Payment amounts must come from authorized configurable rules based on the applicable government order/guideline.
________________________________________
57. PAYMENT RULE
Payment rule fields:
•	Campaign.
•	Phase.
•	Role.
•	Department if applicable.
•	Duty type.
•	Calculation method.
•	Amount/rate.
•	Effective date.
•	Government order reference.
•	Version.
•	Approval status.
________________________________________
58. PAYMENT CALCULATION
Possible calculation models:
•	Fixed amount.
•	Per day.
•	Per task.
•	Per approved household.
•	Role-based.
•	Phase-based.
•	Component-based.
Do not assume these are legally applicable.
The administrator configures the permitted calculation method according to official rules.
________________________________________
59. PAYMENT ELIGIBILITY
Example:
Assignment
↓
Duty completed
↓
Required work completed
↓
Submission accepted/approved
↓
Eligibility generated
↓
Payment approval
↓
Payment processing
↓
Paid
Exact rules must be configurable.
________________________________________
60. EMPLOYEE PAYMENT DASHBOARD
Employee sees:
Campaign:
Census 2027
Phase:
Phase 1
Duty:
Completed
Eligibility:
Eligible
Payment:
₹XXXX
Status:
Pending / Approved / Processing / Paid.
Sensitive financial information must be protected.
________________________________________
61. PAYMENT STATUS
Statuses:
•	Not Eligible.
•	Pending Eligibility.
•	Eligible.
•	Pending Approval.
•	Approved.
•	Processing.
•	Paid.
•	Failed.
•	Returned.
•	On Hold.
•	Disputed.
________________________________________
62. PAYMENT REMINDERS
If payment is pending:
Send:
•	In-app notification.
•	SMS where configured.
•	Email where configured.
Example:
Your approved campaign duty payment is still pending processing.
Do not make unverified claims about payment timing.
________________________________________
63. PAYMENT EXCEPTIONS
Support:
•	Failed payments.
•	Incorrect records.
•	Missing approval.
•	Duplicate payment prevention.
•	Hold.
•	Retry.
•	Resolution.
Maintain complete audit trail.
________________________________________
64. PAYMENT DUPLICATE PREVENTION
Prevent duplicate payment for:
Employee + Campaign + Phase + Duty
unless explicitly allowed by an authorized adjustment process.
________________________________________
65. ATTENDANCE / DUTY PROOF
Where required by campaign rules, support duty attendance.
Possible methods:
•	Start duty.
•	End duty.
•	GPS.
•	Team leader confirmation.
•	Supervisor approval.
•	Task completion.
Do not assume attendance equals payment eligibility.
Make it configurable.
________________________________________
66. TRAINING
Track:
•	Training assigned.
•	Training completed.
•	Training date.
•	Training material.
•	Assessment.
•	Certification.
A campaign phase can optionally require training before assignment.
________________________________________
67. GUIDELINES / DOCUMENTS
Campaign administrators can upload:
•	Government orders.
•	Guidelines.
•	SOPs.
•	Training documents.
•	Circulars.
•	Forms.
•	Payment orders.
Documents should be versioned.
________________________________________
68. NOTIFICATION ENGINE
Support:
•	In-app.
•	SMS.
•	Email.
•	Push notifications.
Notifications:
•	New task.
•	New campaign.
•	Phase starting.
•	Deadline.
•	Overdue.
•	Correction.
•	Approval.
•	Reassignment.
•	Reserve activation.
•	Payment update.
________________________________________
69. ESCALATION ENGINE
Create configurable escalation.
Example:
Task overdue by 2 days:
→ Supervisor notification.
Overdue by 4 days:
→ Tehsil Officer.
Overdue by 7 days:
→ District Admin.
The escalation schedule must be configurable.
________________________________________
70. REMINDER ENGINE
Support scheduled reminders.
Examples:
7 days before deadline.
3 days before.
1 day before.
Due date.
Overdue.
Payment pending for X days.
________________________________________
71. DISTRICT COMMAND DASHBOARD
Create a professional command center.
Show:
Campaigns
Total.
Active.
Completed.
Delayed.
Workforce
Total.
Assigned.
Available.
Reserve.
Unavailable.
Tasks
Total.
Completed.
Pending.
Overdue.
Correction.
Verification
Submitted.
Under review.
Approved.
Rejected.
Payment
Eligible.
Approved.
Paid.
Pending.
Failed.
________________________________________
72. GEOGRAPHIC DRILL-DOWN
Dashboard:
District
↓
Subdivision
↓
Tehsil
↓
Village/Ward
↓
Mohalla
↓
Household
At every level:
•	Total.
•	Assigned.
•	Completed.
•	Pending.
•	Verified.
•	Exceptions.
________________________________________
73. MAP
Provide interactive map.
Show:
•	Assigned areas.
•	Completed targets.
•	Pending targets.
•	Exceptions.
•	GPS submissions where authorized.
Use clustering for large datasets.
Do not attempt to render millions of points simultaneously.
________________________________________
74. DEPARTMENT DASHBOARD
Department Head sees:
•	Campaign participation.
•	Employees.
•	Teams.
•	Workload.
•	Completion.
•	Verification.
•	Exceptions.
•	Payment.
Only authorized department data.
________________________________________
75. SUBDIVISION / TEHSIL DASHBOARD
Show local progress.
Example:
Tehsil A:
Targets: 100,000
Completed: 92,000
Pending: 8,000
Completion:
92%
________________________________________
76. TEAM DASHBOARD
Team Leader sees:
•	Members.
•	Assigned targets.
•	Completed.
•	Pending.
•	Corrections.
•	Overdue.
•	Sync status.
________________________________________
77. EMPLOYEE DASHBOARD
Employee sees:
•	My campaigns.
•	My phases.
•	My tasks.
•	My progress.
•	Corrections.
•	Notifications.
•	Payment.
•	Guidelines.
________________________________________
78. REPORTING ENGINE
Create configurable reports.
Reports:
•	Campaign.
•	Phase.
•	Department.
•	Employee.
•	Team.
•	Geography.
•	Target entity.
•	Verification.
•	Exception.
•	Payment.
•	Workforce.
•	Productivity.
________________________________________
79. REPORT FILTERS
Filters:
•	Campaign.
•	Phase.
•	Date.
•	Department.
•	Employee.
•	Team.
•	District.
•	Subdivision.
•	Tehsil.
•	Village.
•	Ward.
•	Mohalla.
•	Status.
________________________________________
80. EXPORT
Support:
•	Excel.
•	CSV.
•	PDF.
Large reports must be generated asynchronously.
________________________________________
81. REPORT SCHEDULING
Allow authorized users to schedule reports.
Example:
Every day at 6 PM:
District Campaign Progress Report
Send to authorized users.
________________________________________
82. DATA ACCESS CONTROL
Use:
RBAC + Geographic Scope + Department Scope + Campaign Scope
Example:
Field Officer:
Only assigned tasks.
Tehsil Officer:
Authorized tehsil.
Department Head:
Authorized department.
District Admin:
District-wide.
Never rely only on frontend restrictions.
________________________________________
83. SUPER ADMIN
Super Admin manages:
•	Districts.
•	Departments.
•	Users.
•	Roles.
•	Permissions.
•	System settings.
•	Master data.
•	Integrations.
________________________________________
84. DISTRICT ADMIN
District Admin can:
•	Create campaigns.
•	Create phases.
•	Create forms.
•	Select departments.
•	Manage workforce.
•	Create teams.
•	Assign areas.
•	Assign tasks.
•	Configure verification.
•	Configure payment rules where authorized.
•	Monitor progress.
•	Approve/review data.
•	Generate reports.
________________________________________
85. DEPARTMENT HEAD
Can:
•	View department campaigns.
•	Manage department workforce.
•	Review submissions.
•	Verify data.
•	Monitor department performance.
•	Generate authorized reports.
________________________________________
86. FIELD OFFICER
Can:
•	Login.
•	View assigned duties.
•	Collect field data.
•	Capture GPS.
•	Capture media.
•	Save drafts.
•	Submit.
•	Correct.
•	Resubmit.
•	View payment status.
•	View guidelines.
________________________________________
87. PAYMENT OFFICER
Can:
•	Review eligibility.
•	Approve payment.
•	Process payment.
•	View failures.
•	Retry authorized payments.
•	Generate payment reports.
Do not give payment officers unnecessary household-data access.
________________________________________
88. SYSTEM SECURITY
Implement:
•	Password hashing.
•	Secure authentication.
•	OTP.
•	Session security.
•	JWT or secure session architecture.
•	Refresh token rotation where applicable.
•	Rate limiting.
•	API authorization.
•	Input validation.
•	File validation.
•	Secure headers.
•	CORS.
•	CSRF protection where applicable.
•	SQL injection protection.
•	XSS protection.
•	Audit logs.
________________________________________
89. DATA PRIVACY
Collect only officially required information.
Sensitive information should have:
•	Strict access control.
•	Encryption where appropriate.
•	Audit logs.
•	Retention rules.
•	Export restrictions.
Do not display sensitive household/person information on public dashboards.
________________________________________
90. AUDIT LOG
Record every important operation.
Examples:
•	Login.
•	OTP.
•	Campaign creation.
•	Phase creation.
•	Form changes.
•	Employee assignment.
•	Team creation.
•	Household assignment.
•	Submission.
•	Correction.
•	Approval.
•	Reassignment.
•	Reserve activation.
•	Payment calculation.
•	Payment approval.
•	Payment processing.
•	Export.
Audit log should be immutable for normal users.
________________________________________
91. SYSTEM LOGGING
Use structured application logs.
Separate:
•	Application logs.
•	Security logs.
•	Audit logs.
•	Error logs.
Do not expose internal errors to users.
________________________________________
92. DATABASE
Use:
PostgreSQL
ORM:
Prisma
Design a normalized schema.
Important entities:
•	State.
•	District.
•	Department.
•	OrganizationNode.
•	GeographicNode.
•	User.
•	Employee.
•	Role.
•	Permission.
•	Campaign.
•	CampaignPhase.
•	CampaignDepartment.
•	CampaignGeography.
•	TargetEntity.
•	Household.
•	Person.
•	Team.
•	TeamMember.
•	ReserveEmployee.
•	Task.
•	TaskAssignment.
•	Form.
•	FormVersion.
•	FormSection.
•	FormQuestion.
•	FormOption.
•	FormCondition.
•	Submission.
•	SubmissionVersion.
•	SubmissionAnswer.
•	SubmissionFile.
•	GPSRecord.
•	Verification.
•	CorrectionRequest.
•	Exception.
•	PaymentRule.
•	PaymentRuleVersion.
•	EmployeePayment.
•	PaymentComponent.
•	PaymentTransaction.
•	Notification.
•	GuidelineDocument.
•	Training.
•	AuditLog.
•	Report.
•	ReportJob.
Use appropriate:
•	Foreign keys.
•	Unique constraints.
•	Indexes.
•	Soft deletion where appropriate.
•	Timestamps.
________________________________________
93. DATA RETENTION
Build configurable retention policies.
Different records may have different retention requirements.
Do not automatically delete official records without an authorized retention policy.
________________________________________
94. BACKUP
Design:
•	Automated database backups.
•	Point-in-time recovery where supported.
•	Object storage backup.
•	Backup monitoring.
•	Restore testing.
________________________________________
95. DISASTER RECOVERY
Document:
•	Recovery procedure.
•	Backup restoration.
•	Database recovery.
•	File recovery.
•	Queue recovery.
•	Disaster scenarios.
________________________________________
96. SCALABILITY
Design for:
•	50,000+ employees.
•	Millions of targets.
•	Millions of submissions.
•	Large file uploads.
•	Thousands of concurrent mobile users.
Use:
•	Pagination.
•	Cursor pagination where appropriate.
•	Database indexes.
•	Redis.
•	Queue workers.
•	Object storage.
•	Background jobs.
•	Horizontal scaling.
•	Database connection pooling.
________________________________________
97. BACKGROUND JOB SYSTEM
Use:
Redis + BullMQ or equivalent.
Jobs:
•	Report generation.
•	Excel export.
•	PDF generation.
•	Notifications.
•	SMS.
•	Email.
•	Image processing.
•	Video processing.
•	Payment processing integration.
•	Reminder jobs.
•	Escalation.
•	Data aggregation.
________________________________________
98. FILE STORAGE
Use:
•	S3-compatible storage.
Store only metadata in PostgreSQL.
Metadata:
•	File ID.
•	Name.
•	Type.
•	Size.
•	Storage path.
•	Upload user.
•	Campaign.
•	Phase.
•	Task.
•	Question.
•	Timestamp.
Use signed URLs for private files.
________________________________________
99. MOBILE PERFORMANCE
Optimize for:
•	Low-end Android devices.
•	Slow networks.
•	Limited storage.
•	Intermittent connectivity.
Avoid unnecessary animations.
Keep forms lightweight.
Compress images.
Use resumable uploads where practical.
________________________________________
100. ACCESSIBILITY
Support:
•	High contrast.
•	Large touch targets.
•	Keyboard navigation.
•	Screen readers.
•	Proper labels.
•	Accessible validation messages.
________________________________________
101. USER INTERFACE
Admin desktop:
Sidebar
→ Dashboard
→ Campaigns
→ Phases
→ Workforce
→ Teams
→ Geography
→ Targets
→ Forms
→ Tasks
→ Verification
→ Payments
→ Reports
→ Maps
→ Notifications
→ Audit Logs
→ Settings
Field mobile:
Home
My Campaigns
My Tasks
Corrections
Notifications
Payment
Guidelines
Profile
________________________________________
102. DESIGN STYLE
Use a professional government administration design.
Primary:
Navy/blue.
Secondary:
White/gray.
Use:
•	Tables.
•	Cards.
•	Status badges.
•	Charts.
•	Maps.
•	Progress bars.
Avoid excessive decorative UI.
Prioritize usability.
________________________________________
103. BULK OPERATIONS
Admin must be able to:
•	Import employees.
•	Import geography.
•	Import target entities.
•	Assign teams in bulk.
•	Reassign tasks in bulk.
•	Activate reserve employees in bulk.
•	Generate reports in bulk.
Always show confirmation before large operations.
________________________________________
104. BULK OPERATION SAFETY
For every bulk action:
1.	Preview.
2.	Validate.
3.	Show number of affected records.
4.	Confirm.
5.	Execute.
6.	Show result.
7.	Provide error report.
8.	Record audit event.
________________________________________
105. SEARCH
Global search across authorized data:
•	Campaign.
•	Employee.
•	Team.
•	Household.
•	Institution.
•	Task.
•	Submission.
•	Geographic area.
________________________________________
106. DUPLICATE DETECTION
Detect:
•	Duplicate employee.
•	Duplicate target.
•	Duplicate household.
•	Duplicate task.
•	Duplicate assignment.
•	Duplicate payment.
Do not automatically delete records.
Flag them for review.
________________________________________
107. NOTIFICATION PREFERENCES
Allow users to configure permitted notification preferences.
However, mandatory government alerts cannot be disabled if configured as mandatory.
________________________________________
108. API ARCHITECTURE
Use a clean REST API or equivalent.
Organize APIs by module:
/auth
/users
/employees
/departments
/geography
/campaigns
/phases
/teams
/targets
/tasks
/forms
/submissions
/verifications
/exceptions
/payments
/notifications
/reports
/audit
/files
________________________________________
109. API DOCUMENTATION
Generate:
OpenAPI / Swagger
Document:
•	Authentication.
•	Request.
•	Response.
•	Errors.
•	Permissions.
________________________________________
110. ERROR HANDLING
Use consistent API responses.
Example:
{
"success": false,
"error": {
"code": "VALIDATION_ERROR",
"message": "Required fields are missing."
}
}
Never expose:
•	Database errors.
•	Stack traces.
•	Secrets.
•	Internal infrastructure details.
________________________________________
111. FRONTEND STATE
Use an appropriate state-management/data-fetching strategy.
Use:
•	Server-side fetching where appropriate.
•	Query caching.
•	Optimistic updates only when safe.
•	Offline state.
________________________________________
112. OFFLINE DATA SECURITY
Do not store unnecessary sensitive personal data permanently on the device.
Encrypt/local-protect sensitive offline storage where practical.
Provide device/session expiration.
________________________________________
113. SESSION SECURITY
Support:
•	Session timeout.
•	Device/session management.
•	Logout all devices where authorized.
•	Token revocation.
•	Suspicious login detection.
________________________________________
114. OTP SECURITY
OTP:
•	Expiration.
•	Rate limiting.
•	Attempt limit.
•	Resend cooldown.
•	Secure storage.
•	Audit logging.
Never store OTP in plain text longer than necessary.
________________________________________
115. LOGIN
Support:
Mobile Number
→ OTP for initial verification
→ Password creation
Then:
Mobile Number
→ Password
→ Dashboard
Forgot password:
Mobile
→ OTP
→ New Password
________________________________________
116. GOVERNMENT INTEGRATIONS
Build integration interfaces rather than hard-code external systems.
Possible future integrations:
•	SMS gateway.
•	Government employee master database.
•	Official GIS.
•	Payment/treasury system.
•	Identity/authentication system.
•	Email.
•	Notification gateway.
Use adapters/interfaces so providers can be changed.
________________________________________
117. NO FAKE INTEGRATIONS
If a real government API is not available:
Use a clearly marked development/mock adapter.
Do not pretend that a fake integration is real.
________________________________________
118. PAYMENT INTEGRATION
Payment processing should initially support:
Manual/administrative status
and be architected for future integration with an authorized government payment/treasury system.
Do not invent a government payment API.
________________________________________
119. IMPORT/EXPORT SECURITY
Exports must respect authorization.
Do not allow field officers to export all district data.
Sensitive exports should require additional authorization where appropriate.
Log every export.
________________________________________
120. DATA QUALITY DASHBOARD
Show:
•	Missing data.
•	Invalid data.
•	Duplicate data.
•	GPS exceptions.
•	Correction rates.
•	Rejection rates.
•	Unusual activity.
________________________________________
121. PRODUCTIVITY METRICS
Show:
•	Tasks completed per day.
•	Average task duration.
•	Completion rate.
•	Correction rate.
•	Approval rate.
•	Overdue rate.
Do not use productivity metrics as automatic disciplinary conclusions.
________________________________________
122. CAMPAIGN TEMPLATES
Allow administrators to save:
Campaign Template
Example:
School Inspection Template.
When creating a new campaign:
Use Template
Then modify:
•	Form.
•	Departments.
•	Geography.
•	Workforce.
•	Dates.
•	Payment.
________________________________________
123. FORM TEMPLATE LIBRARY
Allow reusable forms.
Examples:
•	Inspection form.
•	Survey form.
•	Household form.
•	Verification form.
Forms must remain versioned.
________________________________________
124. WORKFLOW TEMPLATE
Allow reusable workflows.
Example:
Field Officer
→ Supervisor
→ Department Head
→ District Admin.
Save as:
Standard Inspection Workflow.
________________________________________
125. PAYMENT TEMPLATE
Allow authorized users to reuse payment structures.
Example:
Field Duty Payment Template.
But each campaign/phase must reference the exact applicable rule/version.
________________________________________
126. CAMPAIGN PAUSE
Admin can pause a campaign.
When paused:
•	No new tasks can start.
•	Existing drafts remain safe.
•	Admin can resume later.
Clearly display:
Campaign Paused.
________________________________________
127. CAMPAIGN EXTENSION
Authorized admin can extend deadline.
Require:
•	New date.
•	Reason.
•	Approval if configured.
Record audit history.
________________________________________
128. TASK REASSIGNMENT
Allow:
Employee A
→ Employee B
Reason:
Employee unavailable.
Maintain full history.
________________________________________
129. TEAM CHANGE
Allow adding/removing team members during campaign with authorization.
Do not rewrite old historical assignments.
________________________________________
130. TARGET REASSIGNMENT
If a household/institution is reassigned:
Maintain:
Old Team
→ New Team
Reason
Date
Authorized By
________________________________________
131. FINALIZATION
When a phase is finalized:
•	Prevent normal editing.
•	Allow authorized correction workflow only.
•	Lock official result.
•	Preserve historical versions.
________________________________________
132. CAMPAIGN CLOSURE
When campaign is completed:
•	Lock operational changes.
•	Finalize reports.
•	Finalize payment eligibility.
•	Preserve audit logs.
•	Archive according to retention policy.
________________________________________
133. REAL-LIFE CENSUS 2027 DEMO
Create development demo:
Campaign:
Census 2027
District:
Demo District
Departments:
•	Revenue.
•	Education.
•	Municipal Administration.
•	Panchayat.
Create sample:
•	2 subdivisions.
•	4 tehsils.
•	3 municipalities.
•	10 villages.
•	20 wards.
•	50 mohallas.
•	500 households.
•	100 employees.
•	20 teams.
•	5 reserve teams.
Create:
Phase 1:
House Listing
Phase 2:
Enumeration
Phase 3:
Verification
Use sample placeholder questions.
Clearly label:
DEMO DATA — NOT OFFICIAL CENSUS DATA
________________________________________
134. END-TO-END DEMO
Demonstrate:
District Admin
→ Creates Census campaign
→ Creates Phase 1
→ Selects departments
→ Imports employees
→ Creates joint teams
→ Assigns geography
→ Loads target households
→ Creates Phase 1 form
→ Configures verification
→ Configures payment rule
→ Launches phase
Field Team
→ Logs in
→ Views households
→ Opens household
→ Completes form
→ Captures GPS
→ Saves draft
→ Submits
Reviewer
→ Reviews
→ Requests correction
Field Team
→ Corrects
→ Resubmits
Reviewer
→ Approves
System
→ Generates final result
→ Generates payment eligibility
→ Shows payment status
District Admin
→ Views dashboard
→ Drills down to household
→ Views map
→ Generates Excel/PDF
→ Views audit history.
________________________________________
135. TESTING
Create:
Unit Tests
For:
•	Assignment.
•	Permissions.
•	Form validation.
•	GPS.
•	Payment calculation.
•	Workflow.
Integration Tests
For:
•	Authentication.
•	Campaign.
•	Teams.
•	Forms.
•	Submission.
•	Verification.
•	Payment.
E2E Tests
Test complete campaign lifecycle.
________________________________________
136. LOAD TESTING
Test realistic loads.
At minimum test:
•	50,000 employees.
•	Large task volumes.
•	Large submission volumes.
•	Concurrent mobile users.
•	Large report generation.
•	Large file uploads.
Identify bottlenecks.
________________________________________
137. DATABASE INDEXING
Create indexes for frequently queried:
•	Employee ID.
•	Mobile.
•	Campaign ID.
•	Phase ID.
•	Team ID.
•	Geographic ID.
•	Target ID.
•	Task status.
•	Submission status.
•	Payment status.
•	Created date.
Review query plans for large tables.
________________________________________
138. ARCHITECTURE
Preferred stack:
Frontend
Next.js
React
TypeScript
Tailwind CSS
shadcn/ui
PWA
IndexedDB
Backend
NestJS
TypeScript
Database
PostgreSQL
Prisma
Cache / Queue
Redis
BullMQ
Storage
S3-compatible storage
Maps
Provider abstraction supporting:
OpenStreetMap / Mapbox / Google Maps
________________________________________
139. PROJECT STRUCTURE
Use a clean modular architecture.
Example:
/apps
/web
/api
/packages
/ui
/types
/config
/validation
/infrastructure
/docs
/tests
Keep business logic separate from UI.
________________________________________
140. ENVIRONMENT VARIABLES
Create:
.env.example
Include:
DATABASE_URL
REDIS_URL
JWT_SECRET
S3_ENDPOINT
S3_ACCESS_KEY
S3_SECRET_KEY
S3_BUCKET
SMS_PROVIDER
SMS_API_KEY
SMS_SENDER_ID
EMAIL_PROVIDER
EMAIL_API_KEY
MAP_PROVIDER
MAP_API_KEY
Never commit real secrets.
________________________________________
141. DOCKER
Provide:
Dockerfile
docker-compose.yml
Services:
•	Web.
•	API.
•	PostgreSQL.
•	Redis.
•	Object storage for local development.
________________________________________
142. DEVELOPMENT README
Provide complete instructions:
1.	Install dependencies.
2.	Configure .env.
3.	Start PostgreSQL.
4.	Start Redis.
5.	Run migrations.
6.	Seed database.
7.	Start backend.
8.	Start frontend.
9.	Login using demo credentials.
10.	Run tests.
________________________________________
143. SEED DATA
Create realistic but clearly fake development data.
Include:
•	Admin.
•	Department Heads.
•	Supervisors.
•	Field Officers.
•	Reserve employees.
•	Departments.
•	Geographic hierarchy.
•	Teams.
•	Households.
•	Campaigns.
•	Phases.
•	Forms.
•	Tasks.
Never use real personal information.
________________________________________
144. DEMO CREDENTIALS
Provide development-only demo accounts.
Example:
District Admin
Department Head
Supervisor
Field Officer
Payment Officer
Clearly mark:
DEVELOPMENT ONLY
Do not use these credentials in production.
________________________________________
145. IMPORTANT GOVERNMENT DATA RULE
Do not invent:
•	Official Census questions.
•	Government payment amounts.
•	Government orders.
•	Government employee records.
•	Official geographic datasets.
•	Government APIs.
•	Official Census procedures.
Where official information is unavailable, create:
CONFIGURABLE PLACEHOLDERS
and clearly label them.
________________________________________
146. IMPORTANT DESIGN RULE
Do not create separate applications for:
•	Census.
•	School inspection.
•	Road survey.
•	Flood survey.
Instead create one:
District Campaign Platform
Then:
Campaign Type:
Census
Campaign:
Census 2027
Phase:
House Listing
This makes the platform reusable.
________________________________________
147. MOST IMPORTANT ARCHITECTURAL MODULES
The application must be built around these engines:
1. Campaign Engine
Campaigns and phases.
2. Organization Engine
Departments and hierarchy.
3. Geography Engine
District/tehsil/village/ward/mohalla.
4. Workforce Engine
Employees and availability.
5. Team Engine
Joint teams and reserve teams.
6. Target Entity Engine
Households, schools, roads, etc.
7. Assignment Engine
Assign targets to teams/employees.
8. Form Engine
Dynamic forms and versions.
9. Field Data Engine
Mobile data collection.
10. Offline Sync Engine
Mobile offline operation.
11. Verification Engine
Review and approval.
12. Exception Engine
Data quality and operational exceptions.
13. Payment Engine
Configurable government-guideline-based payment.
14. Notification Engine
SMS/email/push/in-app.
15. Reporting Engine
Dashboards and reports.
16. Audit Engine
Complete history.
________________________________________
148. DEVELOPMENT ORDER
Do not attempt to create the entire application as disconnected pages.
Build in this order:
Phase A — Foundation
•	Architecture.
•	Database.
•	Authentication.
•	RBAC.
•	Organization.
•	Geography.
Phase B — Campaign
•	Campaign.
•	Phase.
•	Department.
•	Workforce.
•	Team.
Phase C — Target & Assignment
•	Target entities.
•	Household.
•	Geographic assignment.
•	Task engine.
•	Workload.
Phase D — Forms
•	Form builder.
•	Dynamic questions.
•	Conditions.
•	Repeating groups.
•	Validation.
•	Versioning.
Phase E — Mobile
•	Field officer UI.
•	Offline.
•	GPS.
•	Image.
•	Video.
•	Sync.
Phase F — Workflow
•	Verification.
•	Correction.
•	Resubmission.
•	Approval.
•	Exceptions.
Phase G — Payment
•	Payment rules.
•	Eligibility.
•	Approval.
•	Status.
•	Reminders.
•	Exceptions.
Phase H — Intelligence
•	Dashboards.
•	Maps.
•	Analytics.
•	Reports.
•	Exports.
Phase I — Production
•	Security.
•	Testing.
•	Load testing.
•	Monitoring.
•	Backups.
•	Disaster recovery.
•	Docker.
•	Documentation.
________________________________________
149. FINAL ACCEPTANCE CRITERIA
The project is considered complete only when a real end-to-end flow works:
District Admin
→ creates campaign
→ creates multiple phases
→ selects departments
→ imports workforce
→ creates joint teams
→ creates reserve teams
→ assigns geography
→ loads target entities
→ creates phase-specific dynamic form
→ creates verification workflow
→ configures authorized payment rule
→ launches campaign
↓
Field Team
→ logs in on mobile
→ receives assigned area
→ sees assigned targets
→ visits target
→ fills form
→ captures GPS where required
→ captures media where required
→ works offline if necessary
→ synchronizes
→ submits
↓
Reviewer
→ receives submission
→ verifies
→ requests correction
↓
Field Team
→ corrects
→ resubmits
↓
Reviewer
→ approves
↓
System
→ finalizes result
→ calculates authorized payment eligibility
→ tracks payment
→ sends notifications
↓
District Admin
→ sees real-time progress
→ drills down geographically
→ views maps
→ views department/team/employee performance
→ views exceptions
→ views payment status
→ generates reports
→ exports authorized data
→ reviews audit history.
________________________________________
150. FINAL INSTRUCTION TO THE AI DEVELOPER
Do not build a toy project.
Do not build only frontend screens.
Do not use hard-coded arrays for core business data.
Do not make fake buttons.
Do not create disconnected demo pages.
Build a real full-stack system with:
Frontend
↕
Backend API
↕
Business Logic
↕
PostgreSQL
↕
Object Storage
↕
Redis/Background Jobs
↕
Notification Services
Every important button must perform a real operation.
Every important record must be persisted.
Every permission must be enforced on the backend.
Every official submission must be versioned.
Every important change must be audited.
Every large operation must be designed for scale.
Every mobile workflow must consider poor connectivity.
Every payment amount must be configurable and linked to an authorized rule/reference.
Every campaign must be configurable.
Every phase must be independently configurable.
Every form must be dynamically configurable.
Every organization/geographic hierarchy must be configurable.
The final product should be a reusable District Administration Digital Campaign & Field Operations Platform, with Census 2027 as one realistic implementation, rather than a Census-only application.
One thing I would strongly recommend
For a project of this scale, don't ask the AI to generate the entire application in one shot. Give it the master prompt above, then make it work module-by-module, starting with the database and architecture.
The most important foundation is:
Organization → Geography → Workforce → Campaign → Phase → Team → Target → Task → Form → Submission → Verification → Result → Payment
If that data model is correct, the rest of the application can evolve without needing to rebuild it later

This is a test prompt created to verify API authentication.

name = "hallucination-investigator"
description = "Use when a task needs root-cause analysis for factuality failures, unsupported claims, or context breakdowns in AI outputs."
model = "gpt-5.6-sol"
model_reasoning_effort = "high"
sandbox_mode = "read-only"
developer_instructions = """
Own hallucination investigation as root-cause analysis across context, retrieval, prompts, tools, and workflow design.

Working mode:
1. Reconstruct the failing example and the evidence the system actually had available.
2. Determine whether the failure came from missing context, bad retrieval, prompt framing, tool misuse, or unsupported inference.
3. Recommend the smallest change that most directly reduces recurrence.
4. Note how to verify the fix with targeted cases.

Focus on:
- whether the answer exceeded available evidence
- retrieval misses, ranking issues, or stale context effects
- prompt wording that encourages overconfident completion
- output formats that hide uncertainty or source gaps
- detection opportunities for unsupported claims before user delivery

Quality checks:
- verify the diagnosis uses the actual failing path, not generic speculation
- separate no-evidence failures from evidence-ignored failures
- recommend fixes that address the root cause rather than only suppressing wording
- include at least one targeted regression case

Return:
- failure reconstruction and likely root cause
- highest-leverage fix and why
- supporting detection or guardrail ideas
- targeted verification cases
- residual risk if only the recommended fix is applied

Do not label every wrong answer a hallucination when the true issue is poor retrieval, stale data, or tool failure unless explicitly requested by the parent agent.
"""

Own hallucination investigation as root-cause analysis across context, retrieval, prompts, tools, and workflow design.

Working mode:
1. Reconstruct the failing example and the evidence the system actually had available.
2. Determine whether the failure came from missing context, bad retrieval, prompt framing, tool misuse, or unsupported inference.
3. Recommend the smallest change that most directly reduces recurrence.
4. Note how to verify the fix with targeted cases.

Focus on:
- whether the answer exceeded available evidence
- retrieval misses, ranking issues, or stale context effects
- prompt wording that encourages overconfident completion
- output formats that hide uncertainty or source gaps
- detection opportunities for unsupported claims before user delivery

Quality checks:
- verify the diagnosis uses the actual failing path, not generic speculation
- separate no-evidence failures from evidence-ignored failures
- recommend fixes that address the root cause rather than only suppressing wording
- include at least one targeted regression case

Return:
- failure reconstruction and likely root cause
- highest-leverage fix and why
- supporting detection or guardrail ideas
- targeted verification cases
- residual risk if only the recommended fix is applied

Do not label every wrong answer a hallucination when the true issue is poor retrieval, stale data, or tool failure unless explicitly requested by the parent agent.

A close-up showcases the exquisite packaging of the tumeric kojic soap, displaying is vibrant orange and yellow designs.

create a PNG image like a stamp saying sent to $(country). Image in red, retro style, horizontal stamp