Borrowing it
Nothing to install: this file belongs to divar-ir/ai-doc-gen. Take a copy, put it at the same path in your own repository, and replace the rules that are about this project with yours.
curl -O https://raw.githubusercontent.com/divar-ir/ai-doc-gen/main/AGENTS.mdgit clone --depth 1 https://github.com/divar-ir/ai-doc-genWrote this? Show the measurements
A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.
[](https://agentmods.dev/instructions/divar-ir/ai-doc-gen/agents-md)<a href="https://agentmods.dev/instructions/divar-ir/ai-doc-gen/agents-md"><img src="https://agentmods.dev/badge/instructions/divar-ir/ai-doc-gen/agents-md/github.svg" alt="Measured on agentmods" height="20"></a>Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.
<a href="https://agentmods.dev/instructions/divar-ir/ai-doc-gen/agents-md"><img src="https://agentmods.dev/badge/instructions/divar-ir/ai-doc-gen/agents-md.svg" alt="Reviewed on agentmods" width="80" height="20"></a>What it costs to keep this loaded
Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5.1 | $0.01434 | $0.01434 |
| Opus 5.5 | $0.00574 | $0.00574 |
| Sonnet 5.5 | $0.00287 | $0.00287 |
| Haiku 4.5 | $0.00143 | $0.00143 |
Grade A, and why
ai-doc-gen AGENTS.md scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 1mo ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
How it starts
The opening of the file, as written. The whole thing — 96 lines — stays where its author put it; the contents beside it link to each section on GitHub.
AI Documentation Generator
Multi-agent Python CLI tool that analyzes codebases and generates documentation: .ai/docs/*.md analyses, README.md, and AI assistant config files (CLAUDE.md, AGENTS.md, .cursor/rules/).
Build & Test
# Install dependencies (Python 3.13 required, <3.14)
uv sync
# Run analysis (writes .ai/docs/*.md)
uv run src/main.py analyze --repo-path .
# Generate README
uv run src/main.py generate readme --repo-path .
# Generate AI assistant config files (CLAUDE.md, AGENTS.md, .cursor/rules/)
uv run src/main.py generate ai-rules --repo-path .
# GitLab batch mode
uv run src/main.py cronjob analyze --max-days-since-last-commit 14
# Format and lint (run both before submitting)
uv run ruff format src/
uv run ruff check src/
Setup: cp .env.sample .env (fill in LLM keys), optionally cp config_example.yaml .ai/config.yaml.
Architecture
- Multi-agent system: 5 analysis agents (structure, dependencies, data flow, request flow, API) run through a
WorkerPool(src/utils/worker_pool.py, concurrency fromANALYZER_MAX_WORKERS, 0 = CPU count); 2 AI-rules generators (markdown + cursor) run viaasyncio.gather(return_exceptions=True). - Handler pattern: each CLI command maps to a handler in
src/handlers/implementingAbstractHandler.handle(); handler configs subclassBaseHandlerConfig+ the agent config (e.g.,AnalyzeHandlerConfig(BaseHandlerConfig, AnalyzerAgentConfig)). - Tool-based agents: pydantic-ai agents with
FileReadToolandListFilesTool(src/agents/tools/); prompts are Jinja2 templates insrc/agents/prompts/*.yaml. - Configuration hierarchy: Pydantic defaults →
.ai/config.yaml→ CLI arguments (merge_dicts()); secrets come from.envvia module-level constants insrc/config.py. - LLM providers: OpenAI-compatible only (
OpenAIChatModel+OpenAIProviderwith base URL override). Three env config sets:ANALYZER_LLM_*,DOCUMENTER_LLM_*,AI_RULES_LLM_*(AI_RULES falls back to DOCUMENTER values).
What this file has done since we first saw it
Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.
- 1mo ago First seen · 96 lines · 1,434 tokens per session scan A c312ac5d8200
ai-doc-gen AGENTS.md is an instructions file published in the GitHub repository divar-ir/ai-doc-gen (767 stars, last pushed 3mo ago), licensed MIT. It adds 1,434 tokens to every session, about $0.0057 per session on Opus 5.5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-30.
Other instructions, from other repositories
vscode buildNext.instructions.md
Working notes and architecture documentation for the new esbuild-based build system in build/next. Use when making changes to the new build pipeline (transpile/bundle commands, NLS plugin, source-map handling, resource copying, or self-hosting watch tasks).
next.js AGENTS.md
AGENTS.md instructions for vercel/next.js, covering next.js development guide, codebase structure, monorepo overview, core package: packages/next and other important packages.
vscode oss-third-party-notices.instructions.md
Instructions for microsoft/vscode, covering vs code oss third-party-notices pipeline, architecture, pipeline flow in ci, cache eligibility and rollout and applying the notice (cutover).
langchain AGENTS.md
AGENTS.md instructions for langchain-ai/langchain, covering global development guidelines for the langchain monorepo, corridor security analysis, project architecture and context, monorepo structure and development tools & commands.
vscode copilot-instructions.md
Copilot instructions for microsoft/vscode, covering vs code copilot instructions, project overview, root folders, core architecture (src/ folder) and built-in extensions (extensions/ folder).
vscode model-prompts.instructions.md
Model-specific prompt authoring and registry guidelines.