Getting it into your agent
One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.
npx agentmods add instructions/gies-ai-experiments/venturebot/agents-mdgit clone --depth 1 https://github.com/gies-ai-experiments/VentureBotWrote 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/gies-ai-experiments/venturebot/agents-md)<a href="https://agentmods.dev/instructions/gies-ai-experiments/venturebot/agents-md"><img src="https://agentmods.dev/badge/instructions/gies-ai-experiments/venturebot/agents-md.svg" alt="Measured on agentmods" 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 | $0.00660 | $0.00660 |
| Opus 5 | $0.00330 | $0.00330 |
| Sonnet 5 | $0.00132 | $0.00132 |
| Haiku 4.5 | $0.00066 | $0.00066 |
Grade A, and why
VentureBot AGENTS.md scanned grade A with 1 finding 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 5d 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.
Makes network callslowCapability
Not a fault in itself. Listed so you know the mod talks to something, and to what.
- Smoke check: `curl http://localhost:8000/healthz` and a simple chat session via `POST /api/chat/sessions`. How it starts
The opening of the file, as written. The whole thing — 35 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Repository Guidelines
Project Structure & Module Organization
services/: Python backend (FastAPI gateway inservices/api_gateway/app/, orchestration inservices/orchestrator/, shared tools inservices/tools/)crewai-agents/: CrewAI blueprint + prompt/task configs (crewai-agents/src/venturebot_crew/config/*.yaml)frontend/: React + Vite SPA (TypeScript) and nginx container for production buildsdocs/,scripts/,data/: architecture notes, ops scripts, local runtime data (SQLite/logs)
Build, Test, and Development Commands
- Backend setup:
python -m venv .venv && source .venv/bin/activate && pip install -r requirements.txt - Run backend (dev):
python -m uvicorn services.api_gateway.app.main:app --reload --port 8000(docs:http://localhost:8000/docs) - Frontend setup:
cd frontend && npm ci - Run frontend (dev):
cd frontend && npm run dev(setVITE_API_BASE_URL=http://localhost:8000if needed) - Lint/build frontend:
cd frontend && npm run lint/npm run build - Run full stack (Docker):
docker compose up --build(frontend:http://localhost, backend:http://localhost:8000)
Coding Style & Naming Conventions
- Python: 4-space indent, type hints where practical,
snake_casefor functions/modules,PascalCasefor classes. - TypeScript/React: prefer functional components,
PascalCasecomponents, keep API URL configurable (seefrontend/src/App.tsx). - Keep request/response models in
services/api_gateway/app/schemas.pyand persistence inservices/api_gateway/app/models.py.
Testing Guidelines
- Backend testing uses
pytest(listed inrequirements.txt). Add tests undertests/astest_*.pyand runpytest. - Smoke check:
curl http://localhost:8000/healthzand a simple chat session viaPOST /api/chat/sessions. - Frontend has no unit test runner configured; use
npm run buildas a sanity check.
Commit & Pull Request Guidelines
- Commit subjects commonly use prefixes like
feat:,fix:,refactor:,docs:,chore:; keep the subject short and imperative. - PRs should include: what changed + why, steps to verify, and screenshots for UI changes.
- Never commit secrets. Use
.env.templateas a starting point for local.env.
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.
- 5d ago First seen · 35 lines · 660 tokens per session scan A 22a318e49507
VentureBot AGENTS.md is an instructions file published in the GitHub repository gies-ai-experiments/VentureBot (5 stars, last pushed 2mo ago), licensed MIT. It adds 660 tokens to every session, about $0.0033 per session on Opus 5. A static security scan graded it A with 1 finding (makes network calls). No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-31.
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).
spec-kit AGENTS.md
AGENTS.md instructions for github/spec-kit, covering agents.md, about spec kit and specify, quickstart — add a new integration in 5 steps, integration architecture and integrationmanifest — file tracking.
codex AGENTS.md
AGENTS.md instructions for openai/codex, covering rust/codex-rs, the codex-core crate, code review rules, crate api surface and model visible context.
vscode oss-third-party-notices.instructions.md
Instructions for microsoft/vscode, covering vs code oss third-party-notices pipeline, architecture, pipeline flow in ci, applying the notice (cutover) and fallback chain (never fail the build).
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.
deepseek-harness AGENTS.md
AGENTS.md instructions for deepseek-ai/deepseek-harness, covering agents.md, pre-stable apis and released session data, repository layout, commands and host sandbox failures.