Borrowing it
Nothing to install: this file belongs to vpeetla-ai/react-agent-pattern. 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/vpeetla-ai/react-agent-pattern/main/AGENTS.mdgit clone --depth 1 https://github.com/vpeetla-ai/react-agent-patternWrote 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/vpeetla-ai/react-agent-pattern/agents-md)<a href="https://agentmods.dev/instructions/vpeetla-ai/react-agent-pattern/agents-md"><img src="https://agentmods.dev/badge/instructions/vpeetla-ai/react-agent-pattern/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/vpeetla-ai/react-agent-pattern/agents-md"><img src="https://agentmods.dev/badge/instructions/vpeetla-ai/react-agent-pattern/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 | $0.00389 | $0.00389 |
| Opus 5.5 | $0.00156 | $0.00156 |
| Sonnet 5.5 | $0.00078 | $0.00078 |
| Haiku 4.5 | $0.00039 | $0.00039 |
Grade A, and why
react-agent-pattern 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 2mo 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.
This is a copy
100% identical to multi-agent-system-pattern AGENTS.md — 0 lines differ, which has more behind it and is treated as the original. This page carries a canonical link to it rather than competing with it.
What it actually says
Agent Instructions — vpeetla-ai org
Read CONTEXT.md for shared vocabulary.
Agentic engineering (Karpathy)
- Think before coding — state assumptions, plan, success criteria
- Simplicity first — minimum diff; no speculative features
- Surgical changes — match existing style; no drive-by refactors
- Goal-driven execution — tests/evals define done; iterate until pass
Stack awareness
This org builds governed agent systems, not chat demos:
- Orchestration (VAP) and governance (AegisAI) are separate layers
- RAG uses access-before-ranking
- Side effects require gateway or HITL
- Self-improvement uses harness + eval loops (LoopForge)
Repo conventions
- Python 3.11+, FastAPI, Pydantic v2, LangGraph for agent graphs
pip install -e ".[dev]"+pytest -qbefore claiming done- README: badges → problem → 60s diagram → honest status table → quick start
- Deploy: Vercel (UI) + Render (API); see
render.yaml
Skills repo
Install org skills from vpeetla-ai-skills:
./scripts/install.sh --cursor --project .
./scripts/install.sh --codex --project .
When stuck
- Check which stack layer the task belongs to
- Read the target repo's
docs/ECOSYSTEM.mdordocs/ARCHITECTURE.md - Use tdd-agent-loops for graph changes; aegis-gateway for side effects
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.
- 2mo ago First seen · 42 lines · 389 tokens per session scan A 2ee79e251ad2
react-agent-pattern AGENTS.md is an instructions file published in the GitHub repository vpeetla-ai/react-agent-pattern (2 stars, last pushed 2mo ago), licensed MIT. It adds 389 tokens to every session, about $0.0016 per session on Opus 5.5. A static security scan graded it A with 0 findings. It is 100% identical to multi-agent-system-pattern AGENTS.md, differing in 0 lines, and is treated as a copy.
react-agent-pattern AGENTS.md compared with instructions from other repositories
| Mod | Type | Stars | Last push | Licence | Scan | Tokens | Works with |
|---|---|---|---|---|---|---|---|
| react-agent-pattern AGENTS.mdvpeetla-ai/react-agent-pattern | Instructions file | 2 | 2mo ago | MIT | A | 389 | Codex, OpenCode |
| vscode buildNext.instructions.mdmicrosoft/vscode | Instructions file | 195k | yesterday | MIT | A | 9,719 | GitHub Copilot |
| next.js AGENTS.mdvercel/next.js | Instructions file | 143k | today | MIT | A | 7,461 | Codex, OpenCode |
| langchain AGENTS.mdlangchain-ai/langchain | Instructions file | 149k | yesterday | MIT | A | 4,680 | Codex, OpenCode |
| vscode oss-third-party-notices.instructions.mdmicrosoft/vscode | Instructions file | 195k | yesterday | MIT | A | 5,516 | GitHub Copilot |
| vscode copilot-instructions.mdmicrosoft/vscode | Instructions file | 195k | yesterday | MIT | A | 3,093 | GitHub Copilot |
| deepseek-harness AGENTS.mddeepseek-ai/deepseek-harness | Instructions file | 274k | 2d ago | MIT | A | 4,313 | Codex, OpenCode |