Borrowing it
Nothing to install: this file belongs to Avyayalaya/agent-prime. 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/Avyayalaya/agent-prime/main/AGENTS.mdgit clone --depth 1 https://github.com/Avyayalaya/agent-primeWrote 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/avyayalaya/agent-prime/agents-md)<a href="https://agentmods.dev/instructions/avyayalaya/agent-prime/agents-md"><img src="https://agentmods.dev/badge/instructions/avyayalaya/agent-prime/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/avyayalaya/agent-prime/agents-md"><img src="https://agentmods.dev/badge/instructions/avyayalaya/agent-prime/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 | $0.03895 | $0.03895 |
| Opus 5.5 | $0.01558 | $0.01558 |
| Sonnet 5.5 | $0.00779 | $0.00779 |
| Haiku 4.5 | $0.00390 | $0.00390 |
Grade A, and why
agent-prime 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 — 244 lines — stays where its author put it; the contents beside it link to each section on GitHub.
AGENTS.md — Agent Prime
Machine-readable system manifest. Primary audience: AI orchestrators deciding whether to route work here.
Overview
Agent Prime is an open-source AI operating system built entirely from markdown files. It provides 13 specialized agents + a runtime-portable 5-agent quality gate (Agent Council), 12 domain skills with typed schemas, persistent memory with recursive self-improvement, 8 structured guardrails, and 4 declarative workflows. Zero dependencies — no database, no runtime, no package manager. Clone the repo and point any LLM at it. The system gets permanently smarter with every correction via an append-only learnings registry that propagates constraints to all agents.
Repository: https://github.com/avyayalaya/agent-prime
Instruction files: CLAUDE.md (Claude Code), .github/copilot-instructions.md (GitHub Copilot), both kept in sync.
Architecture: Markdown-only, 7 layers, cross-LLM compatible (Claude Code, GitHub Copilot, Gemini CLI).
Capabilities
- 13 specialized agents with typed inputs, outputs, and Context Verification Gates
- 12 PM-domain skills with codified methodologies, failure modes, and benchmark scores
- Recursive learning loop: Every user correction becomes a permanent rule in
shared/learnings.md, applied to all agents in all future sessions - 8 structured guardrails enforced via system rules in
CLAUDE.md(including a runtime-portable 5-agent quality gate) - 4 declarative workflows composing agents into end-to-end pipelines
- 49 system rules governing context verification, voice, NDA compliance, change propagation, and quality
- 100+ accumulated learnings across voice, content, process, quality, build, and agent design categories
- Session resilience: Write-ahead journaling, crash recovery, session audit, learning extraction
- Cross-LLM compatibility: Works on Claude Code, GitHub Copilot Chat, Gemini CLI without modification
- Onboarding wizard: Interactive setup in under 10 minutes via the Onboarder agent
- Zero dependencies: No npm, no pip, no Docker. Python 3.10+ for optional scripts only.
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 · 244 lines · 3,895 tokens per session scan A 2af47bd5bd75
agent-prime AGENTS.md is an instructions file published in the GitHub repository Avyayalaya/agent-prime (9 stars, last pushed 5mo ago), licensed MIT. It adds 3,895 tokens to every session, about $0.0156 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 2026-08-31.
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).
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).
deno copilot-instructions.md
Copilot instructions for denoland/deno, covering deno development guide for github copilot, network access, high level overview, key directories and key files to understand first.