Borrowing it
Nothing to install: this file belongs to extra-org/extra. 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/extra-org/extra/main/AGENTS.mdgit clone --depth 1 https://github.com/extra-org/extraWrote 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/extra-org/extra/agents-md)<a href="https://agentmods.dev/instructions/extra-org/extra/agents-md"><img src="https://agentmods.dev/badge/instructions/extra-org/extra/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/extra-org/extra/agents-md"><img src="https://agentmods.dev/badge/instructions/extra-org/extra/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 | $0.04051 | $0.04051 |
| Opus 5.5 | $0.01620 | $0.01620 |
| Sonnet 5.5 | $0.00810 | $0.00810 |
| Haiku 4.5 | $0.00405 | $0.00405 |
Grade A, and why
extra 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 11d 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 — 359 lines — stays where its author put it; the contents beside it link to each section on GitHub.
AGENTS.md
This file is the operating manual for every AI coding agent working in this repository. Read it fully before making any change. If a task ever conflicts with this file, this file wins — stop and ask for clarification.
1. Project mission
This repository is a declarative platform for building AI agent systems.
Developers describe an agent system in YAML. The platform validates that YAML, compiles it into a typed internal graph, and runs it through a long-lived runtime that renders prompt files, calls resolver/tool plugins and MCP servers, exposes an API, and produces execution traces.
The repository is in active development. The YAML validator, compiler,
runtime engine (orchestrators run as supervisor agents), resolver
plugin system, tool plugin loading, MCP client (local and remote servers,
including authenticated MCP via hooks), the runtime hooks system
(11 lifecycle points — see
docs/RUNTIME_HOOKS.md), per-run execution-limit
guardrails (see docs/EXECUTION_LIMITS.md), prompt
rendering, and the CLI (validate, inspect, generate, run, serve,
chat) are implemented. Model access supports both Anthropic and Amazon
Bedrock. Two HTTP API layers exist: a thin agent_engine API (/invoke,
/stream), started by agentctl serve (default port 8090) — stateless, no
persistence, no web client — and agent_manager — a conversation lifecycle
service built on top of it with process-local storage by default, opt-in
SQLite/Postgres persistence, SSE streaming, and the official React web client,
started by the separate agent-manager console script (default port 8100).
agentctl chat is a separate, ephemeral
developer console that persists nothing (see docs/ARCHITECTURE.md §14 for
detail). Basic observability
(structured logging plus a Langfuse callback provider) is wired in. A
Dockerfile/entrypoint.sh provide a basic container image.
The access plugin is wired into child filtering, but the request-context
gate that should populate real identity/permissions into it is not yet
implemented — access filtering currently runs against an empty context, so
protected nodes are not actually enforced today. Treat this as an open
security gap, not a finished feature. See docs/ROADMAP.md
for per-phase status. Agents implement the product task-by-task using the
files in tasks/, though the package layout has evolved beyond what the
original numbered tasks describe (see §4).
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.
- 11d ago Changed · +1 lines · +23 tokens per session 18598cbca5d4
- 2mo ago First seen · 358 lines · 4,028 tokens per session scan A 989ae47478a4
extra AGENTS.md is an instructions file published in the GitHub repository extra-org/extra (117 stars, last pushed 5d ago), licensed MIT. It adds 4,051 tokens to every session, about $0.0162 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.
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