Borrowing it
Nothing to install: this file belongs to atliq/recap. 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/atliq/recap/main/AGENTS.mdgit clone --depth 1 https://github.com/atliq/recapWrote 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/atliq/recap/agents-md)<a href="https://agentmods.dev/instructions/atliq/recap/agents-md"><img src="https://agentmods.dev/badge/instructions/atliq/recap/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/atliq/recap/agents-md"><img src="https://agentmods.dev/badge/instructions/atliq/recap/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 | $0.02577 | $0.02577 |
| Opus 5.5 | $0.01031 | $0.01031 |
| Sonnet 5.5 | $0.00515 | $0.00515 |
| Haiku 4.5 | $0.00258 | $0.00258 |
Grade A, and why
recap 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.
How it starts
The opening of the file, as written. The whole thing — 118 lines — stays where its author put it; the contents beside it link to each section on GitHub.
AGENTS.md
Guidance for AI coding agents - and humans - working in the RECAP repository. This is the single source of truth for how to set up, run, test, and change this project; tool-specific files (CLAUDE.md, etc.) import it. The human-facing overview is in README.md; the security policy is in SECURITY.md.
What RECAP is
RECAP is a local-first Chrome extension (Manifest V3) plus a local Python (FastAPI) RAG backend. It passively indexes the pages a user actually reads and lets them search their browsing history in natural language. Everything runs on the user's machine; page content only leaves the device when the user asks a question - and only the retrieved snippets, sent to the LLM provider the user configured.
Setup & run
Requires Docker (recommended) or Python 3.11+, plus Chrome. Three paths, all of
which install spaCy + the en_core_web_sm model (so the knowledge graph works as soon as you opt in):
# Docker - recommended: reproducible, one command. Serves http://127.0.0.1:8000 (loopback only).
docker compose up --build
# uv - fast, reproducible local dev. `uv sync` installs deps + the spaCy model.
uv sync && uv run python main.py
# pip - simple fallback.
pip install -r requirements.txt && python main.py
pyproject.toml (+ uv.lock) is the canonical dependency set for uv/Docker; requirements.txt
mirrors it for the pip path - keep the two in sync when changing versions. torch is pinned to
the CPU wheel (tool.uv.sources) so images stay small and it runs anywhere; GPU users override it.
- Copy
.env.example→.envand set at least one LLM key (or point at a local Ollama). See LLM & embeddings below. - Docker + a host Ollama: the container can't see the host's
localhost- setLLM_BASE_URL/EMBEDDING_BASE_URLtohttp://host.docker.internal:11434/v1(compose already mapshost.docker.internal). - Load the extension:
chrome://extensions→ enable Developer mode → Load unpacked → select theextension/folder. - Knowledge graph: off by default - retrieval runs BM25 + dense vectors only. Opt in from the extension Options page toggle (calls
POST /settings/kg; takes effect immediately, persisted in DB meta so it survives backend restarts and overrides.env), or setENABLE_KG=truein.envfor a config-only setup. The master switch gates both ingestion NER and the KG retrieval leg; a request'suse_kgcan never override it on. After enabling, backfill already-indexed pages without re-browsing viaPOST /maintenance/rebuild_kg(re-runs NER over stored text; SQLite is the source of truth). Entities need spaCy (installed by default).
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 · 118 lines · 2,577 tokens per session scan A af54dce777a5
recap AGENTS.md is an instructions file published in the GitHub repository atliq/recap (11 stars, last pushed 3mo ago), licensed MIT. It adds 2,577 tokens to every session, about $0.0103 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.
recap AGENTS.md compared with instructions from other repositories
| Mod | Type | Stars | Last push | Licence | Scan | Tokens | Works with |
|---|---|---|---|---|---|---|---|
| recap AGENTS.mdatliq/recap | Instructions file | 11 | 3mo ago | MIT | A | 2,577 | 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 | yesterday | 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 |