Borrowing it
Nothing to install: this file belongs to punt-labs/quarry. 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/punt-labs/quarry/main/AGENTS.mdgit clone --depth 1 https://github.com/punt-labs/quarryWrote 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/punt-labs/quarry/agents-md)<a href="https://agentmods.dev/instructions/punt-labs/quarry/agents-md"><img src="https://agentmods.dev/badge/instructions/punt-labs/quarry/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/punt-labs/quarry/agents-md"><img src="https://agentmods.dev/badge/instructions/punt-labs/quarry/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 | $0.03042 | $0.03042 |
| Opus 5.5 | $0.01217 | $0.01217 |
| Sonnet 5.5 | $0.00608 | $0.00608 |
| Haiku 4.5 | $0.00304 | $0.00304 |
Grade A, and why
quarry 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 25d 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 — 197 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Quarry for Agents
Quarry gives AI agents persistent semantic memory. Index documents, search by meaning, and recall knowledge across sessions — all local, no API keys.
What Quarry Does
You have a context window. It fills up and gets compacted. Quarry sits outside that window as durable storage: you ingest documents and conversation fragments, then search them later by meaning. A query about "margins" finds passages about profitability even if they never use that word.
Quarry handles 20+ formats natively: PDFs (with OCR for scanned pages), source code (AST-aware splitting), spreadsheets, presentations, HTML, Markdown, LaTeX, DOCX, and images.
Integration Model
Quarry integrates with Claude Code as a plugin that provides three layers:
- MCP tools — the core interface. Search, ingest, list, delete, manage databases.
- Slash commands — user-facing shortcuts that call MCP tools with formatting logic.
- Hooks — automatic background behaviors that run without user intervention.
MCP Tools
These are the tools you call directly. Read-only tools are synchronous; write tools are fire-and-forget (return immediately, process in background).
The registered tools (src/quarry/mcp_server.py registers the McpTools set; missions_sync lives in the sibling mcp_missions.py and is registered from the same call):
| Tool | Purpose | Execution |
|---|---|---|
find |
Hybrid search (vector + BM25 via RRF) with optional filters (collection, document_filter, page_type, source_format, agent_handle, memory_type) | Sync |
show |
Retrieve document metadata or a specific page's full text | Sync |
list |
List documents, collections, databases, or registrations | Sync |
status |
Database stats: doc/chunk counts, size, model info | Sync |
ingest |
Ingest a URL (auto-discovers sitemaps); local files and directories go through register_directory + sync_all_registrations |
Background |
remember |
Ingest inline text content with a document name (agent_handle routes it to memory-<handle>; memory_type and summary tag it) |
Background |
learn |
Save a distilled lesson (<= 500 chars) that gets retrieval preference; the only writer of memory_type = lesson |
Background |
delete |
Delete a document or collection | Background |
register_directory |
Register a directory for incremental sync | Background |
deregister_directory |
Remove a directory registration | Background |
sync_all_registrations |
Sync all registered directories | Background |
use |
Switch the active named database | Sync |
missions_sync |
File each frozen ethos mission round of this repo as an observation in memory-<worker> (mission, dry_run, force); run after ethos mission close |
Sync |
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.
- 25d ago Changed · +2 lines · +3 tokens per session f9a479b65609
- 1mo ago Changed · +23 lines · +1,086 tokens per session 21455fb71b7a
- 1mo ago Changed · -1 lines · -8 tokens per session 7f015a1f66eb
- 1mo ago First seen · 173 lines · 1,961 tokens per session scan A 6b876cbd6b91
quarry AGENTS.md is an instructions file published in the GitHub repository punt-labs/quarry (7 stars, last pushed 2d ago), licensed MIT. It adds 3,042 tokens to every session, about $0.0122 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).
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.