Getting it into your agent
One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.
npx agentmods add instructions/punt-labs/quarry/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.svg" alt="Measured on agentmods" 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 | $0.01961 | $0.01961 |
| Opus 5 | $0.00981 | $0.00981 |
| Sonnet 5 | $0.00392 | $0.00392 |
| Haiku 4.5 | $0.00196 | $0.00196 |
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 4d 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 — 173 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).
| 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 file or URL (auto-discovers sitemaps) (supports agent_handle for expertise seeding) | Background |
remember |
Ingest inline text content with a document name (supports agent_handle, memory_type, summary for memory tagging) | 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 |
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.
- 4d 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 (3 stars, last pushed 4d ago), licensed MIT. It adds 1,961 tokens to every session, about $0.0098 per session on Opus 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
agent-toolkit AGENTS.md
Instructions for sanity-io/agent-toolkit, covering sanity project, commands, mcp setup, schema & types and development.
prfaq CLAUDE.md
Instructions for punt-labs/prfaq, covering how i write code, mandatory reading, no "pre-existing" excuse, standards and development workflow.
ocr-mcp AGENTS.md
AGENTS.md instructions for sandraschi/ocr-mcp, covering ocr-mcp — agent guide, entry points, quick ref, standards and key files.
z-spec CLAUDE.md
Claude Code instructions for punt-labs/z-spec, covering z-spec, mandatory reading, read this first, architecture and key architectural boundary: commands vs. surfaces.
memem CLAUDE.md
Claude Code instructions for TT-Wang/memem, covering memem — persistent memory & context assembly, auto-recall, context model (v2.8+), tier 1 — profiles (always-injected) and tier 2 — working rules (procedural, citation-ranked).
ocr-mcp copilot-instructions.md
Copilot instructions for sandraschi/ocr-mcp: You have access to a FastMCP 3.4+ OCR server with 14 backends for document text extraction.