agentmods.dev

canopy CLAUDE.md

canopy CLAUDE.md is an instructions file for coding agents from jayminwest/canopy. It costs 1,491 tokens per session, scanned A, original, MIT.

A project guide for Canopy, a tool that stores reusable prompts in Git-managed text files. It explains the project layout, conventions, commands, and Mulch, the system used to load project-specific expertise.

In plain words
What is it for?
Use it when changing Canopy's Bun and TypeScript code, prompt records, JSONL storage, schemas, command-line interface, or project documentation.
Why use it?
It helps an AI coding assistant understand how this TypeScript project is organized and which preparation command to run before work begins.

Instructions file

39 1mo ago A scan 1,491 tokens original MIT
View the source file jayminwest/canopy
Install

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.

agentmods
npx agentmods add instructions/jayminwest/canopy/claude-md
Clone the repo
git clone --depth 1 https://github.com/jayminwest/canopy
Per session 1,491 This file is loaded in full into every session.
When invoked 1,491 The same file — it is already loaded in full.
Security scan A 0 findings. Scan, not verified.
Origin original No closer match found in the catalogue.
Token cost

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.

ModelPer sessionOnce invoked
Fable 5 $0.01491 $0.01491
Opus 5 $0.00745 $0.00745
Sonnet 5 $0.00298 $0.00298
Haiku 4.5 $0.00149 $0.00149

Measured 3d ago against content hash e8751d9da51d, method: parsed. Prices are Anthropic first-party input rates as of 2026-08-30, from the pricing page.

Security

Grade A, and why

canopy CLAUDE.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 3d 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.

CLAUDE.md · 148 lines

How it starts

The opening of the file, as written. The whole thing — 148 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Canopy

Git-native prompt management for AI agent workflows. Minimal dependencies, JSONL storage, Bun runtime.

Quick Reference

  • Runtime: Bun (TypeScript)
  • Storage: JSONL files (one per record type)
  • CLI prefix: cn
  • Spec: See SPEC.md for full design

Project Structure

.canopy/           # On-disk data (prompts.jsonl, schemas.jsonl, config.yaml)
src/               # Source code (Bun/TypeScript)
SPEC.md            # Detailed specification

Conventions

  • Minimal runtime dependencies — chalk, commander, ajv (ajv powers cn config schema validation)
  • Concurrent-safe: advisory file locks + atomic writes
  • Git-native: JSONL is diffable/mergeable, merge=union gitattribute
  • All CLI commands support --json flag
  • Prompts are composed via sections and inheritance, not duplicated
  • cn emit renders to plain .md (or .ts when emitAs ends in .ts) for downstream consumption

Project Expertise (Mulch)

This project uses Mulch v0.8.0 for structured expertise management.

At the start of every session, run:

ml prime

Injects project-specific conventions, patterns, decisions, failures, references, and guides into your context. Run ml prime --files src/foo.ts before editing a file to load only records relevant to that path (per-file framing, classification age, and confirmation scores included).

For monolith projects where dumping every record wastes context, set prime.default_mode: manifest in .mulch/mulch.config.yaml (or pass --manifest) to emit a quick reference + domain index. Agents then scope-load with ml prime <domain> or ml prime --files <path>.

Before completing your task, record insights worth preserving — conventions discovered, patterns applied, failures encountered, or decisions made:

ml record <domain> --type <convention|pattern|failure|decision|reference|guide> --description "..."

Read the full file on GitHub · 148 lines

Changes

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.

  1. 3d ago First seen · 148 lines · 1,491 tokens per session scan A e8751d9da51d

Subscribe to this mod's changes

canopy CLAUDE.md is an instructions file published in the GitHub repository jayminwest/canopy (39 stars, last pushed 1mo ago), licensed MIT. It adds 1,491 tokens to every session, about $0.0075 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 2026-08-30.

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