paw CLAUDE.md

paw CLAUDE.md is an instructions file for coding agents from Effulgent-Point/paw. It costs 812 tokens per session, scanned B, original, MIT.

A set of instructions for Paw, a toolkit that gives AI coding agents rules, specialized reviewers, and domain knowledge, with permissions limited by agent role.

In plain words
What is it for?
Use it to guide code changes, enforce tests before implementation, run specialized reviews, manage incidents or migrations, and follow safe branch and push rules.
Why use it?
It helps keep agent actions bounded and makes repository rules, testing, and Git practices consistent across independently usable components.

Instructions file

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/effulgent-point/paw/claude-md
Clone the repo
git clone --depth 1 https://github.com/Effulgent-Point/paw

Wrote 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.

agentmods badge for paw CLAUDE.md

README.md
[![agentmods](https://agentmods.dev/badge/instructions/effulgent-point/paw/claude-md.svg)](https://agentmods.dev/instructions/effulgent-point/paw/claude-md)
Your own site
<a href="https://agentmods.dev/instructions/effulgent-point/paw/claude-md"><img src="https://agentmods.dev/badge/instructions/effulgent-point/paw/claude-md.svg" alt="Measured on agentmods" height="20"></a>
Per session 812 This file is loaded in full into every session.
When invoked 812 The same file — it is already loaded in full.
Security scan B 1 finding. 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 $0.00812 $0.00812
Opus 5 $0.00406 $0.00406
Sonnet 5 $0.00162 $0.00162
Haiku 4.5 $0.00081 $0.00081

Measured 5d ago against content hash 2c5359894cfe, method: parsed. Prices are Anthropic first-party input rates as of 2026-08-30, from the pricing page.

Security

Grade B, and why

paw CLAUDE.md scanned grade B with 1 finding 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 5d 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.

Reads agent configuration directoriesmediumAgent snooping

.claude/, .codex/, .gemini/ hold keys, settings and other credentials a mod has no legitimate need for.

- **`hooks/install_hooks.py`** assumes the `~/.claude/settings.json` layout — specifically a top-level `hooks` object keyed by event name. It edits that file in place.
CLAUDE.md · 67 lines

How it starts

The opening of the file, as written. The whole thing — 67 lines — stays where its author put it; the contents beside it link to each section on GitHub.

paw — Personal Agent Workforce

What paw is

A lightweight, composable toolkit that gives your AI coding agent standards enforcement, specialized reviewers, and domain knowledge. Every piece works standalone.

How to work in this repo

Composability is the design

Every directory runs independently. Agents work without skills. Hooks work without agents. Rules are plain markdown anyone can read. Don't add cross-directory dependencies.

Agents have scoped permissions

Most agents are read-only. Only 4 of 18 agents have full access (builder, merge-resolver, migration-architect, incident-commander). This is intentional — trust through bounded autonomy.

Rules are the source of truth

If a rule in rules/ contradicts how an agent behaves, fix the agent. Rules don't bend to implementation convenience.

Tests before code

The builder agent writes failing tests first, then implementation. The test-runner agent verifies. The auto_test_detect hook warns on missing tests.

Git rules

  • Always git pull (merge, not rebase) before push
  • Never git rebase against published history
  • Never git push --force to any branch
  • Never commit to main directly — use a feature branch
  • Always verify git branch shows the intended branch before committing

These are enforced by hooks/git_safety.py and hooks/branch_guard.py.

Adding an agent

  1. Pick the context it loads from contexts/.
  2. Pick the rules it references from rules/.
  3. Define minimum tools — least privilege.
  4. Write the role, process, outputs, done-when.
  5. Add to agents/README.md.

Load contexts/X in an agent file is a prompt directive, not a mechanical import. The AI tool reads the line and opens the file itself. This works in Claude Code, where agent files are loaded into context and the agent can read the repo. In other tools, you may need to paste or otherwise include the referenced context and rule files manually.

Adding a rule

  1. Write the statement, why, hard rules, soft rules.
  2. Identify which agents/hooks enforce it.
  3. Update relevant agents to reference the new rule.
  4. Add to rules/README.md.

Read the full file on GitHub · 67 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. 5d ago First seen · 67 lines · 812 tokens per session scan B 2c5359894cfe

Subscribe to this mod's changes

paw CLAUDE.md is an instructions file published in the GitHub repository Effulgent-Point/paw (2 stars, last pushed 25d ago), licensed MIT. It adds 812 tokens to every session, about $0.0041 per session on Opus 5. A static security scan graded it B with 1 finding (reads agent configuration directories). No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-31.