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/pyautolabs/pyautoarray/claude-mdgit clone --depth 1 https://github.com/PyAutoLabs/PyAutoArrayWhat 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 | $0.00065 | $0.00065 |
| Opus 5 | $0.00032 | $0.00032 |
| Sonnet 5 | $0.00013 | $0.00013 |
| Haiku 4.5 | $0.00006 | $0.00006 |
Grade A, and why
PyAutoArray 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 yesterday.
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.
Copies of this mod
1 near-identical copy found in the catalogue:
- PyAutoNerves CLAUDE.md — 97% identical, 2 lines differ
What it actually says
PyAutoArray — agent instructions
The canonical, agent-agnostic instructions live in AGENTS.md. Claude Code loads them
via the import below; if your tool does not process @-imports, open AGENTS.md in
this directory and read it directly.
@AGENTS.md
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.
- yesterday First seen · 6 lines · 65 tokens per session scan A 90eca13d2ffc
PyAutoArray CLAUDE.md is an instructions file published in the GitHub repository PyAutoLabs/PyAutoArray (10 stars, last pushed 2d ago), licensed MIT. It adds 65 tokens to every session, about $0.0003 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
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scholaraio AGENTS.md
Instructions for ZimoLiao/scholaraio, covering scholaraio - agent entry, what scholaraio is, how to work in this repo, start here and skill-first workflow.
OpenSDL AGENTS.md
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pycaret AGENTS.md
AGENTS.md instructions for pycaret/pycaret, covering agents.md — pycaret agent instructions, tl;dr — the 60-second briefing, start here, non-negotiables and universal rules.
scitex-python CLAUDE.md
Claude Code instructions for scitex-ai/scitex-python, covering workflow orchestration, 1. plan mode default, 2. subagent strategy, 3. self-improvement loop and 4. verification before done.
math-anchor CLAUDE.md
Claude Code instructions for tetracoralla/math-anchor, a project described as: Math Anchor — safe exact and scientific math, units, and dimensional analysis for humans and Agents (macOS + MCP/Codex plugin).