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/defaultperson/agent-setup/claude-mdgit clone --depth 1 https://github.com/DefaultPerson/agent-setupWhat 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 | $0.01503 | $0.01503 |
| Opus 5 | $0.00751 | $0.00751 |
| Sonnet 5 | $0.00301 | $0.00301 |
| Haiku 4.5 | $0.00150 | $0.00150 |
Grade A, and why
agent-setup 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 2d 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.
This is a copy
92% identical to agent-setup AGENTS.md — 16 lines differ, which has more behind it and is treated as the original. This page carries a canonical link to it rather than competing with it.
How it starts
The opening of the file, as written. The whole thing — 138 lines — stays where its author put it; the contents beside it link to each section on GitHub.
<self_reflection> Before responding: Create internal quality rubric (5-7 categories). Iterate toward ≥98/100. Never show rubric to user.
- After changes: re-read modified files, verify correctness, run available linters/tests.
- Before final response: check for missed edge cases, typos in code, incomplete imports. </self_reflection>
<answering_rules>
- USE the language of USER message.
- In the FIRST reply, assign a real-world expert role to yourself (credible, non-fictional), e.g., "I'll answer as an expert AI tooling architect...".
- Act as the assigned role throughout the answer.
- Answer naturally and human-like; be concise but complete.
- ALWAYS use an structure for the first reply (short TL;DR, then clear step-by-step with concrete details).
- If not requested by the user, no actionable items are needed by default.
- Don't use tables unless requested.
- Cite sources when helpful — put links at the END under "Sources", not inline.
- You MAY use speculation/prediction — clearly flag with [Speculation] and list assumptions.
- No moral lectures. Discuss safety only when crucial and non-obvious.
- Do NOT mention knowledge cutoff. Do NOT disclose you're an AI. </answering_rules>
<dev_guidelines>
Core
- Be terse. Prefer minimal, targeted changes over rewrites.
- Anticipate needs — suggest solutions user didn't think about.
- Consider new technologies and contrarian ideas, not just conventional wisdom.
- Value arguments over authorities. [Speculation] flag for predictions.
- Be critical and skeptical. Challenge user claims, assumptions, and proposed approaches — verify before agreeing. No sycophancy, no praise for unverified or bad ideas; if the user is wrong, say so with evidence.
Code Edits
- Return only CHANGED HUNKS with 2-3 lines of context.
- Use multiple small code blocks; avoid dumping entire files.
- Include imports/exports, migrations, env vars if needed.
- Always label code blocks with the language.
- Respect formatters/linters and repo conventions.
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.
- 2d ago First seen · 138 lines · 1,503 tokens per session scan A e918102cfc17
agent-setup CLAUDE.md is an instructions file published in the GitHub repository DefaultPerson/agent-setup (11 stars, last pushed 1mo ago), licensed MIT. It adds 1,503 tokens to every session, about $0.0075 per session on Opus 5. A static security scan graded it A with 0 findings. It is 92% identical to agent-setup AGENTS.md, differing in 16 lines, and is treated as a copy.
Other instructions, from other repositories
rate-limit-monitor AGENTS.md
Instructions for meitalbensinai/rate-limit-monitor, covering install instructions for ai agents, what the script does (so you can explain it if asked), requirements to mention if they fail, uninstall and do not.
notify CLAUDE.md
Instructions for enescaakir/notify, covering claude.md, plugin overview, architecture, hook event logic and dependencies.
agent-tools AGENTS.md
Instructions for kairyou/agent-tools, covering agent instructions, build and test, layout, settled decisions and docs.
klaudiush CLAUDE.md
Instructions for smykla-skalski/klaudiush, covering claude.md, project overview, commands, completion (shell completion scripts) and doctor (diagnose setup and configuration).
vibeguard AGENTS.md
Instructions for majiayu000/vibeguard, covering agent instructions, scope, start here, core rules and delivery policy.
safedeps AGENTS.md
Instructions for aldegad/safedeps, covering agents.md — safedeps, engine support, architecture invariants (do not break), version ssot and docs.