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/kcass16/kevin/claude-mdgit clone --depth 1 https://github.com/kcass16/kevinWrote 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/kcass16/kevin/claude-md)<a href="https://agentmods.dev/instructions/kcass16/kevin/claude-md"><img src="https://agentmods.dev/badge/instructions/kcass16/kevin/claude-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 5.1 | $0.01507 | $0.01507 |
| Opus 5 | $0.00754 | $0.00754 |
| Sonnet 5 | $0.00301 | $0.00301 |
| Haiku 4.5 | $0.00151 | $0.00151 |
Grade A, and why
kevin 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 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.
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.
The source is not reproduced here
A licence we could not identify
The repository carries a LICENSE file, but it is custom or dual enough that GitHub cannot name it and neither can this catalogue. Unknown terms are not permission, so the body is not copied here. Read the licence at the source and decide for yourself.
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.
- 5d ago First seen · 121 lines · 1,507 tokens per session scan A 33ea5ee24a31
kevin CLAUDE.md is an instructions file published in the GitHub repository kcass16/kevin (11 stars, last pushed 5mo ago), with no licence file. It adds 1,507 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.
Other instructions, from other repositories
open-agreements AGENTS.md
AGENTS.md instructions for open-agreements/open-agreements, covering repository guide and local mcp servers.
fedlex-mcp CLAUDE.md
Claude Code instructions for malkreide/fedlex-mcp, covering claude.md, teil 1 — portfolio-konventionen, vor der arbeit, tests and wenn etwas rot ist.
korean-firefighter-law-mcp CLAUDE.md
Claude Code instructions for ssd7830-cmyk/korean-firefighter-law-mcp, covering korean-firefighter-law-mcp, a. 답변 규칙 — 기억이 아니라 이 저장소의 코드가 근거다, b. mcp 도구 사용 and c. 작업 규칙.
contract-ops-mcp AGENTS.md
AGENTS.md instructions for DrBaher/contract-ops-mcp, covering agents, discovery, output contract, safety boundaries (important) and typical loop.
mcp-saos AGENTS.md
Instructions for matematicsolutions/mcp-saos, covering agents.md - mcp-saos, project goal, matematic context (hard constraints), mcp tools (tools contract) and build and test.
legal-case-research AGENTS.md
AGENTS.md instructions for silvrblt/legal-case-research, covering agents.md —— 给 ai 智能体的运行指南（工具无关）, 这个项目是什么, 数据从哪来（两种，二选一）, 一个智能体应当怎么跑 and 哪些 ai 能跑完这套工作流.