claw-skills AGENTS.md

Repository instructions for creating and maintaining skills in claw-skills, a collection of reusable instructions for OpenClaw. It defines the folder layout, required SKILL.md format, naming rules, and release process.

In plain words
What is it for?
Use it when adding a skill, editing its instructions or supporting files, or preparing a claw-skills release.
Why use it?
It prevents skill packages from having missing files, invalid metadata, or an inconsistent structure.

Instructions file for CodexOpenCode

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/docuspeed/claw-skills/agents-md
Clone the repo
git clone --depth 1 https://github.com/docuspeed/claw-skills

Made for: Codex, OpenCode.

Per session 488 This file is loaded in full into every session.
When invoked 488 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 $0.00488 $0.00488
Opus 5 $0.00244 $0.00244
Sonnet 5 $0.00098 $0.00098
Haiku 4.5 $0.00049 $0.00049

Measured 2d ago against content hash d3d94e29bb1b, method: parsed. Prices are Anthropic first-party input rates as of 2026-08-30, from the pricing page.

Security

Grade A, and why

claw-skills AGENTS.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.

AGENTS.md · 62 lines

What it actually says

AGENTS.md

本仓库是一些可用于 OpenClaw 的有趣且实用的 skills 集合(claw-skills),由七转科技维护。

项目结构

claw-skills/
├── AGENTS.md
├── LICENSE
├── README.md
├── .gitignore
└── <skill-name>/
    ├── SKILL.md          # 必需,skill 定义文件
    ├── scripts/          # 可选,辅助脚本
    ├── references/       # 可选,参考资料/文献
    └── assets/           # 可选,图片等静态资源

每个 skill 是一个独立目录,目录名即 skill 名称(使用小写英文 + 连字符命名)。目录内必须包含 SKILL.md 文件,可选包含 scripts/references/assets/ 等子目录。

SKILL.md 格式规范

每个 SKILL.md 必须包含 YAML frontmatter 和正文:

---
name: skill-name
description: 简短描述该 skill 的用途
---

# Skill 标题

正文内容...
  • name:与目录名一致
  • description:一句话描述 skill 功能
  • 正文:skill 的完整定义与规则

贡献新 Skill

  1. 在仓库根目录创建以 skill 名称命名的新目录
  2. 在目录内创建 SKILL.md,遵循上述格式规范
  3. 提交 PR 并确保 frontmatter 格式正确

发版流程

本仓库使用日期版本号(如 v2026.04.03),通过 GitHub Releases 发布更新。

发版步骤:

  1. 确保所有变更已提交到 master 分支
  2. 创建日期 tag 并推送:
    git tag -a v2026.04.03 -m "发版说明"
    git push origin v2026.04.03
    
  3. GitHub Actions 会自动创建 Release,并根据两个 tag 之间的 commit 记录生成更新说明。

用户可通过仓库页面 Watch -> Custom -> Releases 订阅发版通知。

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. 2d ago First seen · 62 lines · 488 tokens per session scan A d3d94e29bb1b

Subscribe to this mod's changes

claw-skills AGENTS.md is an instructions file published in the GitHub repository docuspeed/claw-skills (92 stars, last pushed 5mo ago), licensed MIT. It adds 488 tokens to every session, about $0.0024 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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