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.
git clone --depth 1 https://github.com/wunamesst/skillsWrote 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/commands/wunamesst/skills/extract)<a href="https://agentmods.dev/commands/wunamesst/skills/extract"><img src="https://agentmods.dev/badge/commands/wunamesst/skills/extract/github.svg" alt="Measured on agentmods" height="20"></a>Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.
<a href="https://agentmods.dev/commands/wunamesst/skills/extract"><img src="https://agentmods.dev/badge/commands/wunamesst/skills/extract.svg" alt="Reviewed on agentmods" width="80" 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 | $0.00023 | $0.00217 |
| Opus 5.5 | $0.00009 | $0.00087 |
| Sonnet 5.5 | $0.00005 | $0.00043 |
| Haiku 4.5 | $0.00002 | $0.00022 |
Grade A, and why
extract 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 1mo 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.
What it actually says
从个人项目或工作文档中萃取可复用的知识模式：
- 确认用户授权（本命令即视为授权）
- 读取来源路径下的文件
- 剥离业务属性（公司名、具体数据、内部术语）
- 提炼通用模式、架构原则、设计决策
- 写入
02_Wiki/项目知识/或02_Wiki/业务洞察/ - Frontmatter 标注
[业务萃取]或[个人萃取] - 追加
00_SYSTEM/INGEST_LOG.md
示例： /wiki:extract 04_Work/51Talk/CRM/capacity 业务洞察
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.
- 1mo ago First seen · 19 lines · 23 tokens per session scan A 7b4d46803169
extract is a command published in the GitHub repository wunamesst/skills (2 stars, last pushed 2mo ago), licensed MIT. It adds 23 tokens to every session and 217 once invoked, about $0.0001 per session on Opus 5.5. 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 commands, from other repositories
setup-context
Set up your Skill Memory — a pm-context.md every skill reads so outputs come back tailored to you.
brain
Set up or use your Professional Brain — init, ingest, recall, or review.
notes
Maintain the ROOM BRAIN — the structured state file the coach reasons from.
create
Capture current session context to docs/handoff/HANDOFF.md.
checklist
Generate a custom checklist for the current feature based on user requirements.
clarify
Identify underspecified areas in the current feature spec by asking up to 5 highly targeted clarification questions and encoding answers back into the spec.