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 skills add YangsonHung/awesome-agent-skills --skill ax-extract-workflow-cngit clone --depth 1 https://github.com/YangsonHung/awesome-agent-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/skills/yangsonhung/awesome-agent-skills/ax-extract-workflow-cn)<a href="https://agentmods.dev/skills/yangsonhung/awesome-agent-skills/ax-extract-workflow-cn"><img src="https://agentmods.dev/badge/skills/yangsonhung/awesome-agent-skills/ax-extract-workflow-cn/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/skills/yangsonhung/awesome-agent-skills/ax-extract-workflow-cn"><img src="https://agentmods.dev/badge/skills/yangsonhung/awesome-agent-skills/ax-extract-workflow-cn.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 | $0.00039 | $0.00722 |
| Opus 5 | $0.00019 | $0.00361 |
| Sonnet 5 | $0.00008 | $0.00144 |
| Haiku 4.5 | $0.00004 | $0.00072 |
Grade A, and why
ax-extract-workflow-cn 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 11d 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
ax 工作流复盘
Overview
从本机 ax 数据中重建一个已交付成果背后的工作流。先确定锚点，再找到相关会话，查看对话、工具、技能、提交和子代理委派记录，最后写出一份紧凑、可追溯的复盘。
本技能假设已经安装 ax，相关会话已经完成 ingest，并且本机 ax 数据库可访问。
何时使用
当用户有以下需求时使用本技能：
- 想知道某个功能、PR、演示或成果是怎么交付的
- 想复盘某个结果为什么成功
- 想查看某个日期、提交、主题或仓库事件附近的工作流
- 想找出哪些会话、工具、技能或关键决策促成了某个成果
- 想把过去一次有效的 agent 工作整理成可复用做法
不要使用
以下场景不应使用本技能：
- 只是查看最近做了什么
- 尚未查看历史证据就开始写新的实施计划
- 与具体成果、日期或提交无关的项目状态汇报
- 本机没有可用 ax 数据，却要求复盘细节
使用说明
- 确定锚点：
- 提交 SHA：直接使用该提交。
- 日期：查看该日期前后的短窗口。
- 主题或成果名称：先搜索相关提交。
- 当前仓库的近期工作：查看当前仓库最近会话。
- 查找候选会话：
ax recall "<topic>" --sources=commit --json
ax sessions near <sha> --json
ax sessions around <date> --days=3 --json
ax sessions here --days=14 --json
- 选择最多五个会话。优先选择回合数较多、匹配提交、涉及相关文件，或有相关工具和技能使用记录的会话。
- 查看每个选中的会话：
ax sessions show <id> --json
ax sessions show <id> --by-role
ax sessions show <id> --expand=<subagent-uuid>
- 如果 ax 无法连接数据库，告诉用户先启动 ax 服务，然后停止。不要编造证据。
- 基于证据写复盘：
- 有序工作流：先做了什么，接着做了什么，最后如何收尾。
- 技能和工具作用：说明关键技能或工具各自产出了什么。
- 关键决策：记录用户引导、取舍或改变方向的节点。
- 可复用做法：总结下一次如何复现类似流程。
输出
输出 Markdown，包含：
- 一段摘要
- 按顺序排列的工作流时间线
- 带会话 id、提交或命令的关键证据
- 证据足够时，给出简短可复用流程
语气保持事实化。引用本机证据。无法确认的地方明确标注未知。
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.
- 11d ago First seen · 72 lines · 39 tokens per session scan A 037c6b52ac70
ax-extract-workflow-cn is a skill published in the GitHub repository YangsonHung/awesome-agent-skills (18 stars, last pushed 1mo ago), licensed MIT. It adds 39 tokens to every session and 722 once invoked, about $0.0002 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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