self / sop_extraction
General SOP for extracting and structuring processes or checklists from conversation evidence.
npx skills add ECNU-ICALK/AutoSkill --skill self-sop_extraction --agent claude-code
Same command for any agent — swap --agent for codex, cursor, copilot.
Weekly change comes from our own snapshots, not the repository page — it measures attention, not adoption.
# self / sop_extraction General SOP for extracting and structuring processes or checklists from conversation evidence. ## Prompt Follow this SOP to extract and structure processes from conversation evidence (replace specifics with placeholders like <PROJECT>/<ENV>/<VERSION>): 1) Identify the Offline OpenAI-format conversation source. 2) Note the Title/ID of the conversation. 3) Use the user questions provided as the PRIMARY extraction evidence. 4) Use the full conversation context as SECONDARY reference. 5) In the full conversation section, assistant/model replies are reference-only and not skill evidence. 6) Primary User Questions (main evidence): [Extract from context] 7) Configuration/Context Details: [Extract from context] For each step, include: action, checks, and failure rollback/fallback plan. Output format: for each step number, provide status/result and what to do next. ## Triggers - Use when the user asks for a process or checklist. - Use when you want to reuse a previously mentioned method/SOP. ## Examples ### Example 1 Input: Break this into best-practice, executable steps.
- Prompt
- Triggers
- Examples
- Example 1
What does the self / sop_extraction skill do?
General SOP for extracting and structuring processes or checklists from conversation evidence.
How do I install it?
Run `npx skills add ECNU-ICALK/AutoSkill --skill self-sop_extraction --agent claude-code` — it drops the skill into your project so the agent can pick it up. Swap the --agent value for codex, cursor or copilot if you use one of those.
Where does this skill come from?
From ECNU-ICALK/AutoSkill, a repository with 539 stars. We read it straight from the repository tree rather than a submitted listing, so what you see here is what is actually published.
Is a popular skill a good skill?
Not necessarily. Stars measure attention, not adoption — a repository can trend for a week and be abandoned. That is why we show the weekly change from our own snapshots next to the total, instead of a single flattering number.