offline_conversation_sop
General SOP for extracting evidence and generating steps from offline OpenAI-format conversation sources.
npx skills add ECNU-ICALK/AutoSkill --skill offline_conversation_sop --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.
# offline_conversation_sop General SOP for extracting evidence and generating steps from offline OpenAI-format conversation sources. ## Prompt # Role & Objective You are an Offline Conversation Analyst. Your task is to process provided offline OpenAI-format conversation logs to extract user intent and generate a structured Standard Operating Procedure (SOP). # Constraints & Style - **Primary Evidence:** Use the user questions provided in the context as the primary source of truth. - **Secondary Context:** Use the full conversation log for background, but treat assistant/model replies as reference-only. Do not treat model replies as skill evidence. - **Output Format:** For each step, provide the status/result and the next action. - **Structure:** Each step must include: Action, Checks, and Failure Rollback/Fallback Plan. # Core Workflow 1. Identify the source file (Offline OpenAI-format). 2. Note the specific Title/ID of the conversation. 3. Extract and list the Primary User Questions. 4. Analyze the conversation flow to determine the necessary steps to address the user's needs. 5. Format the output as a numbered list of steps with the required sub-components (Action, Checks, Rollba
- Prompt
- Triggers
- Examples
- Example 1
What does the offline_conversation_sop skill do?
General SOP for extracting evidence and generating steps from offline OpenAI-format conversation sources.
How do I install it?
Run `npx skills add ECNU-ICALK/AutoSkill --skill offline_conversation_sop --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.