Agent skill · operations · cursor
workflow-from-chats
Extract durable working preferences from recent Cursor chats and convert them into skills, rules, or workflow docs. Use when asked to learn preferences, mine feedback, personalize workflows, or generate team/person-specific agent guidance.
Why this skill is useful
Extracts specific user preferences and workflows from chat transcripts, providing personalized guidance that the AI wouldn't generate on its own.
What it needs
About 1k tokens when loaded. Last updated 2026-08-06. 2,555 stars on the source repository.
What this skill does
Workflow From Chats Infer durable working preferences from recent chats. Do not summarize chats; extract reusable workflow guidance. Scope Default to the last 7 days unless the user asks for a different window. Read parent transcripts and relevant subagent transcripts. Use subagent content as evidence, but cite only parent conversations. Do not expose local transcript paths, secrets, customer data, private chat content, or credentials. Workflow 1. State the target workflow or preference surface in one paragraph. 2. Build an internal transcript inventory: title/topic, parent conversation ID, approximate date, completion state, relevant subagents, and why it may contain preference evidence. 3. Scan for explicit preferences, corrections, and workflow markers such as "I prefer", "always", "never", "not what I asked", "stop", "review", "PR", "CI", "logs", and "skill". 4. Extract preference atoms: trigger, workflow step, decision rule, quality bar, stop condition, evidence, and confidence. 5. Rate confidence as strong, medium, weak, or contradicted. 6. Cluster by workflow shape rather than transcript: shipping, review, simplification, debugging, capture, communication, delegation, or validation. 7. Choose the artifact: new skill, skill edit, rule, workflow doc, or no artifact. 8. Draft only the reusable guidance. Filter anecdotes that will not help future tasks. Confidence Strong: explicit user preference, workflow-changing correction, repeated parent-chat pattern, or direct request to encode behavior. Medium: accepted workflow, repeated tool/model/validation preference, or subagent consensus that the parent used successfully. Weak: agent-chosen behavior with no user feedback, one ambiguous transcript, or a likely task-specific correction. Contradicted: evidence points in incompatible directions; ask the user before writing files. Artifact Choice Skill: recurring multi-step workflow with clear triggers. Rule: general behavior that should apply broadly. …
How to use it
Reference it in AdaL, Claude Code, Cursor or any coding agent — nothing to install:
@skills cursor/workflow-from-chats