PluginBench
Skill
Pass
Audit score 90

workflow-from-chats

cursor/plugins

Extract reusable workflow preferences from Cursor chats and convert them into skills, rules, or docs.

What is workflow-from-chats?

This skill analyzes your recent Cursor conversations to identify durable working preferences, patterns, and corrections. Use it to capture how you actually work, generate personalized agent guidance, or document team workflows without manually summarizing chats.

  • Scans recent chat transcripts (default last 7 days) for explicit preferences and workflow patterns
  • Extracts preference atoms with confidence ratings: strong, medium, weak, or contradicted
  • Clusters preferences by workflow shape: shipping, review, debugging, delegation, validation, and others
  • Rates evidence quality and filters anecdotal observations that won't help future tasks
  • Recommends the right artifact type: new skill, skill edit, rule, workflow doc, or no artifact
  • Protects privacy by excluding local paths, secrets, customer data, and credentials

How to install workflow-from-chats

npx skills add https://github.com/cursor/plugins --skill workflow-from-chats
Claude Code
Cursor
Windsurf
Cline

How to use workflow-from-chats

  1. 1.Ask the skill to analyze a specific workflow or preference surface (e.g., 'extract my code review preferences')
  2. 2.Optionally specify a custom time window; defaults to the last 7 days
  3. 3.Review the synthesis: target workflow, evidence corpus, preference profile, and proposed artifacts
  4. 4.Approve or refine the recommended artifact (skill, rule, workflow doc, or none)
  5. 5.The skill drafts only reusable guidance, filtering out task-specific or anecdotal observations

Use cases

Good for
  • Capture your coding standards and review preferences after several chats to encode them as a reusable rule
  • Mine feedback from a week of debugging sessions to identify your preferred error-handling workflow
  • Generate team-specific agent guidance by analyzing shared conversation patterns across multiple developers
  • Document a recurring multi-step process (e.g., shipping workflow) as a new skill after observing it in chats
  • Personalize an agent's behavior by extracting decision rules you've corrected multiple times
Who it's for
  • Individual developers wanting to codify their working style into reusable agent skills
  • Team leads documenting shared workflows and preferences for consistent agent behavior
  • Engineering managers capturing best practices from team conversations
  • Anyone seeking to turn implicit chat feedback into explicit, durable guidance

workflow-from-chats FAQ

What if my preferences contradict across different chats?

The skill rates confidence as 'contradicted' and asks you before writing files, so you can clarify which preference applies in which context.

Does this expose my private chat content or secrets?

No. The skill explicitly excludes local transcript paths, secrets, customer data, private chat content, and credentials from any output.

Can I analyze chats older than 7 days?

Yes. You can specify a custom time window when you invoke the skill; 7 days is the default.

What's the difference between a skill, rule, and workflow doc?

A skill is a recurring multi-step workflow with clear triggers; a rule is general behavior that should apply broadly; a workflow doc is useful context that isn't reliably triggerable.

Will this summarize my chats?

No. The skill extracts reusable workflow guidance and preference atoms, not chat summaries. It filters anecdotes and focuses only on patterns that will help future tasks.

Full instructions (SKILL.md)

Source of truth, from cursor/plugins.


name: workflow-from-chats description: 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.

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.
  • Workflow doc: useful context that is not reliably triggerable.
  • No artifact: situational, stale, or low-confidence observation.

Output

Return a concise synthesis first:

  • Target workflow.
  • Evidence corpus with parent conversation citations only.
  • Preference profile.
  • Adopt, consider, dismissed.
  • Proposed artifacts.
  • Open questions only if they block writing.