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/workflow-from-chats

@bca6129
by cursorcursor/plugins9.1k stars
857

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.

Use this Skill: https://skilld.dev/gh/cursor/plugins/workflow-from-chats

This session only. Nothing lands on disk.

SKILL.md

≈65 tokens always: the name and description. ≈599 when used: this file.

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.

Source: SKILL.md on GitHub

No alerts16d3 checks · Risk SAFE
  • Gen Agent Trust Hub16d

    This skill analyzes chat history to automatically generate agent rules and documentation. While it includes instructions to protect sensitive data, it creates a surface for indirect prompt injection where instructions in chat history could be promoted to durable agent rules.

  • Socket16d

    No alerts

  • Snyk16d

    Risk: LOW · No issues

Signed by skilld at bca6129. This ties the file your Agent reads to that commit on GitHub. It does not review the instructions.

Last checked against GitHub yesterday.

Activeupdated 5 months ago

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