How do I install the Cursor Plugin Teamkit Workflow From Chats skill?

Run npx skillmds@latest add kunanonj/cursor-plugin-teamkit-workflow-from-chats in your terminal (requires Node.js), paste this page's agent-chat prompt into Claude, Cursor, or any MCP-connected agent, or download the SKILL.md file and copy it into your agent's skills directory.

Is Cursor Plugin Teamkit Workflow From Chats safe to use?

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Which AI agents work with Cursor Plugin Teamkit Workflow From Chats?

This skill is tagged as working with Claude Code, Claude.ai, OpenAI Codex. SKILL.md is an open format, so most agents that read a skills directory can load it too.

Is Cursor Plugin Teamkit Workflow From Chats free to use?

Yes. Installing skills from SkillMD is free, and the skill stays under its author's original license.

Who published Cursor Plugin Teamkit Workflow From Chats?

KunanonJ (@kunanonj) published this skill. Their other Agent Skills are listed on their SkillMD profile.

Cursor Plugin Teamkit Workflow From Chats by kunanonj

Name: Cursor Plugin Teamkit Workflow From Chats
Author: KunanonJ

Cursor Plugin Teamkit 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.

KunanonJ 27b8d20 2.6 KB Updated Sep 17, 2026

File contents

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

State the target workflow or preference surface in one paragraph.
Build an internal transcript inventory: title/topic, parent conversation ID, approximate date, completion state, relevant subagents, and why it may contain preference evidence.
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".
Extract preference atoms: trigger, workflow step, decision rule, quality bar, stop condition, evidence, and confidence.
Rate confidence as strong, medium, weak, or contradicted.
Cluster by workflow shape rather than transcript: shipping, review, simplification, debugging, capture, communication, delegation, or validation.
Choose the artifact: new skill, skill edit, rule, workflow doc, or no artifact.
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.

---name: cursor-plugin-teamkit-workflow-from-chatsdescription: 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 ChatsInfer 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.## Workflow1. 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.## OutputReturn 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.

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