dannote/dot-pi/chat-to-skill

Claude Code and agent skill by dannote/dot-pi

Trust tier 3
  • community
Source check pending

Checking that the SKILL.md file is still in the repository.

Convert current chat session into a reusable skill. Use when user says "/chat-to-skill", "save this as skill", "create skill from chat", "turn this into a skill", or wants to preserve learnings from the conversation as long-term memory.

Install

npx vskill@latest install dannote/dot-pi/chat-to-skill

SKILL.md

Chat to Skill

Transform conversation history into reusable skills — long-term memory for Claude.

Process

1. Analyze Dialog

Scan the entire conversation to identify:

  • Primary goal: What was the user trying to achieve?
  • Secondary goals: Any related objectives discovered along the way
  • Errors encountered: Mistakes, dead ends, wrong approaches
  • Successful path: What actually worked
2. Abstract to Reusable Patterns

Critical: Do NOT create skills for specific cases. Abstract to general patterns.

Ask yourself:

  • What CATEGORY of problem was solved? (not the specific instance)
  • What would this look like with different data/context?
  • Would this skill be useful in other projects?

Abstraction levels (from bad to good):

Too specific (BAD)Good abstraction
"Seed users from client Excel""Import spreadsheet data into Rails"
"Parse names into fields"(implementation detail, not a skill)
"Fix pytest in project X""Configure pytest for monorepos"
"Add dark mode to app Y""Implement theme switching in React"

Rules:

  • Remove project names, organization names, specific entities
  • Focus on the TECHNIQUE, not the specific data
  • If something is just an implementation detail (name parsing, date formatting), it's not a separate skill
  • One dialog = usually one skill (the main workflow), not multiple micro-skills
3. Extract Context-Specific Details

Depending on the task type, look for:

Development tasks:

  • Commands and flags that worked
  • Versions and compatibility (what works with what)
  • Configuration that was needed
  • Code patterns and architectural decisions
  • Debugging process (how the root cause was found)
  • Tool/library choices and why

Research/analysis tasks:

  • Sources that proved useful
  • Search strategies that worked
  • How to validate findings

Process/workflow tasks:

  • Order of operations (what must come first)
  • Decision criteria (how choices were made)
  • Stakeholders or dependencies

Any task:

  • Prerequisites that weren't obvious
  • Context that matters for success
  • Signs that indicate the right/wrong path
4. Choose Topic (if multiple found)

If dialog contains several distinct learnable patterns, use AskUserQuestion:

Question: "I found several skill candidates. Which to create?"

Options: List 2-4 abstracted topics (not specific tasks), plus "All of them"

5. Validate Skill Candidate

Before proposing, check:

  • [ ] Is this reusable in other projects/contexts?
  • [ ] Is this a workflow/technique, not just a one-off fix?
  • [ ] Would future-me benefit from having this skill?
  • [ ] Is it abstracted enough to apply broadly?

If NO to any — either abstract further or skip skill creation.

6. Propose Topic (if valid)

Present ONE main skill (not a list of micro-topics):

Skill candidate: [Abstracted name]
What it captures: [1-2 sentences about the reusable pattern]
Key learnings:
- [Main insight 1]
- [Main insight 2]
- [Mistake to avoid]

Then ask using AskUserQuestion tool:

Question: "How does this skill proposal look?"

Options:

  1. "Good, create it" — proceed to step 7
  2. "Too specific" — re-abstract: remove project/entity names, find broader pattern
  3. "Wrong focus" — re-analyze: what was the MAIN technique vs implementation details?
  4. "Not reusable" — reconsider: is this a one-off task or a recurring pattern?
7. Revise (if needed)

Based on user's choice, fix the specific issue:

"Too specific":

  • What broader category does this belong to?
  • Would this apply with different tools/platforms? Generalize.

"Wrong focus":

  • What would you google to solve this problem?
  • The answer is probably the real skill name.

"Not reusable":

  • How often would this exact situation repeat?
  • If rarely — maybe no skill needed. Ask user what they hoped to capture.
8. Prepare Knowledge Package

Goal: One sentence — what this skill helps achieve

Trigger: When should this skill activate? (keywords, file types, contexts)

Mistakes to avoid:

  • Specific errors from the dialog
  • Why they were wrong
  • What they cost (time, confusion)

Optimal path:

  • Shortest working sequence
  • No exploration, only essentials
  • Include specific commands/configs if applicable

Key details:

  • Versions/compatibility if relevant
  • Non-obvious prerequisites
  • How to verify success
9. Create Skill

Use /skill-creator with the prepared knowledge package.

Security

  • Security scanPassed, 90 of 100Pattern checks on the skill's files.
  • Model reviewPassed

Quality evaluation

  • Task evaluationNot runNo evaluation yet. Run one in Skill Studio.

Source

Popularity

Repository stars
56
Repository forks
4
7-day trend score
20

Stars and forks are for the whole GitHub repository, not this skill alone. Not refreshed yet.

Works with

Any agent vskill installs to: 56 targets in all. These 39 have a page on this site.

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  • AI Agent
  • Tabnine Chat
  • Sourcegraph Cody
  • Amazon Q
  • Firebase Genkit
  • Sweep
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  • Mentat
  • Claude Desktop
  • Aider
  • GPT Pilot
  • Plandex
  • bolt.new
  • v0
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  • Anse
  • TypingMind
  • BetterChatGPT
  • LibreChat
  • Warp AI
  • Pieces
  • Fig AI
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