Claude Skill

chat-to-skill

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.

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Download dannote-dot-pi-skills_chat-to-skill-b92ab10.zip · 2 KB
Part of dannote/dot-pi — 15 skills

Install

skills CLI npx skills add https://github.com/dannote/dot-pi/tree/master/skills/chat-to-skill
Claude Code claude plugin marketplace add https://llmmart.ai/marketplace.json && claude plugin install dannote-dot-pi@llmmart
Git git clone https://github.com/dannote/dot-pi.git

The skills CLI installs just this skill, for any of its supported agents. Claude Code installs the whole dannote/dot-pi collection as a plugin from our marketplace. Git is the plain clone.

Skill manifest

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.

Files (dot-pi)
  • SKILL.md 4.8 KB
    ---
    name: chat-to-skill
    description: 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.
    ---
    
    # 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.
    

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