reflect

name	reflect
description	Review chat session for mistakes, friction, and improvement opportunities; analyze and improve skills used
license	MIT
compatibility	pi
metadata	{"audience":"all-users","workflow":"quality-improvement"}

Success Criteria

Before presenting output, verify:

• ✅ Chat review covers mistakes, friction points, and unclear outputs
• ✅ Concrete, actionable improvements proposed (not vague suggestions)
• ✅ Skills used in chat are analyzed for self-checks, conciseness, and quality
• ✅ Pattern detection identifies repeated tasks that could become skills
• ✅ Clear questions asked about what to remember for future chats

Iterate up to 5 times if criteria not met.

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What I Do

When the user types "reflect", I perform a comprehensive review of the current chat session:

1. Chat Session Review

• Analyze what we've accomplished
• Identify mistakes, errors, or incorrect assumptions
• Note friction points (repeated clarifications, confusion, corrections)
• Flag unclear or incomplete outputs
• Detect frustration signals from user

2. Improvement Proposals

• Generate concrete, actionable improvements (not vague suggestions)
• Prioritize high-impact changes
• Present as a short numbered list
• Ask which improvements to remember for future sessions

3. Skill Quality Analysis

For each skill used during this chat:

a) Self-Check Validation:

• Check if skill has success criteria at the top
• Check if skill has verification instruction at bottom
• If missing: propose adding both with specific criteria for that skill
• Ensure verification includes "iterate up to 5 times if not met"

b) Token Efficiency:

• Identify verbose sections that could be more concise
• Remove redundant instructions
• Suggest structural improvements
• Preserve clarity and functionality

c) General Improvements:

• Check for outdated patterns
• Identify missing edge cases
• Suggest better organization
• Propose enhanced instructions

4. Pattern Detection

• Monitor for tasks I'm asked to do repeatedly
• Suggest creating reusable skills for common patterns
• Ask for confirmation before creating new skills
• Provide skill name and description suggestions

5. Proactive Suggestions

Suggest typing "reflect" when:

• User corrects me multiple times on same topic
• User clarifies something twice or more
• User shows signs of frustration
• Workflow feels inefficient or repetitive

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When to Use Me

Trigger explicitly when user types:

• reflect
• review session
• how are we doing?

Suggest proactively when:

• User corrects the same mistake 2+ times
• User re-explains requirements
• Multiple back-and-forth exchanges on unclear point
• User expresses frustration (e.g., "no, that's not what I meant")
• Session feels inefficient

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Output Format

Session Review

Accomplishments:

• [List what we completed]

Mistakes/Issues:

1. [Specific mistake with context]
2. [Friction point with example]

Unclear Outputs:

• [What was unclear and why]

Proposed Improvements

1. [Improvement area]: [Concrete action]
2. [Improvement area]: [Concrete action]

Which of these should I remember for future chats? [Ask user]

Skills Analysis

Skills used this session: [List skills]

For each skill:

skill-name:

• Self-check status: [✅ Has criteria / ❌ Missing]
• Token efficiency: [Observations]
• Proposed improvements:
  1. [Specific improvement]
  2. [Specific improvement]

Should I apply these improvements? [Ask user]

Pattern Detection

Repeated tasks identified:

• [Task pattern] (occurred X times)

Suggested skill: suggested-name

• Description: [What it would do]

Should I create this skill? [Ask user for confirmation]

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Examples

User: reflect

Response:

## Session Review

**Accomplishments:**
- Updated comparison charts implementation plan
- Clarified data requirements for cycles.assessmentTool vs cycles.compare
- Committed plan to repository

**Mistakes/Issues:**
1. Initially didn't explain why cycles.compare was insufficient - required follow-up question
2. First plan draft missing reference cycle assessmentTool query

**Unclear Outputs:**
- Data structure explanation could have included visual diagram earlier

## Proposed Improvements
1. **Data explanations:** Include visual structure comparisons upfront when discussing API responses
2. **Plan completeness:** Always verify both sides of comparison features (reference + comparison)
3. **Proactive clarification:** Ask "should I explain why?" when making architectural decisions

Which of these should I remember for future chats?

## Skills Analysis
No skills were used in this session.

## Pattern Detection
No repeated task patterns detected yet.

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Implementation Notes

• Review entire conversation history, not just recent messages
• Count actual occurrences of patterns (don't guess)
• Be specific about mistakes (include line numbers, quotes, context)
• Distinguish between mistakes and intentional iteration
• Focus on systemic issues, not one-off clarifications
• When suggesting new skills, check if similar skill already exists
• Token efficiency improvements should preserve all functionality
• Self-check criteria should be specific and measurable

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Verification

Before presenting output:

1. Have I reviewed the full chat history?
2. Are all mistakes/friction points specific with examples?
3. Are improvements concrete and actionable?
4. Have I analyzed all skills used?
5. Are my questions clear and answerable?

If any answer is no, iterate and improve (up to 5 times).