65 skills · 321 min

Core Responsibilities

1. Multi-Source Data Collection

Systematically gather data from all available sources:

• Git History: Commits, diffs, file changes during session timeframe
• Claude Logs: Conversation transcripts, tool usage, decision patterns
• Project Files: Test coverage, code quality, compilation status
• User Feedback: Direct input about goals, satisfaction, pain points
• Sub-agent Interactions: When sub-agents were used, gather their feedback

2. Quantitative Analysis

Calculate measurable metrics:

• Session scope (duration, tasks completed, files changed)
• Quality indicators (compilation rate, test coverage, standard compliance)
• Efficiency metrics (tool success rate, rework rate, completion rate)
• User experience data (satisfaction, friction points)

3. Qualitative Assessment

Identify patterns and insights:

• Successful approaches that led to good outcomes
• Problematic patterns that caused issues or delays
• Reusable solutions worth extracting for future use
• Context-specific learnings applicable to this project type

4. Report Generation

Create structured retrospective report using appropriate template:

• Quick Retrospective: Brief session wrap-ups (5-10 minutes)
• Comprehensive Retrospective: Detailed analysis for significant sessions
• Choose template based on session complexity and user needs

Working Process

Step 0: Quick Session Assessment

Before gathering data, determine the appropriate analysis depth:

1. Check session size:

   bashCopy

   # Count recent commits
   git log --oneline --since="1 hour ago" | wc -l
   
   # List session log files with metadata
   ${CLAUDE_PROJECT_DIR}/.claude/skills/extracting-session-data/scripts/list-sessions.sh --sort date | head -5

2. Suggest depth to user based on metrics:

   • Quick (<10 commits, <5MB logs): “5-10 min lightweight analysis”
   • Standard (10-25 commits, 5-20MB logs): “15-20 min balanced analysis”
   • Comprehensive (>25 commits, >20MB logs): “30+ min deep-dive analysis”

3. Let user override: “Based on [X commits, Y MB logs], I recommend a [MODE] retrospective (~Z minutes). Does this work for you, or would you prefer a different depth?”

4. Early exit clause: If user says “just a quick summary” or “high-level overview”, automatically use Quick mode regardless of session size.

Step 1: Establish Session Scope

1. Ask user to define session boundaries (time range or commit range)
2. Clarify session goals: “What were you trying to accomplish?”
3. Confirm retrospective depth from Step 0

Step 2: Gather Data

Execute data collection based on confirmed depth mode:

Depth-Specific Data Collection

Quick Mode:

• Git: git diff <start>..<end> --stat only (no full diffs)
• Logs: Extract statistics and errors only via extracting-session-data skill
• Files: Check compilation status only
• User: 2-3 targeted questions
• Skip: Sub-agent feedback, detailed file analysis

Standard Mode:

• Git: Full commit history + stats, selective diffs for key files
• Logs: Extract metadata, statistics, tool-usage, and errors via extracting-session-data skill
• Files: Quality metrics for changed files
• User: 5-7 questions covering main areas
• Include: Sub-agent feedback if applicable

Comprehensive Mode:

• Git: Everything (full logs, diffs, file analysis)
• Logs: Extract all data types via extracting-session-data skill, may read full logs if <500 lines
• Files: Deep analysis including tests, architecture compliance
• User: Extensive feedback (8-10 questions)
• Include: All sub-agent feedback, pattern extraction

Git Analysis

Use the analyzing-git-sessions skill to collect git data:

Quick Mode: Request “concise” output (stats only, no diffs) Standard Mode: Request “detailed” output for key files Comprehensive Mode: Request “code review” format for full analysis

Invoke skill with session timeframe:

The skill will return structured git metrics needed for retrospective analysis.

Log Processing (Size-Aware)

Use the extracting-session-data skill to access Claude Code native session logs efficiently.

1. List Available Sessions:

   bashCopy

   # List all sessions with metadata (size, lines, date, branch)
   ${CLAUDE_PROJECT_DIR}/.claude/skills/extracting-session-data/scripts/list-sessions.sh

2. Check Session Size:

   bashCopy

   # Get statistics for specific session
   ${CLAUDE_PROJECT_DIR}/.claude/skills/extracting-session-data/scripts/extract-data.sh \
       --type statistics --session SESSION_ID

3. Extract Data Based on Session Size and Mode:

   Quick Mode (or any session >2000 lines):

   bashCopy

   # Extract only statistics and errors
   extract-data.sh --type statistics --session SESSION_ID
   extract-data.sh --type errors --session SESSION_ID --limit 10

   Standard Mode (sessions 500-2000 lines):

   bashCopy

   # Extract metadata, statistics, tool usage, and errors
   extract-data.sh --type metadata --session SESSION_ID
   extract-data.sh --type statistics --session SESSION_ID
   extract-data.sh --type tool-usage --session SESSION_ID
   extract-data.sh --type errors --session SESSION_ID

   Comprehensive Mode (sessions <500 lines):

   bashCopy

   # Extract all available data
   extract-data.sh --type all --session SESSION_ID
   
   # Or read full log file if needed for detailed analysis
   # (Only for small sessions - check line count first!)

4. Multi-Session Analysis:

   bashCopy

   # Filter sessions by criteria
   filter-sessions.sh --since "7 days ago" --branch main
   
   # Extract data from all filtered sessions (omit --session flag)
   extract-data.sh --type statistics  # Runs on all sessions

5. Synthesize Extracted Data: After extraction, synthesize data into compact summary (max 200 lines) before continuing to analysis.

Path Calculation: The extracting-session-data skill handles all path calculations automatically. Session logs are stored in ~/.claude/projects/{project-identifier}/ where the identifier is derived from the working directory path.

Project Analysis

Examine changed files, tests, documentation (depth-appropriate)

User Feedback

Prompt for direct feedback on session experience (question count based on depth mode)

Sub-agent Feedback

If sub-agents were used, invoke them to gather their perspective (Standard/Comprehensive modes only)

Step 3: Analyze Data

Apply session-analytics.md framework:

• Calculate quantitative metrics
• Identify success and problem indicators
• Extract patterns (successful approaches and anti-patterns)
• Assess communication effectiveness and technical quality

Step 4: Generate Insights

Synthesize analysis into actionable insights:

• What went well and why (specific evidence)
• What caused problems and their root causes
• Opportunities for improvement (prioritized by impact)
• Patterns to replicate or avoid in future sessions

Step 5: Create Report

Use appropriate template from retrospective-templates.md:

• Structure findings clearly with evidence
• Include specific file:line references where relevant
• Prioritize recommendations by impact and feasibility
• Make all suggestions actionable and specific

Step 6: Gather User Validation

Present report and ask:

• Does this match your experience?
• Are there other pain points we missed?
• Which improvements would be most valuable to you?

Step 7: Suggest Configuration Improvements

If the retrospective identifies areas for improvement in Claude or Agent interactions:

1. Analyze whether improvements could be codified in configuration files:
   • CLAUDE.md: Core directives, workflow practices, communication patterns
   • SKILL.md files: Skill-specific instructions, working processes, anti-patterns
   • Agent definition files: Agent prompts, tool usage, coordination patterns
2. Draft specific, actionable suggestions for configuration updates:
   • Quote the current text that should be modified (if updating existing content)
   • Provide the proposed new or additional text
   • Explain the rationale based on retrospective findings
3. Present suggestions to the user:
   • “Based on this retrospective, I’ve identified potential improvements to [file]. Would you like me to implement these changes?”
   • Show the specific changes that would be made
4. If the user approves:
   • Apply the changes using the Edit tool
   • Confirm what was updated
5. If the user declines:
   • Document the suggestions in the retrospective report for future consideration

Step 8: Session Archive Information

After the retrospective report is created and validated:

1. Inform the user where session logs are stored:
   • “Session logs are permanently stored in ~/.claude/projects/{project-dir}/{session-id}.jsonl“
   • “These logs are managed by Claude Code and should not be deleted manually”
2. Explain that retrospective reports are saved separately in:
   • ${CLAUDE_PROJECT_DIR}/.claude/skills/retrospecting/reports/
3. Note that Claude Code manages session log retention automatically

Output Standards

Report Quality Requirements

• Evidence-Based: Every claim backed by specific examples
• Actionable: All recommendations include implementation guidance
• Specific: Avoid vague statements; use concrete examples
• Prioritized: Clear indication of high vs low impact items
• Balanced: Acknowledge successes while identifying improvements

File References

Use file:line_number format when referencing specific code locations.

Metrics Presentation

Present metrics in clear tables or lists with context for interpretation.

Recommendations Format

Each recommendation should include:

• What: Specific action to take
• Why: Root cause or rationale
• How: Implementation approach
• Impact: Expected benefit

Integration with Sub-agents

When sub-agents were used during the session:

Feedback Collection

Invoke each sub-agent that participated with prompts like:

• “What aspects of this session worked well for you?”
• “What instructions or context were unclear?”
• “What tools or capabilities did you need but lack?”
• “How could coordination with Claude be improved?”

Synthesis

Incorporate sub-agent feedback into retrospective:

• Identify coordination issues or handoff problems
• Note gaps in instruction clarity or context
• Recognize successful collaboration patterns
• Recommend improvements to sub-agent usage

Context Budget Management

Monitor context usage throughout retrospective to prevent overflow:

Budget Thresholds

• Skill instructions: ~6-8K tokens (this file + auto-loaded contexts)
• Small log file: 2-5K tokens per file
• Large log file: 10-50K+ tokens if read fully
• Git diffs: 5-20K tokens for large changes
• User conversation: Variable (2-10K tokens)

Adaptive Strategy Based on Remaining Budget

High Budget (>100K tokens remaining):

• Safe to use Comprehensive mode
• Read full logs if <2000 lines
• Include full git diffs
• Load detailed metrics from session-analytics.md if needed

Medium Budget (50-100K tokens remaining):

• Use Standard mode by default
• Summarize logs before reading (use bash extraction)
• Selective git diffs for key files only
• Skip extended context loading

Low Budget (<50K tokens remaining):

• Force Quick mode regardless of session size
• Bash-only log summarization (no full reads)
• Git stats only, no diffs
• Warn user: “Limited context available - providing focused analysis on key areas only”

Context Preservation Tactics

1. Extract and discard: Pull key metrics from large files, discard verbose source immediately
2. Synthesize early: Create compact summaries (max 200 lines) before continuing
3. Progressive refinement: Start high-level, drill down only where user indicates interest
4. Spot sampling: Read representative sections rather than entire files

Emergency Fallback

If approaching context limit during analysis:

1. Stop data collection immediately
2. Generate report from data gathered so far
3. Note in report: “Analysis limited by context constraints - [specific areas not covered]”
4. Offer to do targeted follow-up on specific aspects in new conversation

Anti-Patterns to Avoid

Don’t:

• Generate retrospectives without gathering actual data
• Make vague, non-actionable recommendations
• Focus only on negatives; acknowledge what worked well
• Ignore user’s stated priorities and goals
• Create overly long reports that bury key insights
• Analyze sessions without understanding the context and goals

Do:

• Ground analysis in concrete evidence from session data
• Provide specific, actionable recommendations with implementation guidance
• Balance positive recognition with improvement opportunities
• Align recommendations with user’s priorities
• Create concise reports that highlight key insights prominently
• Understand session context before analyzing effectiveness

Cross-Plugin Enrichment

When sibling Bitwarden plugins are installed, retrospectives gain specialist analysis:

Security-Aware Retrospectives (bitwarden-security-engineer plugin)

After collecting git diffs from the session:

• Scan for committed credentials → activate Skill(detecting-secrets) against the session’s git diffs to warn if secrets were inadvertently committed
• Assess security posture of new code → if the session introduced auth, crypto, or input-handling code, activate Skill(analyzing-code-security) to flag potential vulnerabilities in the retrospective report

Quality Classification (bitwarden-code-review plugin)

• Classify session changes by impact → activate Skill(classifying-review-findings) to categorize the session’s changes using the CRITICAL/IMPORTANT/DEBT/SUGGESTED framework, giving users a clear picture of what needs attention

These skills are optional. If unavailable, proceed with standard retrospective analysis.

Success Criteria

A good retrospective should:

1. Inform: User learns something new about their workflow
2. Guide: Clear next steps for improvement
3. Motivate: Recognition of successes encourages continued good practices
4. Focus: Prioritization helps user know where to invest effort
5. Enable: Provides frameworks/patterns user can apply to future sessions

Report Storage

Directory: ${CLAUDE_PROJECT_DIR}/.claude/skills/retrospecting/reports/

Filename format: YYYY-MM-DD-session-description-SESSION_ID.md

• Use ISO date format (YYYY-MM-DD) for chronological sorting
• Keep description brief (3-5 words, hyphen-separated)
• Include session ID from log files for traceability

Example path: ${CLAUDE_PROJECT_DIR}/.claude/skills/retrospecting/reports/2025-10-23-authentication-refactor-3be2bbaf.md