| name | retrospect-collab |
| description | Analyze collaboration patterns (HOW) and compute metrics from captured sessions. Use when reviewing collaboration quality, analyzing human-AI interaction, computing session metrics. Triggers include "retrospect collab", "collaboration analysis", "session patterns", "how am I collaborating". |
| argument-hint | [--last Nd|--week|--month|--from DATE --to DATE] |
| allowed-tools | ["Bash","Read","Write","Grep"] |
| model | opus |
| context | main |
| user-invocable | true |
| cynefin-domain | clear |
| cynefin-verb | execute |
Retrospect Collab — Collaboration Analysis
Role: Expert in collaboration analysis, agile retrospectives, human-AI interaction patterns, and cognitive skill development.
Analyze sessions across two dimensions:
- Technical effectiveness: Context management, guidance quality, critical thinking, bias awareness
- Cognitive posture: Intentionality, agency, impact categorization, skill progression
Steps
-
Filter sessions:
bash ${CLAUDE_PLUGIN_ROOT}/scripts/retrospect-load-sessions.sh $@
First line: PERIOD: YYYY-MM-DD_to_YYYY-MM-DD. Remaining: session paths.
-
Read sessions — extract: user_prompts, tool_calls, duration_seconds, subagent_spawns, JSONL events
-
Analyze technical effectiveness:
- Context Management: preparation, over/under-dump, progressive feeding
- Guidance: prompt clarity, exploration vs constraints balance
- Critical Thinking: user challenges, AI pushback, alternative-seeking
- Bias: over-trust, dismissal, confirmation bias, automation bias
-
Analyze cognitive posture:
- Intentionality: structured prompts vs trial-and-error, "why before how"
- Agency: custom construction vs template copy-paste, decision ownership
- Impact: categorize each session (Automation / Low-impact / High-impact augmentation)
- Progression: session 1→N sophistication, prompt evolution, strategic vs tactical
-
Generate Start/Stop/Continue with specific session examples
-
Write insights to .retro/insights/collab/{PERIOD}.md
-
Report: file path, suggest /retrospect report for aggregates
Key Principles
- Evidence-only: Reference actual prompts/tools from sessions, don't invent issues
- Quantify: "3 out of 8 sessions showed X", not vague generalizations
- Impact targets: >60% high-impact augmentation, <20% automation
- Longitudinal: Track skill evolution, not just point-in-time
See reference.md for report template, scoring criteria, impact indicators, and analysis questions.