Run a close-out retrospective on a client engagement — capture lessons, results, and the renewal/referral path. Use when asked to wrap up a client project, r...
编程
Retrospective Analysis
试用A project retrospective automation tool for friction identification, failure analysis, and improvement generation.
它能做什么
A project retrospective automation tool for friction identification, failure analysis, and improvement generation.
技能文档
Retrospective Analysis Skill
Overview
A project retrospective automation tool that helps teams identify process friction points, analyze failure causes, and generate actionable improvement candidates.
Key Features
- Structured Retrospectives: Track what went well, what was slow, what failed, and gate friction.
- Automatic Analysis: Compute issue counts, friction points, and severity (low/medium/high/critical).
- Improvement Generation: Derive prioritized improvement candidates from frictions and failures.
- Report Generation: Produce recommendations and action items from a retrospective.
- JSON Persistence: Save/load retrospectives and export reports to disk.
- Thread Safety: Concurrent adds and retrospective creation are safe.
Use Cases
- Post-change retrospective record keeping
- Process friction identification across gate checkpoints
- Continuous improvement candidate backlog generation
- Team retrospective reporting and archival
Installation
clawhub install retrospective-analysis
Usage
Basic Usage
from src import RetrospectiveAnalyzer
from src.models import ProjectInfo, GateFriction
analyzer = RetrospectiveAnalyzer()
project = ProjectInfo(name="Auth Refactor", team="Platform", duration="3 weeks", change_id="CH-42")
retro = analyzer.start_retrospective(project)
analyzer.add_what_went_well(retro.id, "fast design review")
analyzer.add_what_was_slow(retro.id, "manual test gate")
analyzer.add_what_failed(retro.id, "deploy rollback")
analyzer.add_gate_friction(
retro.id,
GateFriction(gate="testing-gate", issue="flaky tests", impact="blocked merge", suggested_change="stabilize suite"),
)
analysis = analyzer.analyze(retro.id)
print(analysis.severity, analysis.total_issues)
report = analyzer.generate_report(retro.id)
for item in report.action_items:
print(item)
Persistence
analyzer.save_to_file(retro.id, "retro.json")
loaded = analyzer.load_from_file("retro.json")
analyzer.export_report(retro.id, "report.json")
API Reference
RetrospectiveAnalyzer
start_retrospective(project_info) -> Retrospective— start a new retrospectiveadd_what_went_well(retro_id, item) -> None— record something that went welladd_what_was_slow(retro_id, item) -> None— record something slow/redundantadd_what_failed(retro_id, item) -> None— record a failure/rework causeadd_gate_friction(retro_id, friction) -> None— record gate frictionanalyze(retro_id) -> AnalysisResult— analyze the retrospectivegenerate_report(retro_id) -> RetrospectiveReport— generate a reportget_improvement_candidates(retro_id) -> List[ImprovementCandidate]— get candidatesarchive(retro_id) -> None— archive the retrospectivesave_to_file(retro_id, path)/load_from_file(path)/export_report(retro_id, path)— persistence
Models
RetroStatus: ACTIVE / ANALYZED / REPORTED / ARCHIVEDProjectInfo: name, team, duration, change_idGateFriction: gate, issue, impact, suggested_changeImprovementCandidate: target, recommendation, reason, priorityAnalysisResult: total_issues, friction_points, improvement_candidates, summary, severityRetrospective: id, project_info, status, what_went_well, what_was_slow, what_failed, gate_frictions, created_atRetrospectiveReport: retro_id, project_info, analysis, recommendations, action_items
Severity Logic
| Total Issues | Severity |
|---|---|
| 0 | low |
| 1–4 | medium |
| 5–9 | high |
| 10+ | critical |
Quality Metrics
- 81 comprehensive tests (unit + extended unit + integration + e2e)
- JSON serialization round-trips for all models
- Concurrent operation safety
- MIT License
Changelog
v1.0.0 (2026-07-03)
- Initial release
- Retrospective lifecycle management
- Friction identification and failure analysis
- Improvement candidate generation with priority
- Report generation and JSON persistence
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