Session Retrospective
Analyze conversation corrections to detect skill gaps and auto-improve the skills library. Use after any session with user corrections, rework, or retrospective requests.
Best use case
Session Retrospective is best used when you need a repeatable AI agent workflow instead of a one-off prompt.
Analyze conversation corrections to detect skill gaps and auto-improve the skills library. Use after any session with user corrections, rework, or retrospective requests.
Teams using Session Retrospective should expect a more consistent output, faster repeated execution, less prompt rewriting.
When to use this skill
- You want a reusable workflow that can be run more than once with consistent structure.
When not to use this skill
- You only need a quick one-off answer and do not need a reusable workflow.
- You cannot install or maintain the underlying files, dependencies, or repository context.
Installation
Claude Code / Cursor / Codex
Manual Installation
- Download SKILL.md from GitHub
- Place it in
.claude/skills/session-retrospective/SKILL.mdinside your project - Restart your AI agent — it will auto-discover the skill
How Session Retrospective Compares
| Feature / Agent | Session Retrospective | Standard Approach |
|---|---|---|
| Platform Support | Not specified | Limited / Varies |
| Context Awareness | High | Baseline |
| Installation Complexity | Unknown | N/A |
Frequently Asked Questions
What does this skill do?
Analyze conversation corrections to detect skill gaps and auto-improve the skills library. Use after any session with user corrections, rework, or retrospective requests.
Where can I find the source code?
You can find the source code on GitHub using the link provided at the top of the page.
SKILL.md Source
# Session Retrospective
## **Priority: P1 (OPERATIONAL)**
## Structure
```text
common/session-retrospective/
├── SKILL.md # Protocol (this file)
└── references/
└── methodology.md # Signal tables, taxonomy, report template
```
## Protocol
1. **Extract** — Scan for correction signals (loops, rejections, shape mismatches, lint rework)
2. **Classify** — Root cause: Skill Missing | Incomplete | Example Contradicts Rule | Workflow Gap
3. **Propose** — One fix per root cause: update skill, update reference, new skill, or new workflow
4. **Implement** — Apply to all agent dirs. Keep SKILL.md ≤70 lines. Update `AGENTS.md`
5. **Report** — Output correction count, skills changed, estimated rounds saved
## Guidelines
- **Cite specifics**: Reference concrete conversation moment per proposal
- **Extend first**: Search `AGENTS.md` before creating — update existing skills
- **One fix per loop**: One correction → one targeted skill change
- **Sync all agents**: Apply to every agent skill dir listed in `.skillsrc` `agents` field
- **Follow skill-creator**: New skills comply with `common/skill-creator` standards
## Anti-Patterns
- **No Vague Proposals**: Cite exact gap + fix, not "make X better"
- **No Duplicate Skills**: Search AGENTS.md index first
- **No Oversized Patches**: Extract to `references/` per skill-creator standard
## References
Signal tables, root cause taxonomy, report template, real-world example:
[references/methodology.md](references/methodology.md)Related Skills
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