/retrospective — Save Session Learnings
Capture learnings from the current session as a new skill in the Skills Registry.
Steps
Summarize key findings from the conversation:
- What was the goal?
- What approaches worked?
- What failed and why? (most valuable)
- What were the final parameters/configuration?
Create a new plugin using the template:
- Copy
Skills_Registry/templates/experiment-skill-template/to the appropriate category:plugins/general/— cross-project Python/dev skillsplugins/scientific/— scientific computing patternsplugins/trading/— Alpaca Trading system skillsplugins/kintsugi/— KINTSUGI-specific skills
- Rename
TEMPLATE_NAMEto a descriptive kebab-case name
- Copy
Fill in plugin.json (
.claude-plugin/plugin.json):{ "name": "your-skill-name", "version": "1.0.0", "description": "Specific trigger conditions: (1) scenario one, (2) scenario two. Verified on [environment].", "author": { "name": "smith6jt" }, "skills": "./skills", "repository": "https://github.com/smith-cop/Skills_Registry" }Fill in SKILL.md (
skills/<name>/SKILL.md) with YAML frontmatter and sections:- Experiment Overview — date, goal, environment, status
- Context — problem description
- Verified Workflow — step-by-step with exact commands/code
- Failed Attempts (Critical) — table: approach, result, lesson learned
- Final Parameters — copy-pasteable configurations
- Key Insights — bullet points of important learnings
Create a branch and open a PR to the Skills Registry:
cd Skills_Registry git checkout -b skill/your-skill-name git add plugins/category/your-skill-name/ git commit -m "Add your-skill-name skill: brief description" git push -u origin skill/your-skill-name gh pr create --title "Add skill: your-skill-name" --body "Description of what was learned"
Rules
- Every skill needs specific trigger conditions in the description (not vague advice)
- The "Failed Attempts" table is the most valuable section — always include it
- Include exact hyperparameters and configurations, not general guidance
- Document the environment (software versions, hardware) where verified
- Skills should be specific enough to be actionable but general enough to be reusable
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