self-improvement
Captures learnings, errors, and corrections to enable continuous improvement across agent tasks.
- Logs failures, user corrections, knowledge gaps, and API errors to structured markdown files (
.learnings/ERRORS.md,LEARNINGS.md,FEATURE_REQUESTS.md) with consistent ID, priority, and metadata - Supports promotion of broadly applicable learnings to project memory files (
CLAUDE.md,AGENTS.md,.github/copilot-instructions.md) to prevent recurring mistakes - Includes recurring pattern detection via
Pattern-Keytracking and automatic recurrence counting for systemic issues - Provides hook integration for Claude Code and Codex to trigger learning evaluation after tasks, plus manual workflow for GitHub Copilot
- Enables skill extraction from high-value learnings when they meet criteria (recurring, verified, broadly applicable)
Self-Improvement Skill
Install
gh skill install pskoett/pskoett-skills self-improvement
For CI-only execution, use:
gh skill install pskoett/pskoett-skills self-improvement-ci
Fallback using the Agent Skills CLI:
npx skills add pskoett/pskoett-skills/skills/self-improvement
npx skills add pskoett/pskoett-skills/skills/self-improvement-ci
More from pskoett/pskoett-ai-skills
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CI-only self-improvement workflow using gh-aw (GitHub Agentic Workflows). Captures recurring failure patterns and quality signals from pull request checks, emits structured learning candidates, and proposes durable prevention rules without interactive prompts. Use when: you want automated learning capture in CI/headless pipelines.
460agent-teams-simplify-and-harden
Implementation + audit loop using parallel agent teams with structured simplify, harden, and document passes. Spawns implementation agents to do the work, then audit agents to find complexity, security gaps, and spec deviations, then loops until code compiles cleanly, all tests pass, and auditors find zero issues or the loop cap is reached. Use when: implementing features from a spec or plan, hardening existing code, fixing a batch of issues, or any multi-file task that benefits from a build-verify-fix cycle.
454simplify-and-harden
Post-completion self-review for coding agents that runs simplify, harden, and micro-documentation passes on non-trivial code changes. Use when: a coding task is complete in a general agent session and you want a bounded quality and security sweep before signaling done. For CI pipeline execution, use simplify-and-harden-ci.
426plan-interview
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415intent-framed-agent
Frames coding-agent work sessions with explicit intent capture and drift monitoring. Use when a session transitions from planning/Q&A to implementation for coding tasks, refactors, feature builds, bug fixes, or other multi-step execution where scope drift is a risk.
378dx-data-navigator
Query Developer Experience (DX) data via the DX Data MCP server PostgreSQL database. Use this skill when analyzing developer productivity metrics, team performance, PR/code review metrics, deployment frequency, incident data, AI tool adoption, survey responses, DORA metrics, or any engineering analytics. Triggers on questions about DX scores, team comparisons, cycle times, code quality, developer sentiment, AI coding assistant adoption, sprint velocity, or engineering KPIs.
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