claude-reflect-system: Continual Learning & Self-improving skills system for Claude Code

by haddock-development · Codex Skill · ★ 379

Last updated: · Indexed by AgentSkillsHub · Auto-synced every 8h

Security audit verdict: SAFE · quality 70/100

None of the 42 rules matched — no credential harvesting, no data exfiltration, no curl-pipe-shell installer. Scanned against 42 published rules built on the SlowMist agent-security taxonomy, refreshed every 8 hours.

The quality score combines nine heuristic checks of the repo and its README: completeness, clarity, specificity, examples, structure, agent readiness, step-by-step content, instruction quality and security notes. It rates how well the project explains itself to an agent, not the code.

aiclaude-codeclaude-code-skillscodex-skillscontinuous-improvementllmpythonreflectionself-learningskill-system

Quick Facts

Stars379
Forks43
LanguagePython
CategoryCodex Skill
Quality Score70/100
Last Updated2026-01-17
Created2026-01-05
Platformsclaude-code, codex, python
Est. Tokens~445k

About claude-reflect-system

Claude Code Self-Learning Skills - Reflect System 🧠 "Correct once, never again" - AI that learns from your corrections and never repeats mistakes Keywords: Claude Code, AI Learning, Self-Improving AI, LLM Skills, Machine Learning, Continuous Learning, AI Memory, Developer Tools, Code Automation, Python AI 🎯 What is this? Reflect is a revolutionary self-learning AI system for Claude Code that...

Compatible Skills

These tools work well together with claude-reflect-system for enhanced workflows:

  • skills_collection — semantic(0.38)+complementary+same_lang+similar_pop+shared_platform (58%)
  • yunshu_skillshub — semantic(0.37)+complementary+same_lang+similar_pop+shared_platform (58%)
  • skills — semantic(0.37)+complementary+same_lang+similar_pop+shared_platform (58%)
  • cc-polymath — semantic(0.34)+complementary+same_lang+similar_pop+shared_platform (57%)

claude-reflect-system alternative? Top 6 similar tools

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How this security grade is produced

Grades come from a rule-based scan built on the SlowMist agent-security taxonomy: 42 published rules, covering credential harvesting, data exfiltration, curl | sh installers and more. It is a first-layer scan, not a manual audit — we say so rather than overstate it.

The scale of the problem is documented independently: Liu et al. (2026), in a study of 31,132 agent skills, report that 26.1% contain security vulnerabilities. Our own full-catalog census is published as a citable open dataset.

Sources & who's responsible:

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