self-learn
self-learn captures patterns, failures, and decisions from substantial sessions, scores them for generality and confidence, then proposes targeted framework updates—from project-specific steering rules to cross-cutting framework changes. It's the mechanism that lets your framework evolve from real usage, surfacing diffs for approval before any changes apply.
self-learn extracts lessons from completed sessions and proposes framework improvements based on patterns discovered.
AI-generated summary based on this skill's SKILL.md
Install
Pratiyush/llm-wiki/self-learn · repository language: Python
git clone https://github.com/Pratiyush/llm-wiki
cp -r llm-wiki/.claude/skills/self-learn ~/.claude/skills/self-learnFrequently asked questions
AI-generated answers based on this skill's SKILL.md and metadata
What does self-learn do with lessons from completed sessions?
self-learn extracts lessons and patterns from completed sessions to improve your framework. It analyzes what worked, what failed, and what decisions were made, then scores those learnings for generality and confidence. The skill surfaces diffs for your approval before applying any changes, ensuring your framework evolves deliberately from real usage rather than drifting uncontrolled.
How does self-learn turn session insights into framework rules?
self-learn captures reusable patterns from sessions and converts them into steering rules that can guide future work. It distills candidate lessons from your recent debugging loops and project work, then proposes targeted framework updates—ranging from project-specific rules to cross-cutting framework changes. You review and approve each promotion before it takes effect.
What did we learn today and how does self-learn surface it?
self-learn consolidates lessons learned from your day's work by extracting patterns, failures, and decisions from substantial sessions. It scores each learning for how broadly it applies and how confident the signal is, then proposes framework improvements backed by that evidence. The skill closes the learning loop by turning session insights into actionable framework updates you can version and log.
Can self-learn promote project-specific learnings to framework level?
Yes. self-learn scores and promotes project-specific learnings to framework level when they meet your quality gates. It identifies patterns that emerged from your recent project work and evaluates whether they're general enough to become steering rules for future sessions. Approved promotions get version-bumped and logged to your changelog, creating an audit trail of how your framework evolved.
How does self-learn handle framework version updates?
self-learn version-bumps your framework after learnings are approved and applied. It logs all changes to your changelog so you have a clear record of what evolved and why. This dogfooding meta-loop ensures your framework stays documented and traceable as it grows from real session experience.
SKILL.md
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self-learn
What this skill does
Closes the Dogfooding Meta-Loop from the Open Source Framework v4.1.
Every non-trivial session on a framework-driven project produces lessons: patterns that worked, patterns that failed, gotchas hit, decisions made. Most tools let those lessons evaporate. This skill captures them, runs a quality gate, and proposes framework updates.
It is the reason the framework evolves. Framework v4.0 → v4.1 was a self-learn pass that folded llmwiki's learnings back into the parent Open Source Framework.
When to invoke
- User says "learn from this session", "what did we learn", "extract lessons", "distill this"
- After a substantial feature ships (especially if it required multiple debugging loops)
- At the
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