The master skill in PlanetScale's official pack: runs a full read-only best-practices assessment of a database or org, then produces one evidence-backed report.
Self-LearningSkill
Summary
A meta-skill that spots the moment your agent has just earned a hard-won golden path and writes it down as a reusable skill, so the next session starts already knowing the route.
Features
- Recognises a reusable golden path without being asked and harvests it on the spot
- Captures the procedure and the dead ends, not a one-off answer
- Triage routes each lesson to a skill, to memory, or to the bin
- Three-part promotion rule: a passing check, a named failure pattern, a ruled-out dead end
- Writes to SKILL.md, .cursor/rules/learned/, or AGENTS.md depending on the tool
- Installs across 70+ agents through the community `skills` CLI
Install This Skill
Add this skill to your favorite AI agent in a few steps.
Skill Content
Usage Instructions
Learn how to use this skill with different AI agents.
Example Usage
That took four attempts to get right — remember this so I don't have to re-explain the migration workflow next session.
Description
Every session where you debug something difficult, work out a deployment sequence, or rediscover where the credentials live, that knowledge evaporates when the session ends. The next session starts from zero and re-learns it. Self-Learning is a meta-skill that fixes the leak: it does not do the work, it captures how the work got done.
The loop
- Recognise the moment. A task that only worked after several attempts, a non-obvious command, a project fact you did not know up front, an operational workflow likely to recur — or you simply saying "remember this".
- Capture it unprompted. It acts on the cue immediately, picks the scope and name itself, and tells you afterwards. What gets captured is the procedure, plus a note on what did not work — because skipping a known dead end next session is often worth more than the win.
- Reuse. Next session the entry loads automatically, matched by skill description or because the instructions file is always read.
Two rules that keep it from becoming noise
Triage decides granularity. A multi-step reusable procedure becomes a skill or rule. A single fact or one-line correction goes to lightweight memory. A genuine one-off is skipped. Your config does not fill up with one-liners.
The promotion rule decides confidence. A skill is authoritative — the next session trusts it without re-deriving it — so a session is promoted to a skill only when all three hold: a passing check (a test passed, a clean exit, a green build; "seemed to work" does not count), a named failure pattern it avoids or diagnoses, and at least one concrete dead end ruled out. Miss any one and it stays a tentative memory note. This is what keeps confident-but-unverified guesses out of your standing instructions.
Where it writes
The loop is identical across tools; only the destination differs. Claude Code, Codex and other Agent Skills clients get a new skills/<name>/SKILL.md loaded by description matching. Cursor gets .cursor/rules/learned/<name>.mdc loaded by rule description or globs. Zed, Aider, Gemini CLI and anything else that reads standing instructions get an AGENTS.md entry.
Install with npx skills add kulaxyz/self-learning-skills (auto-detects your agents, -g for global), as a Claude Code plugin, or by copying the folder into place. MIT licensed.
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