self-learning-skills
Memory sidecar for agent work: recall before tasks, record learnings after tasks, review recommendations, optional backport bundles.
Best use case
self-learning-skills is best used when you need a repeatable AI agent workflow instead of a one-off prompt.
Memory sidecar for agent work: recall before tasks, record learnings after tasks, review recommendations, optional backport bundles.
Teams using self-learning-skills should expect a more consistent output, faster repeated execution, less prompt rewriting.
When to use this skill
- You want a reusable workflow that can be run more than once with consistent structure.
When not to use this skill
- You only need a quick one-off answer and do not need a reusable workflow.
- You cannot install or maintain the underlying files, dependencies, or repository context.
Installation
Claude Code / Cursor / Codex
Manual Installation
- Download SKILL.md from GitHub
- Place it in
.claude/skills/self-learning-skills/SKILL.mdinside your project - Restart your AI agent — it will auto-discover the skill
How self-learning-skills Compares
| Feature / Agent | self-learning-skills | Standard Approach |
|---|---|---|
| Platform Support | Not specified | Limited / Varies |
| Context Awareness | High | Baseline |
| Installation Complexity | Unknown | N/A |
Frequently Asked Questions
What does this skill do?
Memory sidecar for agent work: recall before tasks, record learnings after tasks, review recommendations, optional backport bundles.
Where can I find the source code?
You can find the source code on GitHub using the link provided at the top of the page.
SKILL.md Source
# Self-learning sidecar Use this skill to **recall** prior shortcuts before you start work, and to **record** durable “aha” moments + recommendations after you finish. Critical rule: if no learnings exist (cold start), say so and proceed with standard tools — **do not invent memories**. ## 1) PRE-RUN: Recall (before starting work) **When to use:** Before any non-trivial task. **Action:** 1. Locate the project store: `<repo-root>/.agent-skills/self-learning/v1/users/<user>/` 2. Read `<project_store>/INDEX.md` (quick skim). 3. If you need targeted recall, run: - `python scripts/self_learning.py list --query "<keywords>"` - Optional filters: `--skill <name>`, `--tag skill:<name>` 4. Summarize **3–7** directly actionable bullets relevant to the current task (titles + IDs only; no long dumps). ## 2) POST-RUN: Record (after finishing work) **When to use:** You discovered something durable (schema, fix, command sequence, constraint, etc.). **Action:** 1. Capture **1–5** Aha Cards (durable, reusable, specific, non-sensitive). Format: `references/FORMAT.md`. - Ensure every Aha Card and Recommendation has `primary_skill` (use `unknown` if unsure). - Set `scope` to `project` (repo/run-specific) or `portable` (generally reusable; a backport candidate). - If you rediscovered the same learning, treat it as reinforcement (signal) rather than duplicating the full card. 2. Capture **1–5** concrete recommendations (what to change and where). 3. Persist: - `python scripts/self_learning.py record --json payload.json` (or stdin) **Output requirement:** print a short summary + top 3 items, then point to “view more” (`INDEX.md` / `review --format json`). Do not dump long JSON by default. ## 3) REVIEW: Dashboard / Next actions **When to use:** “What’s still open?”, “What’s stale?”, “What should we backport?”, “Most useful learnings this week?” **Action:** - `python scripts/self_learning.py review --days 7` - Full JSON: add `--format json` - Filters: `--skill <name>`, `--scope project|portable`, `--status proposed,accepted,in_progress`, `--query "<keywords>"` ## 4) MAINTENANCE / Governance - Repair store hygiene (append-only): `python scripts/self_learning.py repair --apply` - Update recommendation status/scope: `python scripts/self_learning.py rec-status --id rec_... --status done --scope portable --note "..."` - Optional backport bundle (explicit + auditable): `python scripts/self_learning.py export-backport --skill-path <skill-dir> --ids <aha_ids> [--make-diff] [--apply]` - Inspect backport markers in a skill: `python scripts/self_learning.py backport-inspect --skill-path <skill-dir>` ## Docs - Setup/background: `README.md` - Integration templates (no hooks): `references/INTEGRATION.md` - Rubric/format/portability: `references/RUBRIC.md`, `references/FORMAT.md`, `references/PORTABILITY.md`
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