learning-loop

SkillAI & models

Structured self-improvement system for AI agents with confidence decay, cross-agent sharing, and anomaly detection. Use when: (1) After debugging sessions to capture lessons learned, (2) When receiving feedback or corrections from users, (3) Before risky actions to check relevant rules, (4) Weekly t

Use learning-loop in Claude, ChatGPT or Ahel Desktop

Free. Sign in, add learning-loop and connect your AI. About a minute.

Also: Claude Code · Cursor · Codex

Then ask your AI: use the learning-loop skill

Details

Instructions available. Your AI can read the instructions. Execution depends on the setup they require.

Add ahel to your AI once: Claude, ChatGPT, Cursor, Claude Code or Codex. Then ask it to use this.

learning-loopStart free

What this skill tells your AI

The instructions your AI receives, as published by leoyeai/openclaw-master-skills in skills/learning-loop/SKILL.md and read by ahel’s review.

What the learning loop is

stellar-build ships with a local learning loop: the more you use your skills, the better they get — without anything leaving your machine. It mirrors OpenJarvis's jarvis optimize skills / jarvis bench skills cycle, adapted for markdown skills.

Three moving parts:

  1. Capture — a skill use is a multi-turn span, so capture is decoupled from "skill became active". A PostToolUse:Skill hook marks which skill is resident; a Stop hook records each turn's real assistant output; and a SessionEnd hook closes the span with a summary, counting it as one activation. Everything lands in ~/.stellar-build/traces/<day>.jsonl. Fully local. Opt out with STELLAR_BUILD_NO_TRACE=1.
  2. Optimize (/optimize-skills) — compiles those traces into sharper skills: tightened triggers/instructions and few-shot examples mined from your own successful runs. Every edit is backed up and reversible.
  3. Bench (/bench-skills) — scores skills on held-out prompts so you can measure whether an optimization actually helped.
   use skills  ──▶  ~/.stellar-build/traces/*.jsonl
                          │
              /optimize-skills  (DSPy-style compile)
                          │
                          ▼
            sharper ~/.claude/skills/<skill>/SKILL.md   ◀── stellar-loop restore (undo)
                          │
                /bench-skills  (measure the lift)

What to do when invoked

  • Overview / "how does it work" → explain the three parts above, then point to the two action skills and the CLI.
  • "status" / "is tracing on" / "show my usage" → run the CLI and relay the output:
    • stellar-loop status — install + capture + hook state, trace/optimization counts
    • stellar-loop stats — per-skill usage from local traces
    • stellar-loop tail — most recent trace records The CLI is installed at ~/.stellar-build/bin/stellar-loop (add ~/.stellar-build/bin to PATH, or call it by full path).
  • "optimize" / "improve my skills" → hand off to the optimize-skills skill.
  • "benchmark" / "did it help" → hand off to the bench-skills skill.
  • "undo" / "restore" → stellar-loop restore <skill> reverts the last optimization for that skill from its backup.

Data & privacy

  • Everything lives under ~/.stellar-build/ (traces/, backups/, bench/, optimizations.jsonl). Override the root with STELLAR_BUILD_HOME.
  • Nothing is transmitted anywhere — no API calls, no telemetry. The "optimizer" is your own agent session reasoning over local files.
  • Result previews are truncated and examples are generalized before they ever land in a skill, so traces and learned blocks should not accumulate secrets. Wipe anytime with stellar-loop clear (--all also clears backups).

Quick reference

GoalDo this
See if it's workingstellar-loop status
See what you use moststellar-loop stats
Make skills sharper/optimize-skills (or stellar-loop optimize)
Measure the lift/bench-skills (or stellar-loop bench)
Undo an optimizationstellar-loop restore <skill>
Turn capture offexport STELLAR_BUILD_NO_TRACE=1
Delete all tracesstellar-loop clear

Signals

GitHub stars
2k
Forks
325
Last commit
Jul 2026
Advanced
Item type
skill
Key
learning-loop
Source
github.com/leoyeai/openclaw-master-skills