cao-learning
FeaturedReport task outcomes and distill lessons so the team improves across runs — report_outcome after each unit of work, retrospector handoffs at natural boundaries, and applying injected lessons. Use in workflows that run repeatedly over similar work items. Requires memory.learning_enabled; degrade silently when the tools report disabled.
Install
Quality Score: 89/100
Skill Content
Details
- Author
- awslabs
- Repository
- awslabs/cli-agent-orchestrator
- Created
- 1 years ago
- Last Updated
- today
- Language
- Python
- License
- Apache-2.0
Similar Skills
Semantically similar based on skill content — not just same category
simplicio-learn
Persist what a run taught you so the next run is cheaper and more correct — mine high-signal lessons from the trajectory, dedup them, and write them back to AGENTS.md / memory so they're applied not re-derived. Use after a run or at session end, when the user says "remember this", "do a retrospective", "learn from this run", or when simplicio-tasks closes its self-audit. Keeps memory lean: durable, reusable bullets only — no transcripts, no one-offs.
learn
Run a session retrospective — extract lessons from what happened and persist them where they'll be found next time (CLAUDE.md, MEMORY.md, handoff.xml, skills). Invoke proactively after painful debug sessions, unexpected breakthroughs, end of significant work, or when a pattern recurs across sessions. Apply Kaizen — small improvements, compounded.
capture-learnings
Use in the Learn phase at the end of every task, before declaring done - dispatches the learner agent to record what was learned (conventions, pitfalls, reuse points, decisions) to the cross-session store and refresh the committed memory index, then closes the phase. Runs inline on the main thread (it owns the state write).