# cao-learning

> Claude/Codex skill by [@awslabs](https://omgskills.com/library/awslabs/index.md) · 1.5k stars · Updated 2026-10-28

Report 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.

Tags: agent-orchestration, ai-agents, ai-coding-assistant, antigravity, claude-code, codex, copilot-cli, cursor-cli, developer-tools, hermes, kimi-cli, kiro, mcp, model-context-protocol, multi-agent-systems, opencode, orchestration, python, tmux

## Install

```sh
git clone https://github.com/awslabs/cli-agent-orchestrator /tmp/cli-agent-orchestrator && ln -s /tmp/cli-agent-orchestrator/skills/cao-learning ~/.claude/skills/cao-learning
```

## From README

CAO Self-Learning CAO workflows can improve as they repeat: outcomes you report feed a retrospector agent that distills durable lessons into memory, and those lessons reach future sessions automatically. Your job depends on your role. All of this is opt-in infrastructure. If reportoutcome or a memory tool returns disabled: true, skip it silently and continue your task — learning is off for this run (often deliberately, e.g. a control run) and that is expected, not an error. A bare error with no disabled key is different: say so, don't skip it. That shape means the tool could not reach a verdict — cao-server is unreachable, or its settings.json could not be read — so learning may well be ON while nothing is being recorded. Mention it in your response and carry on with the task.

## Links

- HTML page: https://omgskills.com/library/awslabs/cli-agent-orchestrator/cao-learning/
- GitHub: https://github.com/awslabs/cli-agent-orchestrator
- Author: [@awslabs](https://omgskills.com/library/awslabs/index.md)

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