cao-learning
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.
Install
With your agent
Install OMGSkills skill "awslabs/cli-agent-orchestrator:cao-learning" into this agent's normal skills directory: call the OMGSkills MCP get_install_plan tool for your agent and run the script it returns (it installs only the pinned commit and verifies SKILL.md), and stop if MCP or the pin is unavailable. Do not overwrite or change existing skills without asking me.
Manual command
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-learningFrom 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.