using-agentopslisted

# AgentOps Operating Model AgentOps is the operational layer for coding agents. Publicly, it gives you four things: - **Bookkeeping** — captured learnings, findings, and reusable context - **Validation** — plan and code review before work ships - **Primitives** — single skills, hooks, and CLI surfaces - **Flows** — named compositions like `$research`, `$validation`, and `$rpi` Technically, AgentOps acts as a context compiler: raw session signal becomes reusable knowledge, compiled prevention, and better next work. ## Core Flow: RPI ``` Research → Plan → Implement → Validate ↑ │ └──── Knowledge Flywheel ────┘ ``` ### Research Phase ```bash $research <topic> # Deep codebase exploration ao search "<query>" # Search existing knowledge ao search "<query>" --cite retrieved # Record adoption when a search result is reused ao lookup <id> # Pull full content of specific learning ao lookup --query "x" # Search knowledge by relevance ``` **Output:** `.agents/research/<topic>.md` ### Plan Phase ```bash $pre-mortem <spec> # Simulate failures (error/rescue map, scope modes, prediction tracking) $plan <goal> # Decompose into trackable issues ``` **Output:** Beads issues with dependencies ### Implement Phase ```bash $implement <issue> # Single issue execution $crank <epic> # Autonomous epic loop (uses swarm for waves) $swarm # Parallel execution (fresh context per agent) ``` **Outpu