--- name: using-agentops description: 'Explain AgentOps workflows.' skill_api_version: 1 user-invocable: false context: window: isolated intent: mode: none sections: exclude: [HISTORY, INTEL, TASK] intel_scope: none metadata: tier: meta dependencies: [] internal: true output_contract: "stdout: operating guide" --- # 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 # Deep codebase exploration ao search "" # Search existing knowledge ao search "" --cite retrieved # Record adoption when a search result is reused ao lookup # Pull full content of specific learning ao lookup --query "x" # Search knowledge by relevance ``` **Output:** `.agents/research/.md` ### Plan Phase ```bash /pre-mortem # Simulate failures (error/rescue map, scope modes, prediction tracking) /plan # Decompose into trackable issues ``` **Output:** Beads issues with dependencies ### Implement Phase ```bash /implement # Single issue execution /crank # Autonomous epic loop (uses swarm for waves) /swarm # Parallel execution (fresh context per agent) ``` **Output:** Code changes, tests, documentation ### Validate Phase ```bash /vibe [target] # Code validation (finding classification + suppression + domain checklists) /post-mortem # Validation + streak tracking + prediction accuracy + retro history /retro # Quick-capture a single learning ``` **Output:** `.agents/learnings/`, `.agents/patterns/` ## Phase-to-Skill Mapping | Phase | Primary Skill | Supporting Skills | |-------|---------------|-------------------| | **Discovery** | `/discovery` | `/brainstorm`, `/research`, `/plan`, `/pre-mortem` | | **Implement** | `/crank` | `/implement` (single issue), `/swarm` (parallel execution) | | **Validate** | `/validation` | `/vibe`, `/post-mortem`, `/retro`, `/forge` | **Choosing the skill:** - Use `/implement` for **single issue** execution. **Now defaults to TDD-first** — writes failing tests before implementing. Skip with `--no-tdd`. - Use `/crank` for **autonomous epic execution** (loops waves via swarm until done). Auto-generates file-ownership maps to prevent worker conflicts. - Use `/discovery` for the **discovery phase only** (brainstorm → search → research → plan → pre-mortem). - Use `/validation` for the **validation phase only** (vibe → post-mortem → retro → forge). - Use `/rpi` for **full lifecycle** — delegates to `/discovery` → `/crank` → `/validation`. - Use `/ratchet` to **gate/record progress** through RPI. ## Start Here (12 starters) These are the skills every user needs first. Everything else is available when you need it. | Skill | Purpose | |-------|---------| | `/quickstart` | Guided onboarding — run this first | | `/bootstrap` | One-command full AgentOps setup — fills gaps only | | `/research` | Deep codebase exploration | | `/council` | Multi-model consensus review + finding auto-extraction | | `/vibe` | Code validation (classification + suppression + domain checklists) | | `/rpi` | Full RPI lifecycle orchestrator (`/discovery` → `/crank` → `/validation`) | | `/implement` | Execute single issue | | `/retro --quick` | Quick-capture a single learning into the flywheel | | `/status` | Single-screen dashboard of current work and suggested next action | | `/goals` | Maintain GOALS.yaml fitness specification | | `/push` | Atomic test-commit-push workflow | | `/flywheel` | Knowledge flywheel health monitoring (σ×ρ > δ/100) | ## Advanced Skills (when you need them) | Skill | Purpose | |-------|---------| | `/compile` | Active knowledge intelligence — Mine → Grow → Defrag cycle | | `/llm-wiki` | External reading wiki proposal — raw sources to compiled wiki | | `/harvest` | Cross-rig knowledge consolidation — sweep, dedup, promote to global hub | | `/knowledge-activation` | Operationalize a mature `.agents` corpus into beliefs, playbooks, briefings, and gap surfaces | | `/brainstorm` | Structured idea exploration before planning | | `/discovery` | Full discovery phase orchestrator (brainstorm → search → research → plan → pre-mortem) | | `/plan` | Epic decomposition into issues | | `/design` | Product validation gate — goal alignment, persona fit, competitive differentiation | | `/pre-mortem` | Failure simulation (error/rescue, scope modes, temporal, predictions) | | `/post-mortem` | Validation + streak tracking + prediction accuracy + retro history | | `/bug-hunt` | Root cause analysis | | `/release` | Pre-flight, changelog, version bumps, tag | | `/crank` | Autonomous epic loop (uses swarm for each wave) | | `/swarm` | Fresh-context parallel execution (Ralph pattern) | | `/evolve` | Goal-driven fitness-scored improvement loop | | `/autodev` | PROGRAM.md autonomous development contract setup and validation | | `/dream` | Interactive Dream operator surface for setup, bedtime runs, and morning reports | | `/doc` | Documentation generation | | `/retro` | Quick-capture a learning (full retro → /post-mortem) | | `/validation` | Full validation phase orchestrator (vibe → post-mortem → retro → forge) | | `/ratchet` | Brownian Ratchet progress gates for RPI workflow | | `/forge` | Mine transcripts for knowledge — decisions, learnings, patterns | | `/readme` | Generate gold-standard README for any project | | `/security` | Continuous repository security scanning and release gating | | `/security-suite` | Binary and prompt-surface security suite — static analysis, dynamic tracing, offline redteam, policy gating | | `/test` | Test generation, coverage analysis, and TDD workflow | | `/red-team` | Persona-based adversarial validation — probe docs and skills from constrained user perspectives | | `/review` | Review incoming PRs, agent output, or diffs — SCORED checklist | | `/refactor` | Safe, verified refactoring with regression testing at each step | | `/deps` | Dependency audit, update, vulnerability scanning, and license compliance | | `/perf` | Performance profiling, benchmarking, regression detection, and optimization | | `/scaffold` | Project scaffolding, component generation, and boilerplate setup | | `/scenario` | Author and manage holdout scenarios for behavioral validation | ## Expert Skills (specialized workflows) | Skill | Purpose | |-------|---------| | `/grafana-platform-dashboard` | Build Grafana platform dashboards from templates/contracts | | `/codex-team` | Parallel Codex agent execution | | `/openai-docs` | Official OpenAI docs lookup with citations | | `/oss-docs` | OSS documentation scaffold and audit | | `/reverse-engineer-rpi` | Reverse-engineer a product into feature catalog and specs | | `/pr-research` | Upstream repository research before contribution | | `/pr-plan` | External contribution planning | | `/pr-implement` | Fork-based PR implementation | | `/pr-validate` | PR-specific validation and isolation checks | | `/pr-prep` | PR preparation and structured body generation | | `/pr-retro` | Learn from PR outcomes | | `/complexity` | Code complexity analysis | | `/product` | Interactive PRODUCT.md generation | | `/handoff` | Session handoff for continuation | | `/recover` | Post-compaction context recovery | | `/trace` | Trace design decisions through history | | `/provenance` | Trace artifact lineage to sources | | `/beads` | Issue tracking operations | | `/heal-skill` | Detect and fix skill hygiene issues | | `/converter` | Convert skills to Codex/Cursor formats | | `/update` | Reinstall all AgentOps skills from latest source | ## Knowledge Flywheel Every `/post-mortem` promotes learnings and patterns into `.agents/` so future `/research` starts with better context instead of zero. Inspect, lint, and triage the `.agents/` write surface contract via `ao agents inspect | lint | doctor` (`doctor` rolls up inspect + lint + orphan/stray-dir report; `--strict` fails on orphans). ## Runtime Modes AgentOps has four runtime modes. Do not assume hook automation exists everywhere. | Mode | When it applies | Start path | Closeout path | Guarantees | |------|-----------------|------------|---------------|------------| | `gc` | Gas City (`gc`) binary available and `city.toml` present | gc controller manages sessions; `ao rpi` auto-selects gc executor | gc event bus captures phase/gate/failure/metric events | Default when gc is available. Phase execution via gc sessions, events via gc event bus, agent health via gc health patrol | | `hook-capable` | Claude/OpenCode with lifecycle hooks installed (no gc) | Runtime hook or `ao inject` / `ao lookup` | Runtime hook or `ao forge transcript` + `ao flywheel close-loop` | Automatic startup/context injection and session-end maintenance when hooks are installed | | `codex-native-hooks` | Codex CLI v0.115.0+ with native hook support (March 2026) | Runtime hooks (same as hook-capable) | Runtime hooks (same as hook-capable) | Native lifecycle hooks — same guarantees as hook-capable mode | | `codex-hookless-fallback` | Codex Desktop / Codex CLI pre-v0.115.0 without hook surfaces | `ao codex start` | `ao codex stop` | Explicit startup context, citation tracking, transcript fallback, and close-loop metrics without hooks | | `manual` | No hooks and no Codex-native runtime detection | `ao inject` / `ao lookup` | `ao forge transcript` + `ao flywheel close-loop` | Works everywhere, but lifecycle actions are operator-driven | ## Issue Tracking This workflow uses beads for git-native issue tracking: ```bash bd ready # Unblocked issues bd show # Issue details bd close # Close issue bd vc status # Inspect Dolt state if needed (JSONL auto-sync is automatic) ``` ## Examples ### Startup Context Loading **Hook-capable runtimes** 1. `session-start.sh` (or equivalent) can run at session start. 2. In `manual` mode, MEMORY.md is auto-loaded and the hook points to on-demand retrieval (`ao search`, `ao lookup`). 3. In `lean` mode, the hook extracts pending knowledge and injects prior learnings with a reduced token budget. 4. This skill can be injected automatically into session context. **Codex (v0.115.0+: native hooks, older: hookless fallback)** 1. v0.115.0+: hooks fire automatically — same behavior as hook-capable runtimes above. 2. Pre-v0.115.0: run `ao codex start` explicitly, use `ao lookup` for citations, end with `ao codex stop`. **Result:** The agent gets the RPI workflow, prior context, and a citation path in all modes. ### Workflow Reference During Planning **User says:** "How should I approach this feature?" **What happens:** 1. Agent references this skill's RPI workflow section 2. Agent recommends Research → Plan → Implement → Validate phases 3. Agent suggests `/research` for codebase exploration, `/plan` for decomposition 4. Agent explains `/pre-mortem` for failure simulation before implementation 5. User follows recommended workflow with agent guidance **Result:** Agent provides structured workflow guidance based on this meta-skill, avoiding ad-hoc approaches. ## Troubleshooting | Problem | Cause | Solution | |---------|-------|----------| | Skill not auto-loaded | Hook runtime unavailable or startup path not run | Hook-capable runtimes: verify `hooks/session-start.sh` exists and is enabled. Codex: run `ao codex start` explicitly | | Outdated skill catalog | This file not synced with actual skills/ directory | Update skill list in this file after adding/removing skills | | Wrong skill suggested | Natural language trigger ambiguous | User explicitly calls skill with `/skill-name` syntax | | Workflow unclear | RPI phases not well-documented here | Read full workflow guide in README.md or docs/ARCHITECTURE.md |