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RPI Workflow
You have access to workflow skills for structured development.
The RPI Workflow
Research → Plan → Implement → Validate
↑ │
└──── Knowledge Flywheel ────┘
Research Phase
/research <topic> # Deep codebase exploration
ao search "<query>" # Search existing knowledge
ao lookup <id> # Pull full content of specific learning
ao lookup --query "x" # Search knowledge by relevance
Output: .agents/research/<topic>.md
Plan Phase
/pre-mortem <spec> # Simulate failures before implementing
/plan <goal> # Decompose into trackable issues
Output: Beads issues with dependencies
Implement Phase
/implement <issue> # Single issue execution
/crank <epic> # Autonomous epic loop (uses swarm for waves)
/swarm # Parallel execution (fresh context per agent)
Output: Code changes, tests, documentation
Validate Phase
/vibe [target] # Code validation (security, quality, architecture)
/post-mortem # Full validation + knowledge extraction (council + learnings + activation)
/retro # Quick-capture a single learning
Output: .agents/learnings/, .agents/patterns/
Release Phase
/release [version] # Full release: changelog + bump + commit + tag
/release --check # Readiness validation only (GO/NO-GO)
/release --dry-run # Preview without writing
Output: Updated CHANGELOG.md, version bumps, git tag, .agents/releases/
Phase-to-Skill Mapping
| Phase | Primary Skill | Supporting Skills |
|---|
| Discovery | /discovery | /brainstorm, /research, /plan, /pre-mortem |
| Implement | /crank | /implement (single issue), /swarm (parallel execution) |
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
/swarm directly for parallel execution without beads (TaskList only).
- 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 → → .
Available Skills
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 |
/research | Deep codebase exploration |
/council | Multi-model consensus review (validate, brainstorm, research) |
/vibe | Code validation (complexity + multi-model council) |
/rpi | Full RPI lifecycle orchestrator (research → plan → implement → validate) |
/implement |
Advanced Skills (when you need them)
| Skill | Purpose |
|---|
/athena | Active knowledge intelligence — Mine → Grow → Defrag cycle |
/brainstorm | Structured idea exploration before planning |
/discovery | Full discovery phase orchestrator (brainstorm → search → research → plan → pre-mortem) |
/plan | Epic decomposition into issues |
/pre-mortem | Failure simulation before implementing |
/post-mortem |
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 |
Knowledge Flywheel
Every /post-mortem feeds back to /research:
- Learnings extracted →
.agents/learnings/
- Patterns discovered →
.agents/patterns/
- Research enriched → Future sessions benefit
Issue Tracking
This workflow uses beads for git-native issue tracking:
bd ready # Unblocked issues
bd show <id> # Issue details
bd close <id> # Close issue
bd vc status # Inspect Dolt state if needed (JSONL auto-sync is automatic)
Examples
SessionStart Context Loading
Hook triggers: session-start.sh runs at session start
What happens:
- In
manual mode (default): MEMORY.md is auto-loaded by Claude Code; hook emits a pointer to on-demand retrieval (ao search, ao lookup)
- In
lean mode: hook extracts pending knowledge and injects prior learnings with a reduced token budget
- Hook injects this skill automatically into session context
- Agent loads RPI workflow overview, phase-to-skill mapping, trigger patterns
- User says "check my code" → agent recognizes
/vibe trigger naturally
Result: Agent knows the full skill catalog and workflow from session start. MEMORY.md is auto-loaded by default (manual mode). Set AGENTOPS_STARTUP_CONTEXT_MODE=lean for automatic knowledge injection alongside MEMORY.md.
Workflow Reference During Planning
User says: "How should I approach this feature?"
What happens:
- Agent references this skill's RPI workflow section
- Agent recommends Research → Plan → Implement → Validate phases
- Agent suggests
/research for codebase exploration, /plan for decomposition
- Agent explains
/pre-mortem for failure simulation before implementation
- 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 not configured or SessionStart disabled | Verify hooks/session-start.sh exists; check hook enable flags |
| 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 |
Weekly Installs
207
Repository
boshu2/agentops
GitHub Stars
205
First Seen
Feb 2, 2026
Security Audits
Gen Agent Trust HubPassSocketPassSnykPass
Installed on
codex205
gemini-cli204
github-copilot204
kimi-cli204
amp204
opencode204
