ulpi-io 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) |
| Validate | /validation |
/vibe, /post-mortem, /retro, /forge |
| Release | /release |
— |
Choosing the skill:
- Use
/implementfor single issue execution. Now defaults to TDD-first — writes failing tests before implementing. Skip with--no-tdd. - Use
/crankfor autonomous epic execution (loops waves via swarm until done). Auto-generates file-ownership maps to prevent worker conflicts. - Use
/swarmdirectly for parallel execution without beads (TaskList only). - Use
/discoveryfor the discovery phase only (brainstorm → search → research → plan → pre-mortem). - Use
/validationfor the validation phase only (vibe → post-mortem → retro → forge). - Use
/rpifor full lifecycle — delegates to/discovery→/crank→/validation. - Use
/ratchetto gate/record progress through RPI.
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 |
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) |
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 |
Full validation + knowledge lifecycle (council + extraction + activation + retirement) |
/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 |
/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 |
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 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
manualmode (default): MEMORY.md is auto-loaded by Claude Code; hook emits a pointer to on-demand retrieval (ao search,ao lookup) - In
leanmode: 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
/vibetrigger 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
/researchfor codebase exploration,/planfor decomposition - Agent explains
/pre-mortemfor 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 |