using-agentops

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
/knowledge <query>     # Query existing knowledge

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           # Extract learnings after completion
/retro                 # Quick retrospective

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

Choosing the skill:

• Use /implement for single issue execution.
• Use /crank for autonomous epic execution (loops waves via swarm until done).
• Use /swarm directly for parallel execution without beads (TaskList only).
• Use /ratchet to gate/record progress through RPI.

Available Skills (43 user-facing)

Core Skills (start here)

Power Skills (when you're ready)

Expert Skills (advanced workflows)

Knowledge Flywheel

Every /post-mortem feeds back to /research:

1. Learnings extracted → .agents/learnings/
2. Patterns discovered → .agents/patterns/
3. 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 sync               # Sync with git

Examples

SessionStart Auto-Injection

Hook triggers: session-start.sh runs at session start

What happens:

1. Hook injects this skill automatically into session context
2. Agent loads RPI workflow overview, phase-to-skill mapping, trigger patterns
3. Agent understands available skills without user prompting
4. User says "check my code" → agent recognizes /vibe trigger naturally
5. Agent executes skill using workflow knowledge from this reference

Result: Agent knows the full skill catalog and workflow from session start, enabling natural language skill invocation.

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