using-agentops

Verified·Scanned 2/18/2026

This skill is a meta-reference for the RPI workflow and auto-injection of workflow triggers (e.g., session-start.sh) and includes a validation script scripts/validate.sh. It contains a fixed shell validation script but does not request secrets or explicit external network endpoints.

by boshu2·vad2fcc7·8.2 KB·77 installs
Scanned from main at ad2fcc7 · Transparency log ↗
$ vett add boshu2/agentops/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

PhasePrimary SkillSupporting Skills
Research/research/knowledge, /inject
Plan/plan/pre-mortem
Implement/implement/crank (epic loop), /swarm (parallel execution)
Validate/vibe/retro, /post-mortem
Release/release

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 (33 user-facing)

Core Skills (start here)

SkillPurpose
/researchDeep codebase exploration
/brainstormStructured idea exploration before planning
/planEpic decomposition into issues
/implementExecute single issue
/vibeCode validation (complexity + multi-model council)
/statusSingle-screen dashboard of current work and suggested next action

Power Skills (when you're ready)

SkillPurpose
/councilMulti-model consensus review (validate, brainstorm, research)
/pre-mortemFailure simulation before implementing
/post-mortemFull validation + knowledge extraction
/bug-huntRoot cause analysis
/releasePre-flight, changelog, version bumps, tag
/crankAutonomous epic loop (uses swarm for each wave)
/docDocumentation generation
/retroExtract learnings from completed work
/knowledgeQuery knowledge artifacts
/learnCapture knowledge manually into the flywheel

Expert Skills (advanced workflows)

SkillPurpose
/swarmFresh-context parallel execution (Ralph pattern)
/rpiFull RPI lifecycle orchestrator (research → plan → implement → validate)
/evolveGoal-driven fitness-scored improvement loop
/codex-teamParallel Codex agent execution
/complexityCode complexity analysis
/productInteractive PRODUCT.md generation
/handoffSession handoff for continuation
/inboxAgent mail monitoring
/recoverPost-compaction context recovery
/traceTrace design decisions through history
/provenanceTrace artifact lineage to sources
/beadsIssue tracking operations
/heal-skillDetect and fix skill hygiene issues
/converterConvert skills to Codex/Cursor formats
/updateReinstall all AgentOps skills from latest source

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

Natural Language Triggers

Skills auto-trigger from conversation:

Say ThisRuns
"I need to understand how auth works"/research
"Check my code for issues"/vibe
"Review my code"/vibe
"What could go wrong with this?"/pre-mortem
"Let's execute this epic"/crank
"Execute this epic"/crank
"Spawn agents to work in parallel"/swarm
"Run tasks in parallel"/swarm
"Debug this"/bug-hunt
"Remember this" / "I learned something"/learn
"How did we decide on this?"/trace
"Where did this learning come from?"/provenance
"Cut a release"/release
"Are we ready to release?"/release --check
"What am I working on?"/status
"Get started" / "How do I start?"/quickstart
"Define the product"/product
"Run the full lifecycle"/rpi
"Improve toward goals"/evolve
"Where was I?" / "Lost context"/recover
"End session" / "Pick up later"/handoff
"Update skills"/update

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

ProblemCauseSolution
Skill not auto-loadedHook not configured or SessionStart disabledVerify hooks/session-start.sh exists; check hook enable flags
Outdated skill catalogThis file not synced with actual skills/ directoryUpdate skill list in this file after adding/removing skills
Wrong skill suggestedNatural language trigger ambiguousUser explicitly calls skill with /skill-name syntax
Workflow unclearRPI phases not well-documented hereRead full workflow guide in README.md or docs/ARCHITECTURE.md