ReddRadar
Agent skill
using-agentops
Meta skill explaining the AgentOps workflow. Auto-injected on session start. Covers RPI workflow, Knowledge Flywheel, and skill catalog.
Stars
163
Forks
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Install this agent skill to your Project
npx add-skill https://github.com/majiayu000/claude-skill-registry/tree/main/skills/data/using-agentops
SKILL.md
AgentOps Workflow
You have access to the AgentOps skill set for structured development workflows.
The RPI Workflow
Research → Plan → Implement → Validate
↑ │
└──── Knowledge Flywheel ────┘
Research Phase
bash
/research <topic> # Deep codebase exploration
/knowledge <query> # Query existing knowledge
Output: .agents/research/<topic>.md
Plan Phase
bash
/pre-mortem <spec> # Simulate failures before implementing
/plan <goal> # Decompose into trackable issues
Output: Beads issues with dependencies
Implement Phase
bash
/implement <issue> # Single issue execution
/crank <epic> # Autonomous single-agent execution
/swarm [--agents N] # Parallel multi-agent execution
Output: Code changes, tests, documentation
Validate Phase
bash
/vibe [target] # Code validation (security, quality, architecture)
/post-mortem # Extract learnings after completion
/retro # Quick retrospective
Output: .agents/learnings/, .agents/patterns/
Phase-to-Skill Mapping
| Phase | Primary Skill | Supporting Skills |
|---|---|---|
| Research | /research |
/knowledge, /inject |
| Plan | /plan |
/pre-mortem |
| Implement | /implement |
/crank (single-agent), /swarm (multi-agent) |
| Validate | /vibe |
/retro, /post-mortem |
Available Skills
| Skill | Purpose |
|---|---|
/research |
Deep codebase exploration |
/pre-mortem |
Failure simulation before implementing |
/plan |
Epic decomposition into issues |
/implement |
Execute single issue |
/crank |
Autonomous single-agent execution |
/swarm |
Parallel multi-agent execution (Agent Farm) |
/vibe |
Code validation |
/retro |
Extract learnings |
/post-mortem |
Full validation + knowledge extraction |
/beads |
Issue tracking operations |
/bug-hunt |
Root cause analysis |
/knowledge |
Query knowledge artifacts |
/complexity |
Code complexity analysis |
/doc |
Documentation generation |
Knowledge Flywheel
Every /post-mortem feeds back to /research:
- Learnings extracted →
.agents/learnings/ - Patterns discovered →
.agents/patterns/ - Research enriched → Future sessions benefit
Natural Language Triggers
Skills auto-trigger from conversation:
| Say This | Runs |
|---|---|
| "I need to understand how auth works" | /research |
| "Check my code for issues" | /vibe |
| "What could go wrong with this?" | /pre-mortem |
| "Let's execute this epic" | /crank |
| "Spawn agents to work in parallel" | /swarm |
Issue Tracking
AgentOps uses beads for git-native issue tracking:
bash
bd ready # Unblocked issues
bd show <id> # Issue details
bd close <id> # Close issue
bd sync # Sync with git
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