Skills, Agents & Hooks
Skills are where ido4’s project intelligence lives. Each skill composes multiple MCP tools into an intelligent workflow — assembling context, spotting patterns, and delivering actionable insights. Every claim is backed by real data from the audit trail and analytics. Nothing is guessed.
Together with 4 specialized agents and 2 automation hooks, the plugin layer turns raw governance data into the project understanding that makes AI-hybrid development work.
Complete Inventory
Project Intelligence (any methodology)
| Component | Type | What it does |
|---|---|---|
/ido4dev:standup | Skill | Morning briefing — what’s blocked, what’s at risk, the single highest-leverage action for the day |
/ido4dev:board | Skill | Flow intelligence — cascade blockers, false statuses, review bottlenecks, epic cohesion |
/ido4dev:health | Skill | GREEN / YELLOW / RED verdict across flow, governance, and team dimensions |
/ido4dev:compliance | Skill | Quantitative score (0-100) + structural principle audit + improvement recommendations |
Planning (methodology-specific)
| Component | Type | Methodology | What it produces |
|---|---|---|---|
/ido4dev:plan-wave | Skill | Hydro | Valid-by-construction wave plan respecting all 5 governance principles |
/ido4dev:plan-sprint | Skill | Scrum | Sprint backlog with Definition of Ready gates per work item type |
/ido4dev:plan-cycle | Skill | Shape Up | Betting table with appetite check and circuit breaker risk assessment |
Retrospectives (methodology-specific)
| Component | Type | Methodology | What it analyzes |
|---|---|---|---|
/ido4dev:retro-wave | Skill | Hydro | Velocity, epic integrity, blocking time — real data from audit trail |
/ido4dev:retro-sprint | Skill | Scrum | Sprint goal achievement, DoR effectiveness, carry-over trends |
/ido4dev:retro-cycle | Skill | Shape Up | Bet outcomes, appetite accuracy, circuit breaker decisions |
Specification & Decomposition
| Component | Type | What it does |
|---|---|---|
/ido4dev:decompose | Skill | Transforms a strategic spec into a technical spec with implementation tasks grounded in your codebase |
/ido4dev:spec-validate | Skill | Catches format and quality issues before ingestion |
/ido4dev:spec-quality | Skill | Quality standards for task descriptions, success conditions, effort/risk calibration |
| Code Analyzer | Agent | Maps strategic capabilities to codebase modules, discovers patterns. Uses Read/Glob/Grep. Model: Opus |
| Technical Spec Writer | Agent | Decomposes capabilities into right-sized tasks with code-grounded metadata. Model: Opus |
| Spec Reviewer | Agent | Independent two-stage review — format compliance + quality assessment. Model: Sonnet |
Sandbox & Onboarding
| Component | Type | What it does |
|---|---|---|
/ido4dev:onboard | Skill | Zero-friction first touch — auto-clones demo codebase, creates sandbox, guided governance discovery |
/ido4dev:guided-demo | Skill | Four-act governance walkthrough — project overview, violation discovery, enforcement, full pipeline |
/ido4dev:sandbox-explore | Skill | Interactive exploration — 13 structured paths across governance, enforcement, coordination |
/ido4dev:sandbox | Skill | Sandbox lifecycle management — create, reset, destroy |
/ido4dev:pilot-test | Skill | End-to-end verification that the full governance stack works |
Persistent Intelligence
| Component | Type | What it does |
|---|---|---|
| PM Agent | Agent | Persistent project intelligence brain. Maintains velocity baselines, compliance trends, blocker patterns across sessions. Grounds every recommendation in real data. Model: Sonnet |
| Post-transition | Hook | Fires after state changes. Checks: did this unblock downstream? Create new blocker? Reach milestone? |
| Post-wave-assignment | Hook | Fires after wave assignment. Checks epic integrity and dependency violations. |
Totals: 21 skills + 4 agents + 2 hooks
How Skills Work
Skills are SKILL.md files — structured prompts that tell the AI what to do:
- Call specific MCP tools to gather data
- Analyze results for patterns and anomalies
- Present findings in a consistent format
- Recommend actions grounded in evidence
Composite Data Tools (the performance layer)
Skills don’t make 10+ individual tool calls. They call composite aggregators that assemble everything in one request:
| Aggregator | What it assembles | Used by |
|---|---|---|
get_standup_data | Container status, tasks, PR reviews, blocker analyses, audit trail (24h), analytics, agents, compliance | /ido4dev:standup |
get_board_data | Container status, tasks with PR + lock annotations, analytics, agents | /ido4dev:board |
get_compliance_data | Compliance score, audit trail, analytics, tasks, blocker analyses, integrity checks | /ido4dev:compliance |
get_health_data | Container status, compliance, analytics, agents | /ido4dev:health |
get_task_execution_data | Task spec, upstream context (what was built), sibling patterns, downstream consumers, epic progress, risk flags | Task execution |
These are MCP tools defined in @ido4/mcp — available to any MCP client, not just skills.
Skills vs Prompts vs Agents
| Skills | Prompts | Agents | |
|---|---|---|---|
| Platform | Claude Code (with plugin) | Any MCP client | Claude Code (with plugin) |
| Invocation | /ido4dev:standup | MCP prompt protocol | Invoked by skills |
| Features | Memory, file access, hooks | Tool calls + reasoning | Specialized instructions, model selection |
| Count | 21 | 8 | 4 |
| Purpose | Intelligent workflows | Portable guidance | Focused AI roles |
Cross-Skill Intelligence Loop
Skills share knowledge through Claude Code’s memory, creating a compounding intelligence loop:
- Retro analyzes what happened → persists findings (velocity baselines, blocking patterns, process gaps)
- Standup reads retro findings → contextualizes today’s risks against historical patterns
- Plan reads velocity baselines → grounds capacity estimates in real throughput, not guesses
- Compliance tracks score trends → detects governance degradation across assessments
- PM Agent bridges everything → persistent memory across sessions, coordination across agents
Every skill invocation makes the next one smarter. This is institutional memory in action.
PM Agent
The PM agent is a persistent project intelligence brain — not a chatbot, but a data-grounded advisor:
- Maintains velocity baselines, compliance trends, and blocker patterns across sessions
- Grounds every recommendation in real data — audit trail, analytics, compliance score
- Coordinates multiple agents — detects lock contention, idle agents, work imbalance
- Cannot override the BRE — translates validation failures into actionable guidance
See PM Agent for details.