maestro

star 0

AI agent workflow with interview-driven planning and team-based execution. Use /design to start planning, /work to execute.

ReinaMacCredy By ReinaMacCredy schedule Updated 2/13/2026

name: maestro description: AI agent workflow with interview-driven planning and team-based execution. Use /design to start planning, /work to execute.

Maestro Workflow

"Spend tokens once on a good plan; reuse it many times."

Triggers

Trigger Action
/design <request> Start Prometheus interview mode (supports --quick)
/work Execute plan with Agent Teams (supports --resume)
/setup-check Validate Maestro prerequisites
/status Show current Maestro state
/review Post-execution plan verification
/styleguide Inject code style guides into project CLAUDE.md
/setup Scaffold project context (product, tech stack, guidelines)
/reset Clean stale Maestro state
/analyze <problem or topic> Deep read-only investigation with structured report
/note [--priority <P0-P3>] <text> Capture decisions, context, and constraints to persistent notepad
/learner [--from-session | --from-diff | <topic>] Extract hard-won principles as reusable learned skills
/security-review [<files> | --diff [range]] Delegated security analysis with severity ratings
/ultraqa [--tests|--build|--lint|--typecheck|--custom '<cmd>'] Iterative fix-and-verify loop (max 5 cycles)
/research <topic> [--depth shallow|deep] Multi-agent research with session persistence
/trace Show agent execution timeline and performance summary
/doctor Diagnose and fix Maestro installation issues
/psm Project Session Manager — isolated dev environments with git worktrees and tmux
/release Automated release workflow with version bump, tag, publish, and GitHub release
@tdd TDD implementation (kraken)
@spark Quick fixes
@oracle Strategic advisor (sonnet)
@explore Codebase search

Planning Flow

/design → prometheus (team lead) → detect libraries → fetch docs (Context7/WebSearch) → spawns explore/oracle → interview → leviathan (review) → plan file
  1. User triggers /design <description>
  2. Prometheus creates team if research needed 2.5. Loads prior wisdom from .maestro/wisdom/ (if any) 2.7. Detects external library/framework mentions and fetches docs via Context7 MCP (falls back to WebSearch/WebFetch)
  3. Spawns explore for codebase research (and web research when relevant)
  4. Spawns oracle for architectural decisions
  5. Conducts structured interview (one question at a time, multiple-choice options, incremental validation)
  6. Draft updates in .maestro/drafts/{topic}.md
  7. When clear, generate plan to .maestro/plans/{name}.md
  8. Spawn leviathan to validate plan quality
  9. Cleanup team

Quick mode (--quick) streamlines to: team → 1 explore → 1-2 questions → plan

Execution Flow

/work → orchestrator (team lead) → spawn workers in parallel → workers self-claim tasks
  1. User triggers /work
  2. Orchestrator loads plan from .maestro/plans/ 2.5. Validates plan structure and confirms with user before proceeding 2.7. Optionally creates a git worktree for isolated execution (prevents conflicts with concurrent sessions)
  3. Creates tasks via TaskCreate with dependencies
  4. Spawns 2-4 workers in parallel (kraken, spark)
  5. Assigns first round, workers self-claim remaining via TaskList
  6. Orchestrator verifies results, extracts wisdom to .maestro/wisdom/
  7. Suggests /review for post-execution verification

Use --resume to skip already-completed tasks.

State Directory

.maestro/
├── plans/     # Committed work plans
├── drafts/    # Interview drafts
├── wisdom/    # Accumulated learnings
└── context/   # Project context (product, tech stack, guidelines)

.worktrees/        # Git worktrees for isolated plan execution (project root)

Agents

Agent Purpose Model Team Lead? Has Team Tools?
prometheus Interview-driven planner. Detects libraries and fetches docs via Context7 MCP. Has web research tools (WebSearch, WebFetch) sonnet Yes Yes (full)
orchestrator Execution coordinator sonnet Yes Yes (full)
kraken TDD implementation sonnet No Yes (self-claim)
spark Quick fixes sonnet No Yes (self-claim)
oracle Strategic advisor sonnet No Yes (self-claim)
explore Codebase search haiku No Yes (self-claim)
leviathan Deep plan reviewer sonnet No Yes (self-claim)
wisdom-synthesizer Knowledge consolidation haiku No Yes (self-claim)
progress-reporter Status tracking haiku No Yes (self-claim)
security-reviewer Security analysis (read-only) sonnet No Yes (self-claim)

All agents have TaskList, TaskGet, TaskUpdate, SendMessage for team self-coordination. Only team leads have Task, TeamCreate, and TeamDelete for spawning.

Agent Teams Setup

Requires experimental feature flag in ~/.claude/settings.json:

{
  "env": {
    "CLAUDE_CODE_EXPERIMENTAL_AGENT_TEAMS": "1"
  }
}

Skill Interoperability

Maestro auto-detects installed skills and injects their guidance into worker prompts. This allows workers to follow project-specific conventions without manual configuration.

Discovery locations:

  • Project: .claude/skills/
  • Global: ~/.claude/skills/

Graceful degradation: If no skills are found, workflows proceed normally without injection.

See docs/SKILL-INTEROP.md for full details.

Quick Reference

  • Design: /design add user authentication
  • Execution: /work
  • Research: @explore, @oracle, /research
  • Implementation: @tdd, @spark
  • Analysis: /analyze, /security-review, /trace
  • Quality: /ultraqa, /review, /doctor
  • Knowledge: /note, /learner
  • Setup: /setup, /psm, /release
Install via CLI
npx skills add https://github.com/ReinaMacCredy/loveNovel --skill maestro
Repository Details
star Stars 0
call_split Forks 0
navigation Branch main
article Path SKILL.md
More from Creator
ReinaMacCredy
ReinaMacCredy Explore all skills →