maestro-coordinate — for Claude Code maestro-coordinate, Maestro-Flow, community, for Claude Code, ide skills, detectTaskType, detectNextAction, chainMap, y, --yes, c, --continue

v1.0.0

このスキルについて

適した場面: Ideal for AI agents that need sequential cli-delegate coordinator. each chain step executes via maestro delegate "prompt" --to. ローカライズされた概要: Workflow orchestration CLI with MCP endpoint support and multi-agent dashboard <purpose Sequential CLI-delegate coordinator. This AI agent skill supports Claude Code, Cursor, and Windsurf workflows.

機能

Sequential CLI-delegate coordinator. Each chain step executes via maestro delegate "prompt" --to
with a template-driven prompt. After each step, gemini analysis evaluates output quality and
optimization hints for subsequent steps. All execution is background-async with hook callbacks.
Intent → Resolve Chain → Step 1 → Analysis → Step 2 → Analysis → … → Report
(chainMap) delegate gemini delegate gemini

# Core Topics

catlog22 catlog22
[88]
[12]
Updated: 4/18/2026

Killer-Skills Review

Decision support comes first. Repository text comes second.

Reference-Only Page Review Score: 10/11

This page remains useful for teams, but Killer-Skills treats it as reference material instead of a primary organic landing page.

Original recommendation layer Concrete use-case guidance Explicit limitations and caution Quality floor passed for review
Review Score
10/11
Quality Score
57
Canonical Locale
en
Detected Body Locale
en

適した場面: Ideal for AI agents that need sequential cli-delegate coordinator. each chain step executes via maestro delegate "prompt" --to. ローカライズされた概要: Workflow orchestration CLI with MCP endpoint support and multi-agent dashboard <purpose Sequential CLI-delegate coordinator. This AI agent skill supports Claude Code, Cursor, and Windsurf workflows.

このスキルを使用する理由

推奨ポイント: maestro-coordinate helps agents sequential cli-delegate coordinator. each chain step executes via maestro delegate "prompt" --to. Workflow orchestration CLI with MCP endpoint support and multi-agent dashboard

おすすめ

適した場面: Ideal for AI agents that need sequential cli-delegate coordinator. each chain step executes via maestro delegate "prompt" --to.

実現可能なユースケース for maestro-coordinate

ユースケース: Applying Sequential CLI-delegate coordinator. Each chain step executes via maestro delegate "prompt" --to
ユースケース: Applying with a template-driven prompt. After each step, gemini analysis evaluates output quality and
ユースケース: Applying optimization hints for subsequent steps. All execution is background-async with hook callbacks

! セキュリティと制限

  • 制約事項: Requires repository-specific context from the skill documentation
  • 制約事項: Works best when the underlying tools and dependencies are already configured

Why this page is reference-only

  • - Current locale does not satisfy the locale-governance contract.

Source Boundary

The section below is imported from the upstream repository and should be treated as secondary evidence. Use the Killer-Skills review above as the primary layer for fit, risk, and installation decisions.

After The Review

Decide The Next Action Before You Keep Reading Repository Material

Killer-Skills should not stop at opening repository instructions. It should help you decide whether to install this skill, when to cross-check against trusted collections, and when to move into workflow rollout.

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FAQ & Installation Steps

These questions and steps mirror the structured data on this page for better search understanding.

? Frequently Asked Questions

What is maestro-coordinate?

適した場面: Ideal for AI agents that need sequential cli-delegate coordinator. each chain step executes via maestro delegate "prompt" --to. ローカライズされた概要: Workflow orchestration CLI with MCP endpoint support and multi-agent dashboard <purpose Sequential CLI-delegate coordinator. This AI agent skill supports Claude Code, Cursor, and Windsurf workflows.

How do I install maestro-coordinate?

Run the command: npx killer-skills add catlog22/Maestro-Flow/maestro-coordinate. It works with Cursor, Windsurf, VS Code, Claude Code, and 19+ other IDEs.

What are the use cases for maestro-coordinate?

Key use cases include: ユースケース: Applying Sequential CLI-delegate coordinator. Each chain step executes via maestro delegate "prompt" --to, ユースケース: Applying with a template-driven prompt. After each step, gemini analysis evaluates output quality and, ユースケース: Applying optimization hints for subsequent steps. All execution is background-async with hook callbacks.

Which IDEs are compatible with maestro-coordinate?

This skill is compatible with Cursor, Windsurf, VS Code, Trae, Claude Code, OpenClaw, Aider, Codex, OpenCode, Goose, Cline, Roo Code, Kiro, Augment Code, Continue, GitHub Copilot, Sourcegraph Cody, and Amazon Q Developer. Use the Killer-Skills CLI for universal one-command installation.

Are there any limitations for maestro-coordinate?

制約事項: Requires repository-specific context from the skill documentation. 制約事項: Works best when the underlying tools and dependencies are already configured.

How To Install

  1. 1. Open your terminal

    Open the terminal or command line in your project directory.

  2. 2. Run the install command

    Run: npx killer-skills add catlog22/Maestro-Flow/maestro-coordinate. The CLI will automatically detect your IDE or AI agent and configure the skill.

  3. 3. Start using the skill

    The skill is now active. Your AI agent can use maestro-coordinate immediately in the current project.

! Reference-Only Mode

This page remains useful for installation and reference, but Killer-Skills no longer treats it as a primary indexable landing page. Read the review above before relying on the upstream repository instructions.

Upstream Repository Material

The section below is imported from the upstream repository and should be treated as secondary evidence. Use the Killer-Skills review above as the primary layer for fit, risk, and installation decisions.

Upstream Source

maestro-coordinate

Workflow orchestration CLI with MCP endpoint support and multi-agent dashboard <purpose Sequential CLI-delegate coordinator. This AI agent skill supports

SKILL.md
Readonly
Upstream Repository Material
The section below is imported from the upstream repository and should be treated as secondary evidence. Use the Killer-Skills review above as the primary layer for fit, risk, and installation decisions.
Supporting Evidence
<purpose> Sequential CLI-delegate coordinator. Each chain step executes via `maestro delegate "prompt" --to <tool> --mode write` with a template-driven prompt. After each step, gemini analysis evaluates output quality and generates optimization hints for subsequent steps. All execution is background-async with hook callbacks.
Intent  →  Resolve Chain  →  Step 1  →  Analysis  →  Step 2  →  Analysis  →  …  →  Report
              (chainMap)     delegate    gemini       delegate    gemini
                             callback   callback     callback    callback
</purpose>

<required_reading> @~/.maestro/workflows/maestro-coordinate.codex.md — authoritative detectTaskType, detectNextAction, chainMap (35+ intent patterns, 40+ chain types). Read before executing any step. </required_reading>

<deferred_reading>

<context> $ARGUMENTS — user intent text, or special flags.

Flags:

  • -y, --yes — Auto mode: skip all prompts, inject auto-confirm into delegates
  • -c, --continue — Resume previous session from last incomplete step
  • --dry-run — Show planned chain without executing
  • --chain <name> — Force specific chain (skips intent classification)

Session state: .workflow/.maestro-coordinate/{session-id}/state.json </context>

<invariants> 1. **STOP after each delegate call**: Background execution via `run_in_background: true`, wait for hook callback. 2. **State machine**: Advance via `current_step`, no sync loops for async operations. 3. **Template-driven**: All steps use `coordinate-step.txt`, no per-command prompt assembly. 4. **Context propagation**: Parse PHASE / spec session ID / scratch_dir / issue_id from each step output, feed to next step. 5. **Gemini analysis after each step**: Evaluate output quality, generate hints for next step, chain via `--resume`. 6. **Auto-confirm injection**: `{{AUTO_DIRECTIVE}}` in template prevents blocking during background execution. 7. **Resumable**: `-c` reads `state.json`, jumps to first pending step. 8. **Delegate tool**: `maestro delegate --to codex` for all execution steps; `--to gemini` only for post-step analysis.</invariants> <execution>

Step 1: Parse Arguments

javascript
1const args = $ARGUMENTS.trim(); 2const AUTO_YES = /\b(-y|--yes)\b/.test(args); 3const RESUME = /\b(-c|--continue)\b/.test(args); 4const DRY_RUN = /\b--dry-run\b/.test(args); 5const forcedChain = args.match(/--chain\s+(\S+)/)?.[1] || null; 6const intent = args 7 .replace(/\b(-y|--yes|-c|--continue|--dry-run)\b/g, '') 8 .replace(/--chain\s+\S+/g, '') 9 .trim();

If RESUME: Find latest state.json in .workflow/.maestro-coordinate/, load → jump to Step 6.

Step 2–4: Classify Intent → Confirm

  1. Read .workflow/state.json + .workflow/roadmap.md + current phase
  2. If --chain given → use directly; else classify via detectTaskType + chainMap
  3. If clarity < 2 and not AUTO_YES → clarify via AskUserQuestion (max 2 rounds)
  4. --dry-run: Display chain and exit
  5. User confirmation (skip if AUTO_YES): Execute / Execute from step N / Cancel

Step 5: Setup Session

javascript
1const sessionId = `coord-${new Date().toISOString().replace(/[-:T]/g, '').slice(0, 15)}`; 2const sessionDir = `.workflow/.maestro-coordinate/${sessionId}`; 3 4const state = { 5 session_id: sessionId, status: 'running', 6 created_at: new Date().toISOString(), 7 intent, task_type: taskType, chain_name: chainName, 8 auto_mode: AUTO_YES, phase: resolvedPhase, 9 current_step: 0, gemini_session_id: null, step_analyses: [], 10 steps: chain.map((s, i) => ({ 11 index: i, cmd: s.cmd, args: s.args || '', 12 status: 'pending', exec_id: null, analysis: null 13 })) 14}; 15Write(`${sessionDir}/state.json`, JSON.stringify(state, null, 2));

Step 6: Execute Step via maestro delegate

6a: Assemble args

javascript
1const AUTO_FLAG_MAP = { 2 'maestro-analyze': '-y', 'maestro-brainstorm': '-y', 'maestro-ui-design': '-y', 3 'maestro-plan': '--auto', 'maestro-spec-generate': '-y', 'quality-test': '--auto-fix', 4 'quality-retrospective': '--auto-yes', 5}; 6 7function assembleArgs(step) { 8 let a = (step.args || '') 9 .replace(/\{phase\}/g, context.current_phase || '') 10 .replace(/\{description\}/g, context.user_intent || '') 11 .replace(/\{issue_id\}/g, context.issue_id || '') 12 .replace(/\{spec_session_id\}/g, context.spec_session_id || '') 13 .replace(/\{scratch_dir\}/g, context.scratch_dir || ''); 14 if (state.auto_mode) { 15 const flag = AUTO_FLAG_MAP[step.cmd]; 16 if (flag && !a.includes(flag)) a = a ? `${a} ${flag}` : flag; 17 } 18 return a.trim(); 19}

6b: Build prompt from template + launch

Read ~/.maestro/templates/cli/prompts/coordinate-step.txt, fill placeholders. If previous step has analysis hints, inject as {{ANALYSIS_HINTS}}.

javascript
1const prompt = template 2 .replace('{{COMMAND}}', `/${step.cmd}`) 3 .replace('{{ARGS}}', assembledArgs) 4 .replace('{{STEP_N}}', `${state.current_step + 1}/${state.steps.length}`) 5 .replace('{{AUTO_DIRECTIVE}}', state.auto_mode ? 'Auto-confirm all prompts. No interactive questions.' : '') 6 .replace('{{CHAIN_NAME}}', state.chain_name) 7 .replace('{{ANALYSIS_HINTS}}', analysisHints); 8 9Bash({ 10 command: `maestro delegate ${escapeForShell(prompt)} --to codex --mode write`, 11 run_in_background: true, timeout: 600000 12}); 13// ■ STOP — wait for hook callback

Step 7: Post-Step Callback

javascript
1// Context propagation from output 2const phaseMatch = output.match(/PHASE:\s*(\d+)/m); 3if (phaseMatch) context.current_phase = phaseMatch[1]; 4const specMatch = output.match(/SPEC-[\w-]+/); 5if (specMatch) context.spec_session_id = specMatch[0]; 6const scratchMatch = output.match(/scratch_dir:\s*(.+)/m); 7if (scratchMatch) context.scratch_dir = scratchMatch[1].trim(); 8 9// Success/failure 10const failed = /^STATUS:\s*FAILURE/m.test(output); 11if (!failed) { step.status = 'completed'; } 12else if (state.auto_mode && !step.retried) { step.retried = true; /* re-execute Step 6 */ return; } 13else { step.status = 'skipped'; /* or AskUserQuestion: Retry / Skip / Abort */ } 14 15Write(`${sessionDir}/step-${stepIdx + 1}-output.txt`, output); 16// → Step 7b (gemini analysis) if completed + multi-step chain 17// → else advance current_step, loop to Step 6 or Step 8

Step 7b: Analyze Step Output (via gemini)

javascript
1let delegateCmd = `maestro delegate ${escapeForShell(analysisPrompt)} --to gemini --mode analysis --rule analysis-review-code-quality`; 2if (state.gemini_session_id) delegateCmd += ` --resume ${state.gemini_session_id}`; 3Bash({ command: delegateCmd, run_in_background: true, timeout: 300000 }); 4// ■ STOP — wait for hook callback

Post-analyze: store quality_score + issues + next_step_hints in state.step_analyses[], chain gemini sessions via --resume.

Step 8: Completion Report

============================================================
  MAESTRO-COORDINATE COMPLETE
============================================================
  Session: {session_id}
  Chain:   {chain_name} ({done}/{total})

  Steps:
    [✓] 1. maestro-plan — completed (quality: 85/100)
    [✓] 2. maestro-execute — completed (quality: 78/100)

  Avg Quality: {avg_score}/100
  Next: $maestro-coordinate --continue
============================================================
</execution>

<error_codes>

CodeSeverityDescriptionRecovery
E001errorNo intent and project not initializedSuggest $maestro-init
E002errorClarity too low after 2 roundsAsk to rephrase
E003errorStep failed + abortSuggest resume with -c
E004errorResume session not foundShow available sessions
</error_codes>

<success_criteria>

  • Intent classified and chain selected via detectTaskType + chainMap
  • Each step executed via maestro delegate with coordinate-step template
  • Auto-confirm injected, structured return parsed
  • Each completed step analyzed via maestro delegate --to gemini --mode analysis
  • Analysis hints injected into next step prompt via {{ANALYSIS_HINTS}}
  • Gemini sessions chained via --resume for accumulated context
  • Session state at .workflow/.maestro-coordinate/{session_id}/
  • Completion report with per-step status and quality scores </success_criteria>

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