maestro

by sharpdeveyeVerified

Workflow fluency for AI coding agents. 1 core skill · 25 commands · 7 domain references · memory layer · audit trail — works across Cursor, Claude Code, Gemini CLI, Copilot, and 6 more.

413
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63
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TypeScript
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8/23/2026
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⚠️ Third-Party Software Notice

This skill is third-party open-source software developed and hosted independently on GitHub. SkillTip is an informational directory and does not control or maintain the underlying repository. Any security checks displayed are automated and limited in scope. Review the source code before installing.

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Installation

Add to your Claude Code skills directory:

# Add to your Claude Code skills
git clone https://github.com/sharpdeveye/maestro

Getting Started

Guides for using skills like maestro.

Security Report

Verified

Last scanned: —

{
  "status": "PASSED",
  "issues": []
}

README.md

Maestro — Workflow fluency for AI coding agents

License: MIT Version npm VS Code Marketplace MCP Skills Commands 10 Providers

1 core skill · 25 commands · 7 domain references · memory layer · audit trail

Quick Start · Commands · What's New in v2 · Supported Tools · Contributing


What is Maestro?

AI agents are only as good as the workflows they operate in. Without guidance, you get the same predictable mistakes: unstructured prompts, context window overflows, tool sprawl, no error handling, and multi-agent systems for single-agent problems.

Maestro fights that pattern with:

  • A comprehensive agent-workflow skill with 7 domain-specific reference files (view source)
  • 25 commands to diagnose, evaluate, refine, streamline, fortify, capture, reflect, and more
  • Persistent memory — decisions, audit trail, and session history survive across sessions
  • Curated anti-patterns that explicitly tell the AI what NOT to do
  • A context gathering protocol (.maestro.md or .maestro/context.md) that ensures every command has project-specific awareness
  • Every command recommends a next step — no dead ends

Quick Start

npx skills add sharpdeveye/maestro

Then use any command in your AI coding agent:

/diagnose          # Find workflow issues
/streamline        # Remove unnecessary complexity
/fortify           # Add error handling
/refine            # Final quality pass

Most commands accept an optional argument to focus on a specific area:

/diagnose prompts
/fortify payment-workflow
/specialize legal

Combine Commands

/diagnose /calibrate /refine    # Full workflow: audit → standardize → polish
/evaluate /fortify /accelerate  # Review → harden → optimize

The Skill: agent-workflow

A comprehensive workflow design skill with 7 domain references (view skill):

ReferenceDomain
prompt-engineeringPrompt structure, few-shot, CoT, output schemas
context-managementWindow optimization, memory, state management
tool-orchestrationTool design, chaining, error handling, sandboxing
agent-architectureTopologies, handoffs, multi-agent patterns
feedback-loopsEvaluation, self-correction, regression detection
knowledge-systemsRAG, chunking, embeddings, source attribution
guardrails-safetyValidation, prompt injection, cost ceilings

25 Commands

Analysis — read-only, generate reports

CommandPurpose
/diagnoseSystematic workflow quality audit with scored dimensions
/evaluateHolistic review of workflow interaction quality
/reflect🆕 Analyze command history — which skills work, which fail

Fix & Improve — make targeted changes

CommandPurpose
/refineFinal quality pass on prompts, tools, and configuration
/streamlineRemove unnecessary complexity, flatten over-engineering
/calibrateAlign workflow components to project conventions
/fortifyAdd error handling, retries, fallbacks, circuit breakers
/zero-defectActivate maximum precision mode — zero mistakes allowed

Enhancement — add capabilities

CommandPurpose
/amplifyBoost capabilities with better tools and context
/composeDesign multi-agent orchestration and delegation
/enrichAdd knowledge sources, RAG, and grounding
/accelerateOptimize for speed, reduce latency and cost
/chainBuild effective tool chains and pipelines
/guardAdd safety constraints and security boundaries
/iterateSet up feedback loops and evaluation cycles
/temperReduce over-engineering, simplify overbuilt workflows
/turbochargePush past conventional limits — advanced techniques

Utility

CommandPurpose
/extract-patternExtract reusable patterns from working workflows
/adapt-workflowAdapt workflows for different providers/contexts
/onboard-agentSet up new agent configurations from scratch
/specializeMake workflows domain-specific (legal, medical, etc.)
/teach-maestroOne-time context gathering, saves to .maestro.md
/capture🆕 Save a session summary — persist what happened
/recap🆕 Quick summary of the last session

What's New in v2

Memory Layer

Maestro now remembers what happened across sessions:

.maestro/
├── context.md        ← project context (replaces .maestro.md)
├── decisions.jsonl    ← append-only decision log
├── audit.jsonl        ← every command invocation with cost + duration
└── sessions/
    └── 2026-04-26_fix_auth.md  ← session summaries
  • Backward compatible.maestro.md users change nothing
  • Opt-in.maestro/ is created only when you run /capture or use the extension
  • Git-friendly — session data is gitignored by default, context file is versioned

Audit Trail

Every command invocation is logged with duration, token usage, and estimated cost:

{"command":"fortify","duration_ms":8200,"cost_estimate_usd":0.019,"exit_status":"completed"}

Cost Estimation

Approximate cost tracking for Claude, GPT-4, Gemini, and more. Accuracy: ±20% — useful for trends, not invoicing.

/reflect — Effectiveness Scorecard

Analyze your command history to see which skills work, which fail, and where to improve:

╔══════════════════════════════════════════╗
║          MAESTRO EFFECTIVENESS           ║
╠══════════════════════════════════════════╣
║ Commands Run         23 (7 unique)       ║
║ Completion Rate      87%                 ║
║ Most Used            /fortify (6×)       ║
║ Total Cost           ~$0.47              ║
╚══════════════════════════════════════════╝

Anti-Patterns ("Workflow Slop")

The skill includes explicit guidance on what to avoid:

  • Don't dump entire codebases/databases into context
  • Don't use multi-agent systems for single-agent problems
  • Don't skip error handling (happy path only = production failure)
  • Don't retry the same prompt hoping for different results
  • Don't deploy without cost controls
  • Don't use vague tool descriptions that confuse the model
  • Don't ship without evaluation ("it seems to work" ≠ tested)

Supported Tools

ToolDirectory
Cursor.cursor/skills/
Claude Code.claude/skills/
Gemini CLI.gemini/skills/
Codex CLI.codex/skills/
VS Code Copilot / Antigravity.agents/skills/
Kiro.kiro/skills/
Trae.trae/skills/
Trae China.trae-cn/skills/
OpenCode.opencode/skills/
Pi.pi/skills/

MCP Server

Use Maestro as a live MCP server instead of static skill files. Any MCP-compatible client can connect — no file copying required.

Local (stdio)

Add to your MCP client config (Claude Desktop, Cursor, VS Code, etc.):

{
  "mcpServers": {
    "maestro": {
      "command": "npx",
      "args": ["-y", "maestro-workflow-mcp"]
    }
  }
}

Remote (HTTP)

Host Maestro as a public MCP endpoint:

npx maestro-workflow-mcp --http --port 3001

Clients connect to http://your-server:3001/mcp.

What the MCP Server Exposes

TypeCountDescription
Prompts25One per command — select from the prompt picker
Tools10list_commands, run_command, read_context, init, wave_start, wave_advance, wave_status, write_decision, read_decisions, read_audit
Resources8Core skill + 7 domain references

Manual Installation

If npx skills add doesn't work for your setup, copy the appropriate provider directory to your project root:

# Example for Claude Code
cp -r .claude/skills/ your-project/.claude/skills/

# Example for Cursor
cp -r .cursor/skills/ your-project/.cursor/skills/

Project Structure

maestro/
├── source/skills/           # 25 source skill definitions
│   ├── agent-workflow/      # Core skill + 7 reference files
│   │   └── reference/       # Domain-specific guidance
│   ├── diagnose/            # Analysis commands
│   ├── evaluate/
│   ├── reflect/             # 🆕 Effectiveness analysis
│   ├── refine/              # Fix & improve commands
│   ├── streamline/
│   ├── calibrate/
│   ├── fortify/
│   ├── zero-defect/
│   ├── amplify/             # Enhancement commands
│   ├── compose/
│   ├── enrich/
│   ├── accelerate/
│   ├── chain/
│   ├── guard/
│   ├── iterate/
│   ├── temper/
│   ├── turbocharge/
│   ├── extract-pattern/     # Utility commands
│   ├── adapt-workflow/
│   ├── onboard-agent/
│   ├── specialize/
│   ├── teach-maestro/
│   ├── capture/             # 🆕 Session persistence
│   └── recap/               # 🆕 Session recovery
├── packages/core/           # Shared utilities
│   └── src/
│       ├── context-utils.ts  # Section parser + matcher
│       ├── token-estimator.ts # Token estimation
│       ├── decisions.ts      # 🆕 Decision log
│       ├── audit.ts          # 🆕 Audit trail
│       └── cost-estimator.ts # 🆕 Cost estimation
├── maestro-extension/       # VS Code extension
├── mcp-server/              # MCP server package
│   ├── src/
│   │   ├── index.ts         # Entry point (stdio + HTTP)
│   │   ├── http.ts          # HTTP transport wrapper
│   │   ├── tools.ts         # 10 MCP tools
│   │   ├── prompts.ts       # 25 MCP prompts
│   │   └── resources.ts     # 8 MCP resources
│   └── package.json
├── scripts/
│   ├── build.js             # Multi-provider build pipeline
│   ├── bundle-skills.js     # MCP skill bundler
│   └── validate.js          # Skill validation checks
└── package.json

Contributing

Contributions welcome! Please ensure:

  • All content is original (no copying from other skill projects)
  • SKILL.md files have valid YAML frontmatter with description starting with "Use when..."
  • All code fences have a language specifier
  • Run npm run check to validate before submitting

License

MIT — see LICENSE.

Created by sharpdeveye

Frequently Asked Questions

What is maestro?

maestro is an open-source ai agents skill for AI coding assistants such as Claude Code, Codex CLI, and ChatGPT, built by sharpdeveye. Workflow fluency for AI coding agents. 1 core skill · 25 commands · 7 domain references · memory layer · audit trail — works across Cursor, Claude Code, Gemini CLI, Copilot, and 6 more. It has 413 GitHub stars.

Is maestro safe to use?

Yes. maestro passed SkillsLLM's automated security scan — a dependency vulnerability audit plus prompt-injection heuristics — with no high-severity issues. You can read the full report in the Security Report section on this page.

How do I install maestro?

Clone the repository with "git clone https://github.com/sharpdeveye/maestro" and add it to your Claude Code skills directory (see the Installation section above).

What programming language is maestro written in?

maestro is primarily written in TypeScript. It is open-source under sharpdeveye on GitHub, so you can review or fork the full source.

Are there alternatives to maestro?

Yes. SkillsLLM lists many other AI Agents skills you can browse and compare side by side. Open the AI Agents category from the badge at the top of this page, or use the Related Skills and comparison links further down to weigh maestro against similar tools.

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maestro — AI Skill for Claude Code | SkillTip