Intent-driven workflow orchestration for multi-agent AI development — adaptive lifecycle engine, self-reinforcing knowledge graph, and visual dashboard for Claude Code, Gemini, Codex & more
- ✓Actively maintained (<30d)
- ✓Healthy fork ratio
- ✓Clear description
- !No standard license detected
git clone https://github.com/catlog22/maestro-flow && cp maestro-flow/*.md ~/.claude/agents/24 items in this repository
Read-only code exploration via Bash + CLI semantic dual-source analysis, with schema-validated structured output.
Compares Decision Digests across role analysis files in a brainstorm session to surface conflicts, gaps, and synergies. Read-only — returns structured text for the orchestrator to apply.
Autonomous executor for non-interactive impeccable commands. Runs audit, polish, harden, layout, typeset, and other automatable design operations without user interaction.
Generates multi-file role analysis for a brainstorm session — analysis.md index + per-feature files + optional findings under {output_dir}/{role}/.
Resident pipeline supervisor agent. Message-driven lifecycle for cross-checkpoint quality observation and health monitoring.
Unified worker agent for team pipelines. Executes role-specific logic loaded from a role_spec file within a built-in task lifecycle (discover, execute, report).
UI design token management and prototype generation — W3C Design Tokens Format, state-based components, WCAG AA validation, responsive layout templates.
Evaluates technical topics, proposals, or decisions across multiple dimensions with evidence-based scoring and recommendations.
Analyzes existing codebase from a specific focus area, spawned in parallel
Collaborative planner working within pre-allocated task ID ranges
Implements single tasks atomically with verification and commit discipline
External research agent using Exa MCP for API details, design patterns, and technology evaluation
Test coverage audit with gap detection and test stub generation
Researches implementation approach for a specific roadmap phase
Creates execution plans with task decomposition, waves, and dependencies
Domain research for project initialization, spawned with different focus angles
Merges multiple researcher outputs into a unified research summary
Multi-dimensional code review agent — analyzes changed files for a single review dimension
Creates project roadmap with phased milestones from research and requirements
Goal-backward verification across three layers (existence, substance, connection)
Subagents overview
What people ask about maestro-flow
What is catlog22/maestro-flow?
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catlog22/maestro-flow is subagents for the Claude AI ecosystem. Intent-driven workflow orchestration for multi-agent AI development — adaptive lifecycle engine, self-reinforcing knowledge graph, and visual dashboard for Claude Code, Gemini, Codex & more It has 476 GitHub stars and was last updated today.
How do I install maestro-flow?
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You can install maestro-flow by cloning the repository (https://github.com/catlog22/maestro-flow) or following the README instructions on GitHub. ClaudeWave also provides quick install blocks on this page.
Is catlog22/maestro-flow safe to use?
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Our security agent has analyzed catlog22/maestro-flow and assigned a Trust Score of 64/100 (tier: OK). See the full breakdown of passed checks and flags on this page.
Who maintains catlog22/maestro-flow?
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catlog22/maestro-flow is maintained by catlog22. The last recorded GitHub activity is from today, with 0 open issues.
Are there alternatives to maestro-flow?
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Yes. On ClaudeWave you can browse similar subagents at /categories/agents, sorted by popularity or recent activity.
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[](https://claudewave.com/repo/catlog22-maestro-flow)<a href="https://claudewave.com/repo/catlog22-maestro-flow"><img src="https://claudewave.com/api/badge/catlog22-maestro-flow" alt="Featured on ClaudeWave: catlog22/maestro-flow" width="320" height="64" /></a>More Subagents
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