Claude Flow
An orchestration layer for coordinating Claude-based agent swarms, shared memory, task graphs, and coding workflows.
Editorial research profile
What problem does this project address?
Coordinates specialist agents across planning, implementation, review, testing, and software delivery.
An orchestration layer for coordinating Claude-based agent swarms, shared memory, task graphs, and coding workflows.
Multi-agent core
How do the agents coordinate?
Claude Code
Claude Code is recorded as a coordination characteristic in this project's reviewed taxonomy.
Swarm
Multiple agents work in a decentralized or dynamically coordinated group.
Application fit
Where can it be useful?
Representative use cases
- Decompose a feature or repository task across specialist engineering roles.
- Run implementation and independent review or repair loops.
- Explore autonomous or semi-autonomous software delivery workflows.
Why it may be worth examining
- Provides a concrete end-to-end workflow that can be studied, adapted, or evaluated against a specific task.
- The project exposes 2 recorded coordination characteristics, making their combination easier to examine.
- Its self-hosting classification supports code inspection, internal experiments, and tighter data boundaries.
Engineering adoption guide
What should you verify before adoption?
Project-level trade-offs
- The included workflow and assumptions may be tightly coupled to its demonstration domain or data.
- The project was active at the latest editorial review, but release cadence and issue health should still be checked.
- Multi-agent results depend heavily on models, prompts, tools, data, and evaluation design; revalidate with representative tasks.
Technical and licensing facts
- Recorded as self-hostable; verify model, storage, and external service dependencies before adoption.
- The primary implementation language is TypeScript; assess extension and maintenance cost against your team's stack.
- The recorded license is MIT; confirm the repository's full license text and dependency licenses before formal use.
Recommended evaluation checklist
- 1 Require repository-grounded tests and inspect the produced patch, not only the final report.
- 2 Review sandboxing, command permissions, secret access, and rollback.
- 3 Measure completion rate, regression rate, token cost, and human review time together.
Traceable information
Research basis and freshness
Sources used for this profile
- Official GitHub repository and public metadata
- Official project website or documentation when available
- Repository-verifiable multi-agent mechanism and project scope
- This directory's normalized taxonomy, status, and adoption dimensions
- Last reviewed
- 2026-07-20
- Status
- Active
- GitHub Stars
- Not synced
- Archived
- No
Note: This page supports open-source discovery and engineering evaluation. It is not security, medical, legal, or financial advice. Capabilities and maintenance status may change after review; verify the official repository and documentation before adoption.
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