| FMRS | 63 / 100 · C | 79 / 100 · B |
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| Reliability | 10 / 20 | 12 / 20 |
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| Security and permissions | 12 / 20 | 18 / 20 |
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| Maintenance | 16 / 20 | 16 / 20 |
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| Documentation | 15 / 20 | 18 / 20 |
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| Setup experience | 10 / 20 | 15 / 20 |
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| Best for | - Developers and creators who want to use AI multi-agent collaboration for complex tasks (like business planning, technical solutions, content creation).
- Teams that prefer no-code YAML workflows over writing Python code.
- Users who want to leverage existing AI subscriptions (like Claude, Gemini, Copilot) to reduce costs.
| - Engineering teams scaling AI coding agents while controlling spend
- Platform teams that need auditable, rollback-aware agent execution records
- Organizations using multiple agents (Claude, Codex, Gemini) under one governed flow
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| Not for | - Deep customization scenarios requiring fine-grained control over each agent's internal logic.
- Enterprises with strict data privacy requirements, as some API calls require network access.
- Scenarios relying on small local models (e.g., 8B level) for high-quality outputs, as multi-role handoffs may amplify drift.
| - Developers who just want a simple code-completion helper without run governance
- Teams unwilling to accept local JSONL run records with HMAC signing
- Environments without a supported adapter (Claude/Codex/Gemini CLIs, direct provider, or verifier-only)
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| Required permissions | - When executing workflows, it calls configured LLM APIs or local CLIs, requiring network access and API permissions.
- It can read/write local file system (e.g., read input files, save outputs to `ao-output/` directory).
- The MCP server itself only provides stdio communication and does not actively access external systems.
| - Read/write access to the configured repo root (writable scope restrictable via --allow-path/--deny-path)
- Ability to invoke the chosen agent CLI (Claude/Codex/Gemini, etc.) and its underlying model account
- Local disk writes for run records, receipts, and share outputs (share/run-receipt., etc.)
- Execution of user-configured verifier commands (e.g. npm test)
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| Risks and side effects | - LLM outputs may be inaccurate or hallucinated; acceptance criteria can mitigate but not fully avoid.
- When using third-party APIs, ensure API keys are securely stored to prevent leakage.
- Workflows with human approval nodes require user intervention, otherwise the flow pauses.
| - Verifier commands are executed; poorly chosen verifier commands carry security risk despite preflight policy checks
- Cost and token figures may be estimates (labeled with provenance) and should not be treated as settled accounting
- Receipt integrity must be verified before use as trustworthy evidence; missing rollback evidence is flagged as EVIDENCE_BOUNDARY
- Policy defaults come from martin.config.yaml and can be overridden by CLI flags; misconfiguration can loosen safety boundaries
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| Supported clients | Claude Desktop, Claude Code, Cursor | Claude Code, Codex, Gemini CLI, Cursor, VS Code, GitHub Copilot, Continue |
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| Tools | 6 | 0 |
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