--- title: "agent-opt vs myclaw-bench" type: "comparison" canonical_url: "https://www.graphcanon.com/compare/future-agi-agent-opt-vs-leoyeai-myclaw-bench" tools: ["future-agi-agent-opt", "leoyeai-myclaw-bench"] --- # agent-opt vs myclaw-bench *GraphCanon updated Aug 4, 2026* ## Verdict Pick agent-opt if agent-opt is tailored for teams that require automated optimization of AI workflows and support for continuous integration/continuous delivery (CI/CD), relying on Python and specific library dependencies; pick myclaw-bench if myclaw-bench is a benchmark suite comprising 45 tasks across four tiers designed for evaluating AI agents within the OpenClaw platform. [agent-opt](https://app.futureagi.com) reports 71 GitHub stars, 7 forks, and 0 open issues, last pushed Jun 30, 2026. [myclaw-bench](https://myclaw.ai) has 227 stars, 38 forks, and 2 open issues, last pushed Jul 20, 2026. Figures are from public GitHub metadata via [agent-opt's repository](https://github.com/future-agi/agent-opt) and [myclaw-bench's repository](https://github.com/LeoYeAI/myclaw-bench). | | [agent-opt](/tools/future-agi-agent-opt.md) | [myclaw-bench](/tools/leoyeai-myclaw-bench.md) | | --- | --- | --- | | Tagline | Open Source Library for Automated Optimization of AI Agent Workflows | Benchmark for AI agents on OpenClaw | | Stars | 71 | 227 | | Forks | 7 | 38 | | Open issues | 0 | 2 | | Language | Python | Python | | Adopt for | Agent-opt is tailored for teams that require automated optimization of AI workflows and support for continuous integration/continuous delivery (CI/CD), relying on Python and specific library dependencies. | myclaw-bench is a benchmark suite comprising 45 tasks across four tiers designed for evaluating AI agents within the OpenClaw platform. | | Persona | - | - | | Runtime | - | - | | License | Apache-2.0 | MIT | | Categories | AI Agents, Evaluation & Observability | AI Agents, Evaluation & Observability | ## Trust and health _Sourced signals - not a safety guarantee. No winner column._ | | [agent-opt](/tools/future-agi-agent-opt.md) | [myclaw-bench](/tools/leoyeai-myclaw-bench.md) | | --- | --- | --- | | Maintenance | Steady (60%) | Active (82%) | | Days since push | 35d | 8d | | Open issues (now) | 0 | 2 | | Owner type | Organization | User | | Full report | [trust report](/tools/future-agi-agent-opt/trust.md) | [trust report](/tools/leoyeai-myclaw-bench/trust.md) | ## Shared compatibility - **Python**: [agent-opt](/tools/future-agi-agent-opt.md) - Python runtime; [myclaw-bench](/tools/leoyeai-myclaw-bench.md) - Python runtime ## Decision facts: agent-opt - **Adopt for:** Agent-opt is tailored for teams that require automated optimization of AI workflows and support for continuous integration/continuous delivery (CI/CD), relying on Python and specific library dependencies. ## Decision facts: myclaw-bench - **Requirements:** Requires Python version 3.10 or higher to execute the benchmark tasks.; Necessitates installation of the 'uv' package manager from Astral for dependencies management. - **Adopt for:** myclaw-bench is a benchmark suite comprising 45 tasks across four tiers designed for evaluating AI agents within the OpenClaw platform. ## Choose when ### Choose agent-opt if… - License: agent-opt is Apache-2.0, myclaw-bench is MIT. - Tags unique to agent-opt: agent, ai-agents, aioptimization, automation. - - When your project needs seamless CI/CD integration alongside automated optimization ### Choose myclaw-bench if… - License: myclaw-bench is MIT, agent-opt is Apache-2.0. - Requirements: Requires Python version 3.10 or higher to execute the benchmark tasks.; Necessitates installation of the 'uv' package manager from Astral for dependencies management.. - Tags unique to myclaw-bench: ai-agent-evaluation, benchmarking-tools, openclaw. - Use myclaw-bench if you are developing AI agents specifically for deployment on the OpenClaw platform, as it offers a precise evaluation tailored to this ecosystem. ## When NOT to use agent-opt - - If your project does not require Python or if it cannot meet the specific requirement of having Python ≥ 3.10 - - In scenarios where CI/CD integration is not a priority for your AI workflow optimization ## When NOT to use myclaw-bench - Avoid using myclaw-bench if your AI agents will not be deployed on the OpenClaw platform, as its benchmarks are specifically designed to test within this framework. - Do not use if you require synthetic tests for controlling variables in a highly abstracted scenario, since myclaw-bench exclusively leverages real agent session data. ## Common questions ### What is the difference between agent-opt and myclaw-bench? agent-opt: Open Source Library for Automated Optimization of AI Agent Workflows. myclaw-bench: Benchmark for AI agents on OpenClaw. See the comparison table for live GitHub stats and shared categories. ### When should I choose agent-opt over myclaw-bench? Choose agent-opt over myclaw-bench when License: agent-opt is Apache-2.0, myclaw-bench is MIT; Tags unique to agent-opt: agent, ai-agents, aioptimization, automation; - When your project needs seamless CI/CD integration alongside automated optimization. ### When should I choose myclaw-bench over agent-opt? Choose myclaw-bench over agent-opt when License: myclaw-bench is MIT, agent-opt is Apache-2.0; Requirements: Requires Python version 3.10 or higher to execute the benchmark tasks.; Necessitates installation of the 'uv' package manager from Astral for dependencies management.; Tags unique to myclaw-bench: ai-agent-evaluation, benchmarking-tools, openclaw; Use myclaw-bench if you are developing AI agents specifically for deployment on the OpenClaw platform, as it offers a precise evaluation tailored to this ecosystem. ### When should I avoid agent-opt? - If your project does not require Python or if it cannot meet the specific requirement of having Python ≥ 3.10 - In scenarios where CI/CD integration is not a priority for your AI workflow optimization ### When should I avoid myclaw-bench? Avoid using myclaw-bench if your AI agents will not be deployed on the OpenClaw platform, as its benchmarks are specifically designed to test within this framework. Do not use if you require synthetic tests for controlling variables in a highly abstracted scenario, since myclaw-bench exclusively leverages real agent session data. ### Is agent-opt or myclaw-bench more popular on GitHub? myclaw-bench has more GitHub stars (227 vs 71). Stars measure visibility, not whether either tool fits your constraints. ### Are agent-opt and myclaw-bench open source? Yes - both are open-source projects on GitHub (agent-opt: Apache-2.0, myclaw-bench: MIT). ### Where can I find alternatives to agent-opt or myclaw-bench? GraphCanon lists graph-backed alternatives at [agent-opt alternatives](/tools/future-agi-agent-opt/alternatives) and [myclaw-bench alternatives](/tools/leoyeai-myclaw-bench/alternatives) ([agent-opt markdown twin](/tools/future-agi-agent-opt/alternatives.md), [myclaw-bench markdown twin](/tools/leoyeai-myclaw-bench/alternatives.md)), ranked by typed relationship edges rather than popularity votes. ### Is there a machine-readable version of this comparison? Yes. The markdown twin at [this comparison](/compare/future-agi-agent-opt-vs-leoyeai-myclaw-bench.md) mirrors this page for agents and LLM crawlers, with the same stats table and FAQ answers. ### Which is better maintained, agent-opt or myclaw-bench? agent-opt: Steady. myclaw-bench: Active. Compare maintenance labels, days since push, and release cadence in the trust section below - stars alone do not measure maintenance. ### Where are the full trust reports for agent-opt and myclaw-bench? GraphCanon publishes per-repo trust reports with dated maintenance, provenance, and scan summaries: [agent-opt trust report](/tools/future-agi-agent-opt/trust); [myclaw-bench trust report](/tools/leoyeai-myclaw-bench/trust). --- **Machine-readable endpoints** - JSON: [`/api/graphcanon/graph?tool=future-agi-agent-opt`](/api/graphcanon/graph?tool=future-agi-agent-opt) - LLM index: [/llms.txt](/llms.txt) - Full corpus: [/llms-full.txt](/llms-full.txt) _GraphCanon - The knowledge graph for AI development. https://www.graphcanon.com/_