--- title: "agent-opt vs ClawBench" type: "comparison" canonical_url: "https://www.graphcanon.com/compare/future-agi-agent-opt-vs-tiger-ai-lab-clawbench" tools: ["future-agi-agent-opt", "tiger-ai-lab-clawbench"] --- # agent-opt vs ClawBench *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 ClawBench if clawBench offers an open-source benchmark framework for evaluating browser-based AI agents on real-world online tasks. [agent-opt](https://app.futureagi.com) reports 71 GitHub stars, 7 forks, and 0 open issues, last pushed Jun 30, 2026. [ClawBench](https://claw-bench.com) has 532 stars, 30 forks, and 47 open issues, last pushed Jul 28, 2026. Figures are from public GitHub metadata via [agent-opt's repository](https://github.com/future-agi/agent-opt) and [ClawBench's repository](https://github.com/TIGER-AI-Lab/ClawBench). | | [agent-opt](/tools/future-agi-agent-opt.md) | [ClawBench](/tools/tiger-ai-lab-clawbench.md) | | --- | --- | --- | | Tagline | Open Source Library for Automated Optimization of AI Agent Workflows | Open-source benchmark for browser AI agents on daily tasks | | Stars | 71 | 532 | | Forks | 7 | 30 | | Open issues | 0 | 47 | | 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. | ClawBench offers an open-source benchmark framework for evaluating browser-based AI agents on real-world online tasks. | | Persona | - | - | | Runtime | - | - | | License | Apache-2.0 | ClawBench operates under the Apache-2.0 license, offering a permissive free software license that encourages software reuse and interoperability. | | 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) | [ClawBench](/tools/tiger-ai-lab-clawbench.md) | | --- | --- | --- | | Maintenance | Steady (60%) | Very active (96%) | | Days since push | 35d | 0d | | Open issues (now) | 0 | 47 | | Full report | [trust report](/tools/future-agi-agent-opt/trust.md) | [trust report](/tools/tiger-ai-lab-clawbench/trust.md) | ## Shared compatibility - **Python**: [agent-opt](/tools/future-agi-agent-opt.md) - Python runtime; [ClawBench](/tools/tiger-ai-lab-clawbench.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: ClawBench - **Requirements:** Requires setup for browser automation tasks within the Chrome environment. - **Adopt for:** ClawBench offers an open-source benchmark framework for evaluating browser-based AI agents on real-world online tasks. - **License detail:** ClawBench operates under the Apache-2.0 license, offering a permissive free software license that encourages software reuse and interoperability. ## Choose when ### Choose agent-opt if… - Tags unique to agent-opt: agent, ai-agents, aioptimization, automation. - - When your project needs seamless CI/CD integration alongside automated optimization - Leaner open-issue backlog (0). ### Choose ClawBench if… - Requirements: Requires setup for browser automation tasks within the Chrome environment.. - Tags unique to ClawBench: agent-evaluation, agentic-ai, browser-agent, llm-evaluation. - You are developing a browser AI agent and wish to measure its performance against everyday online activities, as ClawBench specifically simulates these scenarios. ## 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 ClawBench - If your focus is solely on backend server-based AI evaluations without a browser interface involvement, ClawBench will not be the appropriate choice. - For those developing standalone applications or mobile agents, ClawBench’s browser-centric tasks will not reflect their operational capabilities accurately. ## Common questions ### What is the difference between agent-opt and ClawBench? agent-opt: Open Source Library for Automated Optimization of AI Agent Workflows. ClawBench: Open-source benchmark for browser AI agents on daily tasks. See the comparison table for live GitHub stats and shared categories. ### When should I choose agent-opt over ClawBench? Choose agent-opt over ClawBench when Tags unique to agent-opt: agent, ai-agents, aioptimization, automation; - When your project needs seamless CI/CD integration alongside automated optimization; Leaner open-issue backlog (0). ### When should I choose ClawBench over agent-opt? Choose ClawBench over agent-opt when Requirements: Requires setup for browser automation tasks within the Chrome environment.; Tags unique to ClawBench: agent-evaluation, agentic-ai, browser-agent, llm-evaluation; You are developing a browser AI agent and wish to measure its performance against everyday online activities, as ClawBench specifically simulates these scenarios. ### 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 ClawBench? If your focus is solely on backend server-based AI evaluations without a browser interface involvement, ClawBench will not be the appropriate choice. For those developing standalone applications or mobile agents, ClawBench’s browser-centric tasks will not reflect their operational capabilities accurately. ### Is agent-opt or ClawBench more popular on GitHub? ClawBench has more GitHub stars (532 vs 71). Stars measure visibility, not whether either tool fits your constraints. ### Are agent-opt and ClawBench open source? Yes - both are open-source projects on GitHub (agent-opt: Apache-2.0, ClawBench: Apache-2.0). ### Where can I find alternatives to agent-opt or ClawBench? GraphCanon lists graph-backed alternatives at [agent-opt alternatives](/tools/future-agi-agent-opt/alternatives) and [ClawBench alternatives](/tools/tiger-ai-lab-clawbench/alternatives) ([agent-opt markdown twin](/tools/future-agi-agent-opt/alternatives.md), [ClawBench markdown twin](/tools/tiger-ai-lab-clawbench/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-tiger-ai-lab-clawbench.md) mirrors this page for agents and LLM crawlers, with the same stats table and FAQ answers. ### Which is better maintained, agent-opt or ClawBench? agent-opt: Steady. ClawBench: Very 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 ClawBench? GraphCanon publishes per-repo trust reports with dated maintenance, provenance, and scan summaries: [agent-opt trust report](/tools/future-agi-agent-opt/trust); [ClawBench trust report](/tools/tiger-ai-lab-clawbench/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/_