Comparison
agent-opt vs ClawBench
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.
Markdown twin · agent-opt alternatives · ClawBench alternatives
GraphCanon updated 2w
vs
Trust & integrity
| Signal | agent-opt | ClawBench |
|---|---|---|
| Maintenance | Steady (35d since push) As of 2w · github_public_v1 | Very active (0d since push) As of 3w · github_public_v1 |
| Provenance | Not a fork · Organization account As of 2w · github_public_v1 | Not a fork · Organization account As of 3w · github_public_v1 |
| OSV dependency advisories | No lockfile (source not queried) As of 1mo · osv@v1 | No lockfile (source not queried) As of 1mo · osv@v1 |
| deps.dev advisories | Not queried deps.dev@v1 | Not queried deps.dev@v1 |
| OpenSSF Scorecard | Not queried openssf-scorecard@v1 | Not queried openssf-scorecard@v1 |
Tagline
- agent-opt
- Open Source Library for Automated Optimization of AI Agent Workflows
- ClawBench
- Open-source benchmark for browser AI agents on daily tasks
Stars
- agent-opt
- 71
- ClawBench
- 532
Forks
- agent-opt
- 7
- ClawBench
- 30
Open issues
- agent-opt
- 0
- ClawBench
- 47
Language
- agent-opt
- Python
- ClawBench
- Python
Adopt for
- agent-opt
- 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
- ClawBench offers an open-source benchmark framework for evaluating browser-based AI agents on real-world online tasks.
Persona
- agent-opt
- -
- ClawBench
- -
Runtime
- agent-opt
- -
- ClawBench
- -
License
- agent-opt
- Apache-2.0
- ClawBench
- ClawBench operates under the Apache-2.0 license, offering a permissive free software license that encourages software reuse and interoperability.
Last pushed
- agent-opt
- Jun 30, 2026
- ClawBench
- Jul 28, 2026
Categories
- agent-opt
- AI Agents, Evaluation & Observability
- ClawBench
- AI Agents, Evaluation & Observability
Trust and health
Maintenance
- agent-opt
- Steady (60%)
- ClawBench
- Very active (96%)
Days since push
- agent-opt
- 35d
- ClawBench
- 0d
Open issues (now)
- agent-opt
- 0
- ClawBench
- 47
Full report
- agent-opt
- Trust report
- ClawBench
- Trust report
Shared compatibility
- Python · agent-opt: Python runtime · ClawBench: Python runtime
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).
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
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 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.
Explore
Sources
Every stat on this page traces to a dated GitHub sync, license file, enrichment field, or trust scan.
- GitHub stars (future-agi/agent-opt) · observed Aug 4, 2026
- GitHub forks (future-agi/agent-opt) · observed Aug 4, 2026
- Last push (future-agi/agent-opt) · observed Jun 30, 2026
- License file (Apache-2.0) · observed Aug 4, 2026
- Decision facts (enrichment) · observed Jul 17, 2026
- Trust scan (lockfile / OSV) · observed Jul 11, 2026
- GitHub stars (TIGER-AI-Lab/ClawBench) · observed Jul 28, 2026
- GitHub forks (TIGER-AI-Lab/ClawBench) · observed Jul 28, 2026
- Last push (TIGER-AI-Lab/ClawBench) · observed Jul 28, 2026
- License file (Apache-2.0) · observed Jul 28, 2026
- Decision facts (enrichment) · observed Jul 16, 2026
- Trust scan (lockfile / OSV) · observed Jul 11, 2026
GitHub stars on cards: agent-opt 71 · ClawBench 532 (synced Aug 4, 2026).
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 and ClawBench alternatives (agent-opt markdown twin, ClawBench markdown twin), 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 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; ClawBench trust report.