Home/Compare/eval-view vs myclaw-bench

Comparison

eval-view vs myclaw-bench

Verdict

Pick eval-view if regression testing for AI agents to detect behavioral changes and output quality regressions over time; 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.

Markdown twin · eval-view alternatives · myclaw-bench alternatives

GraphCanon updated 3w

eval-view logo

eval-view

hidai25/eval-view

126pushed Jul 26, 2026
vs
myclaw-bench logo

myclaw-bench

LeoYeAI/myclaw-bench

227pushed Jul 20, 2026

Trust & integrity

Signaleval-viewmyclaw-bench
Maintenance
Very active (6d since push)
As of 3w · github_public_v1
Active (8d since push)
As of 3w · github_public_v1
Provenance
Not a fork · Personal account
As of 3w · github_public_v1
Not a fork · Personal 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

eval-view
Regression testing for AI agents
myclaw-bench
Benchmark for AI agents on OpenClaw

Stars

eval-view
126
myclaw-bench
227

Forks

eval-view
21
myclaw-bench
38

Open issues

eval-view
3
myclaw-bench
2

Language

eval-view
Python
myclaw-bench
Python

Adopt for

eval-view
Regression testing for AI agents to detect behavioral changes and output quality regressions over time.
myclaw-bench
myclaw-bench is a benchmark suite comprising 45 tasks across four tiers designed for evaluating AI agents within the OpenClaw platform.

Persona

eval-view
-
myclaw-bench
-

Runtime

eval-view
-
myclaw-bench
-

License

eval-view
The software uses the Apache-2.0 license, offering permissive terms for use and distribution.
myclaw-bench
MIT

Last pushed

eval-view
Jul 26, 2026
myclaw-bench
Jul 20, 2026

Categories

eval-view
AI Agents, Evaluation & Observability
myclaw-bench
AI Agents, Evaluation & Observability

Trust and health

Maintenance

eval-view
Very active (96%)
myclaw-bench
Active (82%)

Days since push

eval-view
6d
myclaw-bench
8d

Open issues (now)

eval-view
3
myclaw-bench
2

Full report

eval-view
Trust report
myclaw-bench
Trust report

Shared compatibility

  • Python · eval-view: Python runtime · myclaw-bench: Python runtime

Choose eval-view if…

  • License: eval-view is Apache-2.0, myclaw-bench is MIT.
  • Pricing: Free to use under the terms of the Apache License, Version 2.0..
  • Requirements: Python environment is required for installation and usage.; Installation with pip: `pip install evalview`; Offline support means no live API keys necessary for the basic diff functionality..
  • Tags unique to eval-view: agent-benchmark, agent-evaluation, ai-agents, regression-testing.
  • eval-view ships Docker support for self-hosted deployment.
  • When you need to track and assess the behavior consistency of your AI agent across versions without involving live API calls.

When NOT to use eval-view

  • If you do not need to monitor specific behavioral characteristics such as tool call sequences and parameter consistency over time.
  • When real-time output quality evaluation is critical, as eval-view's offline diffing does not provide immediate feedback on output changes without an LLM judge.

Choose myclaw-bench if…

  • License: myclaw-bench is MIT, eval-view 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 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.

Explore

Sources

Every stat on this page traces to a dated GitHub sync, license file, enrichment field, or trust scan.

GitHub stars on cards: eval-view 126 · myclaw-bench 227 (synced Aug 2, 2026).

Common questions

What is the difference between eval-view and myclaw-bench?
eval-view: Regression testing for AI agents. myclaw-bench: Benchmark for AI agents on OpenClaw. See the comparison table for live GitHub stats and shared categories.
When should I choose eval-view over myclaw-bench?
Choose eval-view over myclaw-bench when License: eval-view is Apache-2.0, myclaw-bench is MIT; Pricing: Free to use under the terms of the Apache License, Version 2.0.; Requirements: Python environment is required for installation and usage.; Installation with pip: pip install evalview; Offline support means no live API keys necessary for the basic diff functionality.; Tags unique to eval-view: agent-benchmark, agent-evaluation, ai-agents, regression-testing; eval-view ships Docker support for self-hosted deployment; When you need to track and assess the behavior consistency of your AI agent across versions without involving live API calls.
When should I choose myclaw-bench over eval-view?
Choose myclaw-bench over eval-view when License: myclaw-bench is MIT, eval-view 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 eval-view?
If you do not need to monitor specific behavioral characteristics such as tool call sequences and parameter consistency over time. When real-time output quality evaluation is critical, as eval-view's offline diffing does not provide immediate feedback on output changes without an LLM judge.
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 eval-view or myclaw-bench more popular on GitHub?
myclaw-bench has more GitHub stars (227 vs 126). Stars measure visibility, not whether either tool fits your constraints.
Are eval-view and myclaw-bench open source?
Yes - both are open-source projects on GitHub (eval-view: Apache-2.0, myclaw-bench: MIT).
Where can I find alternatives to eval-view or myclaw-bench?
GraphCanon lists graph-backed alternatives at eval-view alternatives and myclaw-bench alternatives (eval-view markdown twin, myclaw-bench 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, eval-view or myclaw-bench?
eval-view: Very active. 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 eval-view and myclaw-bench?
GraphCanon publishes per-repo trust reports with dated maintenance, provenance, and scan summaries: eval-view trust report; myclaw-bench trust report.

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