Comparison
eval-view vs kitaru
Verdict
Pick eval-view if eval-view is a Python-based tool for regression testing of AI agents, supporting multiple platforms like LangGraph, CrewAI, OpenAI, and Anthropic. It snapshots AI behavior and detects regressions through diffing tool and; pick kitaru if kitaru focuses on recording, replaying, and enhancing the performance of AI agents in production environments using technology from ZenML.
Markdown twin · eval-view alternatives · kitaru alternatives
GraphCanon updated Sep 29, 2026
6views this month
Trust & integrity
| Signal | eval-view | kitaru |
|---|---|---|
| Maintenance | Active (13d since push) As of Sep 18, 2026 · github_public_v1 | Very active (0d since push) As of Sep 29, 2026 · github_public_v1 |
| Provenance | Not a fork · Personal account As of Sep 18, 2026 · github_public_v1 | Not a fork · Organization account As of Sep 29, 2026 · github_public_v1 |
| OSV dependency advisories | No lockfile (source not queried) As of Sep 18, 2026 · osv@v1 | No lockfile (source not queried) As of Jul 11, 2026 · 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, snapshots behavior, diffs tool calls, catches regressions in CI
- kitaru
- Record, replay, and improve AI agents in production, built on ZenML
Stars
- eval-view
- 134
- kitaru
- 297
Forks
- eval-view
- 24
- kitaru
- 25
Open issues
- eval-view
- 2
- kitaru
- 48
Language
- eval-view
- Python
- kitaru
- Python
Adopt for
- eval-view
- Eval-view is a Python-based tool for regression testing of AI agents, supporting multiple platforms like LangGraph, CrewAI, OpenAI, and Anthropic. It snapshots AI behavior and detects regressions through diffing tool and
- kitaru
- Kitaru focuses on recording, replaying, and enhancing the performance of AI agents in production environments using technology from ZenML.
Persona
- eval-view
- -
- kitaru
- -
Runtime
- eval-view
- -
- kitaru
- -
License
- eval-view
- Apache-2.0
- kitaru
- Apache-2.0
Last pushed
- eval-view
- Sep 5, 2026
- kitaru
- Sep 29, 2026
Categories
- eval-view
- AI Agents, Evaluation & Observability
- kitaru
- AI Agents, Evaluation & Observability
Trust and health
Maintenance
- eval-view
- Active (82%)
- kitaru
- Very active (96%)
Days since push
- eval-view
- 13d
- kitaru
- 0d
Open issues (now)
- eval-view
- 2
- kitaru
- 48
Stars delta
- eval-view
- +8 (30d)
- kitaru
- +71 (30d)
Owner type
- eval-view
- User
- kitaru
- Organization
Full report
- eval-view
- Trust report
- kitaru
- Trust report
Shared compatibility
- Python · eval-view: Python runtime · kitaru: Python runtime
Choose eval-view if…
- Tags unique to eval-view: agent-benchmark, agent-evaluation, agentic-ai, anthropic.
- When you need to snapshot and diff the behavior of AI agents across multiple platforms, including LangGraph, CrewAI, OpenAI, and Anthropic.
- Leaner open-issue backlog (2).
When NOT to use eval-view
- If you are working exclusively with AI platforms not supported by eval-view, such as those not listed among LangGraph, CrewAI, OpenAI, and Anthropic.
- When you do not require regression testing or behavior snapshotting for your AI agents, as eval-view is specifically designed for these purposes.
- If you are looking for a tool that does not involve backend API charges for executing your agent, as eval-view does not skip these charges even with the --no-judge flag.
- If you need a tool that automatically handles the migration from the OpenAI Assistants API to the Responses API without manual intervention, as eval-view requires following a migration guide for this.
Choose kitaru if…
- Tags unique to kitaru: agent-framework, checkpoints, durable-execution, llm.
- - You need to ensure the continuous improvement of AI agents that are already deployed; Kitaru allows you to replay scenarios with different approaches to identify improvements.
- More GitHub stars (297 vs 134) - visibility, not fit.
When NOT to use kitaru
- - If your project is in the early stages of development without a clear need for replaying historical data or improving upon past behaviors;
- - When working outside Python, as Kitaru does not currently offer support for other programming languages.
Explore
Sources
Every stat on this page traces to a dated GitHub sync, license file, enrichment field, or trust scan.
- GitHub stars (hidai25/eval-view) · observed Sep 20, 2026
- GitHub forks (hidai25/eval-view) · observed Sep 20, 2026
- Last push (hidai25/eval-view) · observed Sep 5, 2026
- License file (Apache-2.0) · observed Sep 20, 2026
- Decision facts (enrichment) · observed Sep 18, 2026
- Trust scan (lockfile / OSV) · observed Sep 18, 2026
- GitHub stars (zenml-io/kitaru) · observed Sep 29, 2026
- GitHub forks (zenml-io/kitaru) · observed Sep 29, 2026
- Last push (zenml-io/kitaru) · observed Sep 29, 2026
- License file (Apache-2.0) · observed Sep 29, 2026
- Decision facts (enrichment) · observed Jul 17, 2026
- Trust scan (lockfile / OSV) · observed Jul 11, 2026
GitHub stars on cards: eval-view 134 · kitaru 297 (synced Sep 20, 2026).
Common questions
- What is the difference between eval-view and kitaru?
- eval-view: Regression testing for AI agents, snapshots behavior, diffs tool calls, catches regressions in CI. kitaru: Record, replay, and improve AI agents in production, built on ZenML. See the comparison table for live GitHub stats and shared categories.
- When should I choose eval-view over kitaru?
- Choose eval-view over kitaru when Tags unique to eval-view: agent-benchmark, agent-evaluation, agentic-ai, anthropic; When you need to snapshot and diff the behavior of AI agents across multiple platforms, including LangGraph, CrewAI, OpenAI, and Anthropic; Leaner open-issue backlog (2).
- When should I choose kitaru over eval-view?
- Choose kitaru over eval-view when Tags unique to kitaru: agent-framework, checkpoints, durable-execution, llm; - You need to ensure the continuous improvement of AI agents that are already deployed; Kitaru allows you to replay scenarios with different approaches to identify improvements; More GitHub stars (297 vs 134) - visibility, not fit.
- When should I avoid eval-view?
- If you are working exclusively with AI platforms not supported by eval-view, such as those not listed among LangGraph, CrewAI, OpenAI, and Anthropic. When you do not require regression testing or behavior snapshotting for your AI agents, as eval-view is specifically designed for these purposes. If you are looking for a tool that does not involve backend API charges for executing your agent, as eval-view does not skip these charges even with the --no-judge flag. If you need a tool that automatically handles the migration from the OpenAI Assistants API to the Responses API without manual intervention, as eval-view requires following a migration guide for this.
- When should I avoid kitaru?
- - If your project is in the early stages of development without a clear need for replaying historical data or improving upon past behaviors; - When working outside Python, as Kitaru does not currently offer support for other programming languages.
- Is eval-view or kitaru more popular on GitHub?
- kitaru has more GitHub stars (297 vs 134). Stars measure visibility, not whether either tool fits your constraints.
- Are eval-view and kitaru open source?
- Yes - both are open-source projects on GitHub (eval-view: Apache-2.0, kitaru: Apache-2.0).
- Where can I find alternatives to eval-view or kitaru?
- GraphCanon lists graph-backed alternatives at eval-view alternatives and kitaru alternatives (eval-view markdown twin, kitaru 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 kitaru?
- eval-view: Active. kitaru: 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 eval-view and kitaru?
- GraphCanon publishes per-repo trust reports with dated maintenance, provenance, and scan summaries: eval-view trust report; kitaru trust report.