--- title: "eval-view vs just-eval" type: "comparison" canonical_url: "https://www.graphcanon.com/compare/hidai25-eval-view-vs-re-align-just-eval" tools: ["hidai25-eval-view", "re-align-just-eval"] --- # eval-view vs just-eval *GraphCanon updated Sep 20, 2026* ## 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 just-eval if just-eval provides a straightforward GPT-based framework for evaluating LLMs across multiple dimensions with clear outputs. [eval-view](https://evalview.com) reports 134 GitHub stars, 24 forks, and 2 open issues, last pushed Sep 5, 2026. [just-eval](https://allenai.github.io/re-align/) has 90 stars, 7 forks, and 2 open issues, last pushed Jan 29, 2024. Figures are from public GitHub metadata via [eval-view's repository](https://github.com/hidai25/eval-view) and [just-eval's repository](https://github.com/Re-Align/just-eval). | | [eval-view](/tools/hidai25-eval-view.md) | [just-eval](/tools/re-align-just-eval.md) | | --- | --- | --- | | Tagline | Regression testing for AI agents, snapshots behavior, diffs tool calls, catches regressions in CI | A simple GPT-based evaluation tool for multi-aspect, interpretable assessment of LLMs. | | Stars | 134 | 90 | | Forks | 24 | 7 | | Open issues | 2 | 2 | | Language | Python | Python | | Adopt for | 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 | just-eval provides a straightforward GPT-based framework for evaluating LLMs across multiple dimensions with clear outputs. | | Persona | - | - | | Runtime | - | - | | License | Apache-2.0 | MIT | | Categories | AI Agents, Evaluation & Observability | Evaluation & Observability | ## Trust and health _Sourced signals - not a safety guarantee. No winner column._ | | [eval-view](/tools/hidai25-eval-view.md) | [just-eval](/tools/re-align-just-eval.md) | | --- | --- | --- | | Maintenance | Active (82%) | Dormant (18%) | | Days since push | 13d | 953d | | Stars delta | +8 (30d) | 0 (30d) | | Open issues delta | -1 (30d) | 0 (30d) | | Owner type | User | Organization | | Full report | [trust report](/tools/hidai25-eval-view/trust.md) | [trust report](/tools/re-align-just-eval/trust.md) | ## Shared compatibility - **Python**: [eval-view](/tools/hidai25-eval-view.md) - Python runtime; [just-eval](/tools/re-align-just-eval.md) - Python runtime ## Decision facts: eval-view - **Adopt for:** 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 ## Decision facts: just-eval - **Adopt for:** just-eval provides a straightforward GPT-based framework for evaluating LLMs across multiple dimensions with clear outputs. ## Choose when ### Choose eval-view if… - License: eval-view is Apache-2.0, just-eval is MIT. - Tags unique to eval-view: agent-benchmark, agent-evaluation, agentic-ai, ai-agents. - Also covers AI Agents. - eval-view ships Docker support for self-hosted deployment. - When you need to snapshot and diff the behavior of AI agents across multiple platforms, including LangGraph, CrewAI, OpenAI, and Anthropic. ### Choose just-eval if… - License: just-eval is MIT, eval-view is Apache-2.0. - Tags unique to just-eval: evaluation, gpt4, llm, llm-eval. - When your team requires an in-depth yet interpretable evaluation of LLM performance, focusing on various aspects. ## 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. ## When NOT to use just-eval - Avoid if direct integration with competing API services is needed as just-eval focuses solely on OpenAI API key configuration. - Not suitable when your project demands a custom evaluation framework that extends beyond simple GPT-based assessments. ## Common questions ### What is the difference between eval-view and just-eval? eval-view: Regression testing for AI agents, snapshots behavior, diffs tool calls, catches regressions in CI. just-eval: A simple GPT-based evaluation tool for multi-aspect, interpretable assessment of LLMs.. See the comparison table for live GitHub stats and shared categories. ### When should I choose eval-view over just-eval? Choose eval-view over just-eval when License: eval-view is Apache-2.0, just-eval is MIT; Tags unique to eval-view: agent-benchmark, agent-evaluation, agentic-ai, ai-agents; Also covers AI Agents; eval-view ships Docker support for self-hosted deployment; When you need to snapshot and diff the behavior of AI agents across multiple platforms, including LangGraph, CrewAI, OpenAI, and Anthropic. ### When should I choose just-eval over eval-view? Choose just-eval over eval-view when License: just-eval is MIT, eval-view is Apache-2.0; Tags unique to just-eval: evaluation, gpt4, llm, llm-eval; When your team requires an in-depth yet interpretable evaluation of LLM performance, focusing on various aspects. ### 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 just-eval? Avoid if direct integration with competing API services is needed as just-eval focuses solely on OpenAI API key configuration. Not suitable when your project demands a custom evaluation framework that extends beyond simple GPT-based assessments. ### Is eval-view or just-eval more popular on GitHub? eval-view has more GitHub stars (134 vs 90). Stars measure visibility, not whether either tool fits your constraints. ### Are eval-view and just-eval open source? Yes - both are open-source projects on GitHub (eval-view: Apache-2.0, just-eval: MIT). ### Where can I find alternatives to eval-view or just-eval? GraphCanon lists graph-backed alternatives at [eval-view alternatives](/tools/hidai25-eval-view/alternatives) and [just-eval alternatives](/tools/re-align-just-eval/alternatives) ([eval-view markdown twin](/tools/hidai25-eval-view/alternatives.md), [just-eval markdown twin](/tools/re-align-just-eval/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/hidai25-eval-view-vs-re-align-just-eval.md) mirrors this page for agents and LLM crawlers, with the same stats table and FAQ answers. ### Which is better maintained, eval-view or just-eval? eval-view: Active. just-eval: Dormant. 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 just-eval? GraphCanon publishes per-repo trust reports with dated maintenance, provenance, and scan summaries: [eval-view trust report](/tools/hidai25-eval-view/trust); [just-eval trust report](/tools/re-align-just-eval/trust). --- **Machine-readable endpoints** - JSON: [`/api/graphcanon/graph?tool=hidai25-eval-view`](/api/graphcanon/graph?tool=hidai25-eval-view) - 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/_