--- title: "contextcheck vs eval-view" type: "comparison" canonical_url: "https://www.graphcanon.com/compare/addepto-contextcheck-vs-hidai25-eval-view" tools: ["addepto-contextcheck", "hidai25-eval-view"] --- # contextcheck vs eval-view *GraphCanon updated Sep 20, 2026* ## Verdict Pick contextcheck if contextcheck, an MIT-licensed Python framework for evaluating large language models and RAG systems through configurable YAML settings that integrate with CI pipelines; 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. [contextcheck](https://addepto.com/) reports 97 GitHub stars, 11 forks, and 1 open issues, last pushed Dec 11, 2024. [eval-view](https://evalview.com) has 134 stars, 24 forks, and 2 open issues, last pushed Sep 5, 2026. Figures are from public GitHub metadata via [contextcheck's repository](https://github.com/Addepto/contextcheck) and [eval-view's repository](https://github.com/hidai25/eval-view). | | [contextcheck](/tools/addepto-contextcheck.md) | [eval-view](/tools/hidai25-eval-view.md) | | --- | --- | --- | | Tagline | Framework for LLMs and RAGs testing in Python | Regression testing for AI agents, snapshots behavior, diffs tool calls, catches regressions in CI | | Stars | 97 | 134 | | Forks | 11 | 24 | | Open issues | 1 | 2 | | Language | Python | Python | | Adopt for | Contextcheck, an MIT-licensed Python framework for evaluating large language models and RAG systems through configurable YAML settings that integrate with CI pipelines. | 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 | | Persona | - | - | | Runtime | - | - | | License | MIT | Apache-2.0 | | Categories | Evaluation & Observability, Model Training | AI Agents, Evaluation & Observability | ## Trust and health _Sourced signals - not a safety guarantee. No winner column._ | | [contextcheck](/tools/addepto-contextcheck.md) | [eval-view](/tools/hidai25-eval-view.md) | | --- | --- | --- | | Maintenance | Dormant (18%) | Active (82%) | | Days since push | 635d | 13d | | Open issues (now) | 1 | 2 | | Stars delta | +1 (30d) | +8 (30d) | | Open issues delta | 0 (30d) | -1 (30d) | | Owner type | Organization | User | | Full report | [trust report](/tools/addepto-contextcheck/trust.md) | [trust report](/tools/hidai25-eval-view/trust.md) | ## Decision facts: contextcheck - **Adopt for:** Contextcheck, an MIT-licensed Python framework for evaluating large language models and RAG systems through configurable YAML settings that integrate with CI pipelines. ## 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 ## Choose when ### Choose contextcheck if… - License: contextcheck is MIT, eval-view is Apache-2.0. - Tags unique to contextcheck: ai-chat, ai-testing, chatbot-framework, ci-integration. - Also covers Model Training. - When you require a framework specifically designed to test the robustness of both LLMs and Retrieval-Augmented Generation systems within Python projects. ### Choose eval-view if… - License: eval-view is Apache-2.0, contextcheck 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 NOT to use contextcheck - Avoid if you aim for a framework without configuration flexibility through YAML as contextcheck strictly relies on this format for setting up test environments. - Skip contextcheck if your project environment or requirements do not align with the MIT license terms, especially in contexts where licensing compatibility must be strictly observed. ## 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. ## Common questions ### What is the difference between contextcheck and eval-view? contextcheck: Framework for LLMs and RAGs testing in Python. eval-view: Regression testing for AI agents, snapshots behavior, diffs tool calls, catches regressions in CI. See the comparison table for live GitHub stats and shared categories. ### When should I choose contextcheck over eval-view? Choose contextcheck over eval-view when License: contextcheck is MIT, eval-view is Apache-2.0; Tags unique to contextcheck: ai-chat, ai-testing, chatbot-framework, ci-integration; Also covers Model Training; When you require a framework specifically designed to test the robustness of both LLMs and Retrieval-Augmented Generation systems within Python projects. ### When should I choose eval-view over contextcheck? Choose eval-view over contextcheck when License: eval-view is Apache-2.0, contextcheck 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 avoid contextcheck? Avoid if you aim for a framework without configuration flexibility through YAML as contextcheck strictly relies on this format for setting up test environments. Skip contextcheck if your project environment or requirements do not align with the MIT license terms, especially in contexts where licensing compatibility must be strictly observed. ### 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. ### Is contextcheck or eval-view more popular on GitHub? eval-view has more GitHub stars (134 vs 97). Stars measure visibility, not whether either tool fits your constraints. ### Are contextcheck and eval-view open source? Yes - both are open-source projects on GitHub (contextcheck: MIT, eval-view: Apache-2.0). ### Where can I find alternatives to contextcheck or eval-view? GraphCanon lists graph-backed alternatives at [contextcheck alternatives](/tools/addepto-contextcheck/alternatives) and [eval-view alternatives](/tools/hidai25-eval-view/alternatives) ([contextcheck markdown twin](/tools/addepto-contextcheck/alternatives.md), [eval-view markdown twin](/tools/hidai25-eval-view/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/addepto-contextcheck-vs-hidai25-eval-view.md) mirrors this page for agents and LLM crawlers, with the same stats table and FAQ answers. ### Which is better maintained, contextcheck or eval-view? contextcheck: Dormant. eval-view: 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 contextcheck and eval-view? GraphCanon publishes per-repo trust reports with dated maintenance, provenance, and scan summaries: [contextcheck trust report](/tools/addepto-contextcheck/trust); [eval-view trust report](/tools/hidai25-eval-view/trust). --- **Machine-readable endpoints** - JSON: [`/api/graphcanon/graph?tool=addepto-contextcheck`](/api/graphcanon/graph?tool=addepto-contextcheck) - 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/_