--- title: "eval-view vs tree-of-thoughts" type: "comparison" canonical_url: "https://www.graphcanon.com/compare/hidai25-eval-view-vs-kyegomez-tree-of-thoughts" tools: ["hidai25-eval-view", "kyegomez-tree-of-thoughts"] --- # eval-view vs tree-of-thoughts *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 tree-of-thoughts if (Tree-of-Thoughts) Plug in and Play Implementation of Tree of Thoughts for Elevated Model Reasoning. [eval-view](https://evalview.com) reports 134 GitHub stars, 24 forks, and 2 open issues, last pushed Sep 5, 2026. [tree-of-thoughts](https://discord.gg/qUtxnK2NMf) has 4.6k stars, 376 forks, and 21 open issues, last pushed Jul 29, 2025. Figures are from public GitHub metadata via [eval-view's repository](https://github.com/hidai25/eval-view) and [tree-of-thoughts's repository](https://github.com/kyegomez/tree-of-thoughts). | | [eval-view](/tools/hidai25-eval-view.md) | [tree-of-thoughts](/tools/kyegomez-tree-of-thoughts.md) | | --- | --- | --- | | Tagline | Regression testing for AI agents, snapshots behavior, diffs tool calls, catches regressions in CI | Plug in and Play Implementation of Tree of Thoughts for Elevated Model Reasoning | | Stars | 134 | 4,588 | | Forks | 24 | 376 | | Open issues | 2 | 21 | | 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 | (Tree-of-Thoughts) Plug in and Play Implementation of Tree of Thoughts for Elevated Model Reasoning | | Persona | - | - | | Runtime | - | - | | License | Apache-2.0 | Licensed under Apache-2.0, allowing for wide usage but requires preservation of copyright and license notices | | Categories | AI Agents, Evaluation & Observability | Evaluation & Observability, Model Training | ## Trust and health _Sourced signals - not a safety guarantee. No winner column._ | | [eval-view](/tools/hidai25-eval-view.md) | [tree-of-thoughts](/tools/kyegomez-tree-of-thoughts.md) | | --- | --- | --- | | Maintenance | Active (82%) | Dormant (18%) | | Days since push | 13d | 418d | | Open issues (now) | 2 | 21 | | Stars delta | +8 (30d) | -2 (30d) | | Open issues delta | -1 (30d) | 0 (30d) | | Full report | [trust report](/tools/hidai25-eval-view/trust.md) | [trust report](/tools/kyegomez-tree-of-thoughts/trust.md) | ## 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: tree-of-thoughts - **Pricing:** freemium - Free to use due to open-source nature; potential costs associated with hosting and any paid models it interfaces with - **Requirements:** Min 4 GB RAM - **Adopt for:** (Tree-of-Thoughts) Plug in and Play Implementation of Tree of Thoughts for Elevated Model Reasoning - **License detail:** Licensed under Apache-2.0, allowing for wide usage but requires preservation of copyright and license notices ## Choose when ### Choose eval-view if… - 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 tree-of-thoughts if… - Pricing: Free to use due to open-source nature; potential costs associated with hosting and any paid models it interfaces with. - Requirements: Min 4 GB RAM. - Tags unique to tree-of-thoughts: artificial-intelligence, chatgpt, deep-learning, gpt4. - Also covers Model Training. - - When you require enhanced reasoning capabilities from large language models through structured problem-solving techniques ## 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 tree-of-thoughts - - Avoid if you need solutions that are heavily customizable beyond what is provided, as it may not offer deep configuration options - - Should be avoided in scenarios where minimal dependency installations are critical, as this tool might come with broader package dependencies that could complicate setup ## Common questions ### What is the difference between eval-view and tree-of-thoughts? eval-view: Regression testing for AI agents, snapshots behavior, diffs tool calls, catches regressions in CI. tree-of-thoughts: Plug in and Play Implementation of Tree of Thoughts for Elevated Model Reasoning. See the comparison table for live GitHub stats and shared categories. ### When should I choose eval-view over tree-of-thoughts? Choose eval-view over tree-of-thoughts when 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 tree-of-thoughts over eval-view? Choose tree-of-thoughts over eval-view when Pricing: Free to use due to open-source nature; potential costs associated with hosting and any paid models it interfaces with; Requirements: Min 4 GB RAM; Tags unique to tree-of-thoughts: artificial-intelligence, chatgpt, deep-learning, gpt4; Also covers Model Training; - When you require enhanced reasoning capabilities from large language models through structured problem-solving techniques. ### 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 tree-of-thoughts? - Avoid if you need solutions that are heavily customizable beyond what is provided, as it may not offer deep configuration options - Should be avoided in scenarios where minimal dependency installations are critical, as this tool might come with broader package dependencies that could complicate setup ### Is eval-view or tree-of-thoughts more popular on GitHub? tree-of-thoughts has more GitHub stars (4,588 vs 134). Stars measure visibility, not whether either tool fits your constraints. ### Are eval-view and tree-of-thoughts open source? Yes - both are open-source projects on GitHub (eval-view: Apache-2.0, tree-of-thoughts: Apache-2.0). ### Where can I find alternatives to eval-view or tree-of-thoughts? GraphCanon lists graph-backed alternatives at [eval-view alternatives](/tools/hidai25-eval-view/alternatives) and [tree-of-thoughts alternatives](/tools/kyegomez-tree-of-thoughts/alternatives) ([eval-view markdown twin](/tools/hidai25-eval-view/alternatives.md), [tree-of-thoughts markdown twin](/tools/kyegomez-tree-of-thoughts/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-kyegomez-tree-of-thoughts.md) mirrors this page for agents and LLM crawlers, with the same stats table and FAQ answers. ### Which is better maintained, eval-view or tree-of-thoughts? eval-view: Active. tree-of-thoughts: 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 tree-of-thoughts? GraphCanon publishes per-repo trust reports with dated maintenance, provenance, and scan summaries: [eval-view trust report](/tools/hidai25-eval-view/trust); [tree-of-thoughts trust report](/tools/kyegomez-tree-of-thoughts/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/_