--- title: "stepshield vs eval-view" type: "comparison" canonical_url: "https://www.graphcanon.com/compare/glo26-stepshield-vs-hidai25-eval-view" tools: ["glo26-stepshield", "hidai25-eval-view"] --- # stepshield vs eval-view *GraphCanon updated Sep 20, 2026* ## Verdict Pick stepshield if stepShield aids in evaluating temporal guardrail effectiveness on AI agents through step-level annotations, ideal for ensuring security over time; 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. [stepshield](https://huggingface.co/datasets/glo26/stepshield) reports 76 GitHub stars, 17 forks, and 18 open issues, last pushed Sep 5, 2026. [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 [stepshield's repository](https://github.com/glo26/stepshield) and [eval-view's repository](https://github.com/hidai25/eval-view). | | [stepshield](/tools/glo26-stepshield.md) | [eval-view](/tools/hidai25-eval-view.md) | | --- | --- | --- | | Tagline | Temporal evaluation benchmark for AI agent guardrails | Regression testing for AI agents, snapshots behavior, diffs tool calls, catches regressions in CI | | Stars | 76 | 134 | | Forks | 17 | 24 | | Open issues | 18 | 2 | | Language | Python | Python | | Adopt for | StepShield aids in evaluating temporal guardrail effectiveness on AI agents through step-level annotations, ideal for ensuring security over time. | 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 | Other | Apache-2.0 | | Categories | AI Agents, Evaluation & Observability | AI Agents, Evaluation & Observability | ## Trust and health _Sourced signals - not a safety guarantee. No winner column._ | | [stepshield](/tools/glo26-stepshield.md) | [eval-view](/tools/hidai25-eval-view.md) | | --- | --- | --- | | Days since push | 7d | 13d | | Open issues (now) | 18 | 2 | | Stars delta | -1 (30d) | +8 (30d) | | Open issues delta | +2 (30d) | -1 (30d) | | Full report | [trust report](/tools/glo26-stepshield/trust.md) | [trust report](/tools/hidai25-eval-view/trust.md) | ## Shared compatibility - **Python**: [stepshield](/tools/glo26-stepshield.md) - Python runtime; [eval-view](/tools/hidai25-eval-view.md) - Python runtime ## Decision facts: stepshield - **Adopt for:** StepShield aids in evaluating temporal guardrail effectiveness on AI agents through step-level annotations, ideal for ensuring security over time. ## 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 stepshield if… - License: stepshield is Other, eval-view is Apache-2.0. - Tags unique to stepshield: agent-security, ai-safety, benchmark, dataset. - When you need to measure the timing of interventions rather than just if they occur ### Choose eval-view if… - License: eval-view is Apache-2.0, stepshield is Other. - Tags unique to eval-view: agent-benchmark, agent-evaluation, agentic-ai, 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 stepshield - If your project does not require temporal analysis of guardrail performance - When you seek real-time intervention and do not need pre-defined trajectory datasets ## 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 stepshield and eval-view? stepshield: Temporal evaluation benchmark for AI agent guardrails. 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 stepshield over eval-view? Choose stepshield over eval-view when License: stepshield is Other, eval-view is Apache-2.0; Tags unique to stepshield: agent-security, ai-safety, benchmark, dataset; When you need to measure the timing of interventions rather than just if they occur. ### When should I choose eval-view over stepshield? Choose eval-view over stepshield when License: eval-view is Apache-2.0, stepshield is Other; Tags unique to eval-view: agent-benchmark, agent-evaluation, agentic-ai, 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 stepshield? If your project does not require temporal analysis of guardrail performance When you seek real-time intervention and do not need pre-defined trajectory datasets ### 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 stepshield or eval-view more popular on GitHub? eval-view has more GitHub stars (134 vs 76). Stars measure visibility, not whether either tool fits your constraints. ### Are stepshield and eval-view open source? Yes - both are open-source projects on GitHub (stepshield: Other, eval-view: Apache-2.0). ### Where can I find alternatives to stepshield or eval-view? GraphCanon lists graph-backed alternatives at [stepshield alternatives](/tools/glo26-stepshield/alternatives) and [eval-view alternatives](/tools/hidai25-eval-view/alternatives) ([stepshield markdown twin](/tools/glo26-stepshield/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/glo26-stepshield-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, stepshield or eval-view? stepshield: Active. 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 stepshield and eval-view? GraphCanon publishes per-repo trust reports with dated maintenance, provenance, and scan summaries: [stepshield trust report](/tools/glo26-stepshield/trust); [eval-view trust report](/tools/hidai25-eval-view/trust). --- **Machine-readable endpoints** - JSON: [`/api/graphcanon/graph?tool=glo26-stepshield`](/api/graphcanon/graph?tool=glo26-stepshield) - 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/_