Comparison
agentdojo vs eval-view
Verdict
Pick agentdojo if agentDojo serves as a benchmarking environment to evaluate security attacks, like prompt injection, and defenses for Large Language Model (LLM) agents; 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.
Markdown twin · agentdojo alternatives · eval-view alternatives
GraphCanon updated Oct 6, 2026
10views this month
vs
Trust & integrity
| Signal | agentdojo | eval-view |
|---|---|---|
| Maintenance | Slowing (125d since push) As of Oct 6, 2026 · github_public_v1 | Active (13d since push) As of Sep 18, 2026 · github_public_v1 |
| Provenance | Not a fork · Organization account As of Oct 6, 2026 · github_public_v1 | Not a fork · Personal account As of Sep 18, 2026 · github_public_v1 |
| OSV dependency advisories | No lockfile (source not queried) As of Jul 11, 2026 · osv@v1 | No lockfile (source not queried) As of Sep 18, 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
- agentdojo
- A Dynamic Environment to Evaluate Prompt Injection Attacks and Defenses for LLM Agents
- eval-view
- Regression testing for AI agents, snapshots behavior, diffs tool calls, catches regressions in CI
Stars
- agentdojo
- 893
- eval-view
- 134
Forks
- agentdojo
- 235
- eval-view
- 24
Open issues
- agentdojo
- 72
- eval-view
- 2
Language
- agentdojo
- Python
- eval-view
- Python
Adopt for
- agentdojo
- AgentDojo serves as a benchmarking environment to evaluate security attacks, like prompt injection, and defenses for Large Language Model (LLM) agents.
- 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
Persona
- agentdojo
- -
- eval-view
- -
Runtime
- agentdojo
- -
- eval-view
- -
License
- agentdojo
- MIT
- eval-view
- Apache-2.0
Last pushed
- agentdojo
- Jun 2, 2026
- eval-view
- Sep 5, 2026
Categories
- agentdojo
- AI Agents, Evaluation & Observability
- eval-view
- AI Agents, Evaluation & Observability
Trust and health
Maintenance
- agentdojo
- Slowing (36%)
- eval-view
- Active (82%)
Days since push
- agentdojo
- 125d
- eval-view
- 13d
Open issues (now)
- agentdojo
- 72
- eval-view
- 2
Stars delta
- agentdojo
- +91 (30d)
- eval-view
- +8 (30d)
Open issues delta
- agentdojo
- +21 (30d)
- eval-view
- -1 (30d)
Owner type
- agentdojo
- Organization
- eval-view
- User
Full report
- agentdojo
- Trust report
- eval-view
- Trust report
Shared compatibility
- Python · agentdojo: Python runtime · eval-view: Python runtime
Choose agentdojo if…
- License: agentdojo is MIT, eval-view is Apache-2.0.
- Pricing: Open-source under the MIT License. Some advanced features might require additional libraries or APIs..
- Requirements: Min 8 GB RAM.
- Tags unique to agentdojo: benchmark, large-language-models, prompt-injection, security.
- AgentDojo serves as a benchmarking environment to evaluate security attacks, like prompt injection, and defenses for Large Language Model (LLM) agents.
When NOT to use agentdojo
- Last GitHub push was Jun 2, 2026 (slowing maintenance). Validate activity before betting a new project on agentdojo.
- AI Agents: Don't use an agent loop when a deterministic workflow would do; agents add latency, cost, and non-determinism.
- Evaluation & Observability: Defer heavyweight eval infra only until you have real traffic - never skip it once users depend on answers.
Choose eval-view if…
- License: eval-view is Apache-2.0, agentdojo is MIT.
- 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 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.
Explore
Sources
Every stat on this page traces to a dated GitHub sync, license file, enrichment field, or trust scan.
- GitHub stars (ethz-spylab/agentdojo) · observed Oct 6, 2026
- GitHub forks (ethz-spylab/agentdojo) · observed Oct 6, 2026
- Last push (ethz-spylab/agentdojo) · observed Jun 2, 2026
- License file (MIT) · observed Oct 6, 2026
- Decision facts (enrichment) · observed Jul 12, 2026
- Trust scan (lockfile / OSV) · observed Jul 11, 2026
- 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 on cards: agentdojo 893 · eval-view 134 (synced Oct 6, 2026).
Common questions
- What is the difference between agentdojo and eval-view?
- agentdojo: A Dynamic Environment to Evaluate Prompt Injection Attacks and Defenses for LLM Agents. 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 agentdojo over eval-view?
- Choose agentdojo over eval-view when License: agentdojo is MIT, eval-view is Apache-2.0; Pricing: Open-source under the MIT License. Some advanced features might require additional libraries or APIs.; Requirements: Min 8 GB RAM; Tags unique to agentdojo: benchmark, large-language-models, prompt-injection, security; AgentDojo serves as a benchmarking environment to evaluate security attacks, like prompt injection, and defenses for Large Language Model (LLM) agents.
- When should I choose eval-view over agentdojo?
- Choose eval-view over agentdojo when License: eval-view is Apache-2.0, agentdojo is MIT; 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 agentdojo?
- Last GitHub push was Jun 2, 2026 (slowing maintenance). Validate activity before betting a new project on agentdojo. AI Agents: Don't use an agent loop when a deterministic workflow would do; agents add latency, cost, and non-determinism. Evaluation & Observability: Defer heavyweight eval infra only until you have real traffic - never skip it once users depend on answers.
- 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 agentdojo or eval-view more popular on GitHub?
- agentdojo has more GitHub stars (893 vs 134). Stars measure visibility, not whether either tool fits your constraints.
- Are agentdojo and eval-view open source?
- Yes - both are open-source projects on GitHub (agentdojo: MIT, eval-view: Apache-2.0).
- Where can I find alternatives to agentdojo or eval-view?
- GraphCanon lists graph-backed alternatives at agentdojo alternatives and eval-view alternatives (agentdojo markdown twin, eval-view 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, agentdojo or eval-view?
- agentdojo: Slowing. 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 agentdojo and eval-view?
- GraphCanon publishes per-repo trust reports with dated maintenance, provenance, and scan summaries: agentdojo trust report; eval-view trust report.