Comparison
agentdojo vs AssetOpsBench
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 AssetOpsBench if assetOpsBench is a specialized framework for developing and evaluating AI agents in Industry 4.0 contexts, with an emphasis on operations and maintenance scenarios including HVAC systems and IoT management.
Markdown twin · agentdojo alternatives · AssetOpsBench alternatives
GraphCanon updated Oct 6, 2026
vs
Trust & integrity
| Signal | agentdojo | AssetOpsBench |
|---|---|---|
| Maintenance | Slowing (125d since push) As of Oct 6, 2026 · github_public_v1 | Very active (0d since push) As of Sep 20, 2026 · github_public_v1 |
| Provenance | Not a fork · Organization account As of Oct 6, 2026 · github_public_v1 | Not a fork · Organization account As of Sep 20, 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 Jul 11, 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
- AssetOpsBench
- Framework for building and evaluating AI agents targeting Industry 4.0 asset operations
Stars
- agentdojo
- 893
- AssetOpsBench
- 2.3k
Forks
- agentdojo
- 235
- AssetOpsBench
- 325
Open issues
- agentdojo
- 72
- AssetOpsBench
- 45
Language
- agentdojo
- Python
- AssetOpsBench
- 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.
- AssetOpsBench
- AssetOpsBench is a specialized framework for developing and evaluating AI agents in Industry 4.0 contexts, with an emphasis on operations and maintenance scenarios including HVAC systems and IoT management.
Persona
- agentdojo
- -
- AssetOpsBench
- -
Runtime
- agentdojo
- -
- AssetOpsBench
- -
License
- agentdojo
- MIT
- AssetOpsBench
- Apache-2.0
Last pushed
- agentdojo
- Jun 2, 2026
- AssetOpsBench
- Sep 20, 2026
Categories
- agentdojo
- AI Agents, Evaluation & Observability
- AssetOpsBench
- AI Agents, Evaluation & Observability
Trust and health
Maintenance
- agentdojo
- Slowing (36%)
- AssetOpsBench
- Very active (96%)
Days since push
- agentdojo
- 125d
- AssetOpsBench
- 0d
Open issues (now)
- agentdojo
- 72
- AssetOpsBench
- 45
Stars delta
- agentdojo
- +91 (30d)
- AssetOpsBench
- +235 (30d)
Open issues delta
- agentdojo
- +21 (30d)
- AssetOpsBench
- 0 (30d)
Full report
- agentdojo
- Trust report
- AssetOpsBench
- Trust report
Shared compatibility
- Python · agentdojo: Python runtime · AssetOpsBench: Python runtime
Choose agentdojo if…
- License: agentdojo is MIT, AssetOpsBench 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 AssetOpsBench if…
- License: AssetOpsBench is Apache-2.0, agentdojo is MIT.
- Tags unique to AssetOpsBench: ai-for-physical-assets, condition-based-maintenance, hvac-maintenance, iot.
- When you need detailed evaluation frameworks for multiple types of AI agents operating in industry environments
When NOT to use AssetOpsBench
- If your project focus is on general-purpose AI outside the domain-specific context of industrial operations
- Do not use if you require real-time agent orchestration without any emphasis on condition-based or predictive maintenance in asset management
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 (IBM/AssetOpsBench) · observed Sep 20, 2026
- GitHub forks (IBM/AssetOpsBench) · observed Sep 20, 2026
- Last push (IBM/AssetOpsBench) · observed Sep 20, 2026
- License file (Apache-2.0) · observed Sep 20, 2026
- Decision facts (enrichment) · observed Jul 16, 2026
- Trust scan (lockfile / OSV) · observed Jul 11, 2026
GitHub stars on cards: agentdojo 893 · AssetOpsBench 2.3k (synced Oct 6, 2026).
Common questions
- What is the difference between agentdojo and AssetOpsBench?
- agentdojo: A Dynamic Environment to Evaluate Prompt Injection Attacks and Defenses for LLM Agents. AssetOpsBench: Framework for building and evaluating AI agents targeting Industry 4.0 asset operations. See the comparison table for live GitHub stats and shared categories.
- When should I choose agentdojo over AssetOpsBench?
- Choose agentdojo over AssetOpsBench when License: agentdojo is MIT, AssetOpsBench 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 AssetOpsBench over agentdojo?
- Choose AssetOpsBench over agentdojo when License: AssetOpsBench is Apache-2.0, agentdojo is MIT; Tags unique to AssetOpsBench: ai-for-physical-assets, condition-based-maintenance, hvac-maintenance, iot; When you need detailed evaluation frameworks for multiple types of AI agents operating in industry environments.
- 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 AssetOpsBench?
- If your project focus is on general-purpose AI outside the domain-specific context of industrial operations Do not use if you require real-time agent orchestration without any emphasis on condition-based or predictive maintenance in asset management
- Is agentdojo or AssetOpsBench more popular on GitHub?
- AssetOpsBench has more GitHub stars (2,304 vs 893). Stars measure visibility, not whether either tool fits your constraints.
- Are agentdojo and AssetOpsBench open source?
- Yes - both are open-source projects on GitHub (agentdojo: MIT, AssetOpsBench: Apache-2.0).
- Where can I find alternatives to agentdojo or AssetOpsBench?
- GraphCanon lists graph-backed alternatives at agentdojo alternatives and AssetOpsBench alternatives (agentdojo markdown twin, AssetOpsBench 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 AssetOpsBench?
- agentdojo: Slowing. AssetOpsBench: Very 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 AssetOpsBench?
- GraphCanon publishes per-repo trust reports with dated maintenance, provenance, and scan summaries: agentdojo trust report; AssetOpsBench trust report.