--- title: "agentdojo vs agents-towards-production" type: "comparison" canonical_url: "https://www.graphcanon.com/compare/ethz-spylab-agentdojo-vs-nirdiamant-agents-towards-production" tools: ["ethz-spylab-agentdojo", "nirdiamant-agents-towards-production"] --- # agentdojo vs agents-towards-production *GraphCanon updated Jul 12, 2026* ## 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 agents-towards-production if agents-towards-production is an open-source project focused on providing comprehensive, step-by-step tutorials for developing AI agents from the prototype stage to enterprise-ready deployment. This guide includes best-pr. [agentdojo](https://agentdojo.spylab.ai/) reports 659 GitHub stars, 168 forks, and 33 open issues, last pushed Jun 2, 2026. [agents-towards-production](https://github.com/NirDiamant/agents-towards-production) has 21k stars, 2.8k forks, and 11 open issues, last pushed Jul 4, 2026. Figures are from public GitHub metadata via [agentdojo's repository](https://github.com/ethz-spylab/agentdojo) and [agents-towards-production's repository](https://github.com/NirDiamant/agents-towards-production). | | [agentdojo](/tools/ethz-spylab-agentdojo.md) | [agents-towards-production](/tools/nirdiamant-agents-towards-production.md) | | --- | --- | --- | | Tagline | A Dynamic Environment to Evaluate Prompt Injection Attacks and Defenses for LLM Agents | End-to-end, code-first tutorials for building production-grade GenAI agents | | Stars | 659 | 20,953 | | Forks | 168 | 2,789 | | Open issues | 33 | 11 | | Language | Python | Jupyter Notebook | | Adopt for | AgentDojo serves as a benchmarking environment to evaluate security attacks, like prompt injection, and defenses for Large Language Model (LLM) agents. | agents-towards-production is an open-source project focused on providing comprehensive, step-by-step tutorials for developing AI agents from the prototype stage to enterprise-ready deployment. This guide includes best-pr | | Persona | - | - | | Runtime | - | - | | License | MIT | Other | | Categories | AI Agents, Evaluation & Observability | AI Agents | ## Trust and health _Sourced signals - not a safety guarantee. No winner column._ | | [agentdojo](/tools/ethz-spylab-agentdojo.md) | [agents-towards-production](/tools/nirdiamant-agents-towards-production.md) | | --- | --- | --- | | Maintenance | Steady (60%) | Very active (96%) | | Days since push | 39d | 6d | | Open issues (now) | 33 | 11 | | Owner type | Organization | User | | Security scan | No lockfile | No MCP manifest | | Full report | [trust report](/tools/ethz-spylab-agentdojo/trust.md) | [trust report](/tools/nirdiamant-agents-towards-production/trust.md) | ## Decision facts: agentdojo - **Pricing:** freemium - Open-source under the MIT License. Some advanced features might require additional libraries or APIs. - **Requirements:** Min 8 GB RAM - **Adopt for:** AgentDojo serves as a benchmarking environment to evaluate security attacks, like prompt injection, and defenses for Large Language Model (LLM) agents. ## Decision facts: agents-towards-production - **Adopt for:** agents-towards-production is an open-source project focused on providing comprehensive, step-by-step tutorials for developing AI agents from the prototype stage to enterprise-ready deployment. This guide includes best-pr ## Choose when ### Choose agentdojo if… - agentdojo is primarily Python; agents-towards-production is Jupyter Notebook. - License: agentdojo is MIT, agents-towards-production is Other. - 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. - Also covers Evaluation & Observability. - AgentDojo serves as a benchmarking environment to evaluate security attacks, like prompt injection, and defenses for Large Language Model (LLM) agents. ### Choose agents-towards-production if… - agents-towards-production is primarily Jupyter Notebook; agentdojo is Python. - License: agents-towards-production is Other, agentdojo is MIT. - Tags unique to agents-towards-production: agent-framework, agentic-ai, deployment, genai. - * When you aim to deploy AI agents using cloud services such as AWS Bedrock AgentCore Runtime, where automatic infrastructure management and standardized communication patterns are key. ## When NOT to use 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 NOT to use agents-towards-production - * If your enterprise strictly forbids using cloud services; this tool emphasizes both cloud and on-prem deployment strategies but may not fit entirely on-prem infrastructures. - * When you are looking for a fully managed service without code-first or tutorial-guided approaches, as 'agents-towards-production' focuses heavily on hands-on tutorials and end-to-end guide creation. - * If your specific AI agent workload does not align with the foundational deployment patterns covered (containerization, AWS Bedrock, Ollama on-prem solutions, Runpod GPU deployment), other tools may, - other_remarks_and_conditions_of_use_or_nonuse_examples_with_links_or_code_snippets_e.g_github_issues__pull_requests__branch_names_etc_that_affect_anyoftheabove_can_be_cited_if_pertinent. ## Common questions ### What is the difference between agentdojo and agents-towards-production? agentdojo: A Dynamic Environment to Evaluate Prompt Injection Attacks and Defenses for LLM Agents. agents-towards-production: End-to-end, code-first tutorials for building production-grade GenAI agents. See the comparison table for live GitHub stats and shared categories. ### When should I choose agentdojo over agents-towards-production? Choose agentdojo over agents-towards-production when agentdojo is primarily Python; agents-towards-production is Jupyter Notebook; License: agentdojo is MIT, agents-towards-production is Other; 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; Also covers Evaluation & Observability; 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 agents-towards-production over agentdojo? Choose agents-towards-production over agentdojo when agents-towards-production is primarily Jupyter Notebook; agentdojo is Python; License: agents-towards-production is Other, agentdojo is MIT; Tags unique to agents-towards-production: agent-framework, agentic-ai, deployment, genai; * When you aim to deploy AI agents using cloud services such as AWS Bedrock AgentCore Runtime, where automatic infrastructure management and standardized communication patterns are key. ### When should I avoid 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 agents-towards-production? * If your enterprise strictly forbids using cloud services; this tool emphasizes both cloud and on-prem deployment strategies but may not fit entirely on-prem infrastructures. * When you are looking for a fully managed service without code-first or tutorial-guided approaches, as 'agents-towards-production' focuses heavily on hands-on tutorials and end-to-end guide creation. * If your specific AI agent workload does not align with the foundational deployment patterns covered (containerization, AWS Bedrock, Ollama on-prem solutions, Runpod GPU deployment), other tools may, other_remarks_and_conditions_of_use_or_nonuse_examples_with_links_or_code_snippets_e.g_github_issues__pull_requests__branch_names_etc_that_affect_anyoftheabove_can_be_cited_if_pertinent. ### Is agentdojo or agents-towards-production more popular on GitHub? agents-towards-production has more GitHub stars (20,953 vs 659). Stars measure visibility, not whether either tool fits your constraints. ### Are agentdojo and agents-towards-production open source? Yes - both are open-source projects on GitHub (agentdojo: MIT, agents-towards-production: Other). ### Where can I find alternatives to agentdojo or agents-towards-production? GraphCanon lists graph-backed alternatives at [agentdojo alternatives](/tools/ethz-spylab-agentdojo/alternatives) and [agents-towards-production alternatives](/tools/nirdiamant-agents-towards-production/alternatives) ([agentdojo markdown twin](/tools/ethz-spylab-agentdojo/alternatives.md), [agents-towards-production markdown twin](/tools/nirdiamant-agents-towards-production/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/ethz-spylab-agentdojo-vs-nirdiamant-agents-towards-production.md) mirrors this page for agents and LLM crawlers, with the same stats table and FAQ answers. ### Which is better maintained, agentdojo or agents-towards-production? agentdojo: Steady. agents-towards-production: 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 agents-towards-production? GraphCanon publishes per-repo trust reports with dated maintenance, provenance, and scan summaries: [agentdojo trust report](/tools/ethz-spylab-agentdojo/trust); [agents-towards-production trust report](/tools/nirdiamant-agents-towards-production/trust). --- **Machine-readable endpoints** - JSON: [`/api/graphcanon/graph?tool=ethz-spylab-agentdojo`](/api/graphcanon/graph?tool=ethz-spylab-agentdojo) - 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/_