--- title: "agentdojo vs ChainForge" type: "comparison" canonical_url: "https://www.graphcanon.com/compare/ethz-spylab-agentdojo-vs-ianarawjo-chainforge" tools: ["ethz-spylab-agentdojo", "ianarawjo-chainforge"] --- # agentdojo vs ChainForge *GraphCanon updated Aug 20, 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 ChainForge if web-based visual programming tool for prompt testing on LLMs; supports local installation and Docker for advanced feature access. [agentdojo](https://agentdojo.spylab.ai/) reports 716 GitHub stars, 188 forks, and 41 open issues, last pushed Jun 2, 2026. [ChainForge](https://chainforge.ai/docs) has 3.0k stars, 256 forks, and 70 open issues, last pushed Jun 10, 2026. Figures are from public GitHub metadata via [agentdojo's repository](https://github.com/ethz-spylab/agentdojo) and [ChainForge's repository](https://github.com/ianarawjo/ChainForge). | | [agentdojo](/tools/ethz-spylab-agentdojo.md) | [ChainForge](/tools/ianarawjo-chainforge.md) | | --- | --- | --- | | Tagline | A Dynamic Environment to Evaluate Prompt Injection Attacks and Defenses for LLM Agents | An open-source visual programming environment for battle-testing prompts to LLMs. | | Stars | 716 | 3,027 | | Forks | 188 | 256 | | Open issues | 41 | 70 | | Language | Python | TypeScript | | Adopt for | AgentDojo serves as a benchmarking environment to evaluate security attacks, like prompt injection, and defenses for Large Language Model (LLM) agents. | Web-based visual programming tool for prompt testing on LLMs; supports local installation and Docker for advanced feature access. | | Persona | - | - | | Runtime | - | - | | License | MIT | MIT | | Categories | AI Agents, Evaluation & Observability | Evaluation & Observability, LLM Frameworks | ## Trust and health _Sourced signals - not a safety guarantee. No winner column._ | | [agentdojo](/tools/ethz-spylab-agentdojo.md) | [ChainForge](/tools/ianarawjo-chainforge.md) | | --- | --- | --- | | Days since push | 63d | 70d | | Open issues (now) | 41 | 70 | | Stars delta | Unknown | +14 (30d) | | Open issues delta | Unknown | +1 (30d) | | Owner type | Organization | User | | Full report | [trust report](/tools/ethz-spylab-agentdojo/trust.md) | [trust report](/tools/ianarawjo-chainforge/trust.md) | ## Shared compatibility - **Python**: [agentdojo](/tools/ethz-spylab-agentdojo.md) - Python runtime; [ChainForge](/tools/ianarawjo-chainforge.md) - Python runtime ## 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: ChainForge - **Adopt for:** Web-based visual programming tool for prompt testing on LLMs; supports local installation and Docker for advanced feature access. ## Choose when ### Choose agentdojo if… - agentdojo is primarily Python; ChainForge is TypeScript. - 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, prompt-injection, security. - Also covers AI Agents. - AgentDojo serves as a benchmarking environment to evaluate security attacks, like prompt injection, and defenses for Large Language Model (LLM) agents. ### Choose ChainForge if… - ChainForge is primarily TypeScript; agentdojo is Python. - Tags unique to ChainForge: ai, evaluation, llmops, prompt-engineering. - Also covers LLM Frameworks. - ChainForge ships Docker support for self-hosted deployment. - Need extensive features beyond web limitations ## 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 ChainForge - Looking for a solution without local setup or Docker support - Prefer not managing API keys via environment variable configuration ## Common questions ### What is the difference between agentdojo and ChainForge? agentdojo: A Dynamic Environment to Evaluate Prompt Injection Attacks and Defenses for LLM Agents. ChainForge: An open-source visual programming environment for battle-testing prompts to LLMs.. See the comparison table for live GitHub stats and shared categories. ### When should I choose agentdojo over ChainForge? Choose agentdojo over ChainForge when agentdojo is primarily Python; ChainForge is TypeScript; 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, prompt-injection, security; Also covers AI Agents; 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 ChainForge over agentdojo? Choose ChainForge over agentdojo when ChainForge is primarily TypeScript; agentdojo is Python; Tags unique to ChainForge: ai, evaluation, llmops, prompt-engineering; Also covers LLM Frameworks; ChainForge ships Docker support for self-hosted deployment; Need extensive features beyond web limitations. ### 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 ChainForge? Looking for a solution without local setup or Docker support Prefer not managing API keys via environment variable configuration ### Is agentdojo or ChainForge more popular on GitHub? ChainForge has more GitHub stars (3,027 vs 716). Stars measure visibility, not whether either tool fits your constraints. ### Are agentdojo and ChainForge open source? Yes - both are open-source projects on GitHub (agentdojo: MIT, ChainForge: MIT). ### Where can I find alternatives to agentdojo or ChainForge? GraphCanon lists graph-backed alternatives at [agentdojo alternatives](/tools/ethz-spylab-agentdojo/alternatives) and [ChainForge alternatives](/tools/ianarawjo-chainforge/alternatives) ([agentdojo markdown twin](/tools/ethz-spylab-agentdojo/alternatives.md), [ChainForge markdown twin](/tools/ianarawjo-chainforge/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-ianarawjo-chainforge.md) mirrors this page for agents and LLM crawlers, with the same stats table and FAQ answers. ### Which is better maintained, agentdojo or ChainForge? agentdojo: Steady. ChainForge: Steady. 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 ChainForge? GraphCanon publishes per-repo trust reports with dated maintenance, provenance, and scan summaries: [agentdojo trust report](/tools/ethz-spylab-agentdojo/trust); [ChainForge trust report](/tools/ianarawjo-chainforge/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/_