--- title: "jailbreak-evaluation vs agent-learning-kit" type: "comparison" canonical_url: "https://www.graphcanon.com/compare/controllability-jailbreak-evaluation-vs-future-agi-agent-learning-kit" tools: ["controllability-jailbreak-evaluation", "future-agi-agent-learning-kit"] --- # jailbreak-evaluation vs agent-learning-kit *GraphCanon updated Aug 5, 2026* ## Verdict Pick jailbreak-evaluation if jailbreak-evaluation is a Python package aimed at evaluating if AI models have been jailbroken by generating outputs that diverge from expected programming; pick agent-learning-kit if agent-learning-kit is a Python framework for evaluating AI-related workflows with modules for faithfulness assessment, embedding similarity analysis, and feedback loop integration via ChromaDB. [jailbreak-evaluation](https://arxiv.org/abs/2404.06407) reports 27 GitHub stars, 8 forks, and 0 open issues, last pushed Nov 4, 2024. [agent-learning-kit](https://futureagi.com) has 118 stars, 43 forks, and 6 open issues, last pushed Aug 1, 2026. Figures are from public GitHub metadata via [jailbreak-evaluation's repository](https://github.com/controllability/jailbreak-evaluation) and [agent-learning-kit's repository](https://github.com/future-agi/agent-learning-kit). | | [jailbreak-evaluation](/tools/controllability-jailbreak-evaluation.md) | [agent-learning-kit](/tools/future-agi-agent-learning-kit.md) | | --- | --- | --- | | Tagline | Python package for language model jailbreak evaluation | Evaluation Framework for all your AI related Workflows | | Stars | 27 | 118 | | Forks | 8 | 43 | | Open issues | 0 | 6 | | Language | Python | Python | | Adopt for | jailbreak-evaluation is a Python package aimed at evaluating if AI models have been jailbroken by generating outputs that diverge from expected programming. | Agent-learning-kit is a Python framework for evaluating AI-related workflows with modules for faithfulness assessment, embedding similarity analysis, and feedback loop integration via ChromaDB. | | Persona | - | - | | Runtime | - | - | | License | Apache-2.0 | Apache-2.0 | | Categories | Evaluation & Observability | Evaluation & Observability | ## Trust and health _Sourced signals - not a safety guarantee. No winner column._ | | [jailbreak-evaluation](/tools/controllability-jailbreak-evaluation.md) | [agent-learning-kit](/tools/future-agi-agent-learning-kit.md) | | --- | --- | --- | | Maintenance | Dormant (18%) | Very active (96%) | | Days since push | 638d | 0d | | Open issues (now) | 0 | 6 | | Full report | [trust report](/tools/controllability-jailbreak-evaluation/trust.md) | [trust report](/tools/future-agi-agent-learning-kit/trust.md) | ## Shared compatibility - **Python**: [jailbreak-evaluation](/tools/controllability-jailbreak-evaluation.md) - Python runtime; [agent-learning-kit](/tools/future-agi-agent-learning-kit.md) - Python runtime ## Decision facts: jailbreak-evaluation - **Requirements:** The tool depends on having PyTorch and FastChat installed; An API key from the OpenAI Platform is required for full functionality - **Adopt for:** jailbreak-evaluation is a Python package aimed at evaluating if AI models have been jailbroken by generating outputs that diverge from expected programming. ## Decision facts: agent-learning-kit - **Adopt for:** Agent-learning-kit is a Python framework for evaluating AI-related workflows with modules for faithfulness assessment, embedding similarity analysis, and feedback loop integration via ChromaDB. ## Choose when ### Choose jailbreak-evaluation if… - Requirements: The tool depends on having PyTorch and FastChat installed; An API key from the OpenAI Platform is required for full functionality. - Tags unique to jailbreak-evaluation: ai safety, evaluation tools, jailbreaks, language-models. - When you need to assess whether an AI model can be manipulated to produce unpredictable or unintended outcomes through specific inputs, such as jailbreaking. ### Choose agent-learning-kit if… - Tags unique to agent-learning-kit: ai-agents, ci-cd, evaluation, ml. - When you need comprehensive evaluation of your AI models including faithfulness checks using DeBERTa NLI model installed. - More GitHub stars (118 vs 27) - visibility, not fit. ## When NOT to use jailbreak-evaluation - If your project does not involve assessing the security or integrity of how an AI model responds to manipulative input techniques designed to exploit design weaknesses. - When you do not need dependencies on specific frameworks like PyTorch and FastChat, as jailbreak-evaluation requires these without automating their installation. ## When NOT to use agent-learning-kit - If your workflow does not align with the specific evaluation criteria and methods supported by agent-learning-kit. - When you seek a framework that integrates with backend systems other than those provided as optional extras, such as MongoDB or DynamoDB instead of ChromaDB. ## Common questions ### What is the difference between jailbreak-evaluation and agent-learning-kit? jailbreak-evaluation: Python package for language model jailbreak evaluation. agent-learning-kit: Evaluation Framework for all your AI related Workflows. See the comparison table for live GitHub stats and shared categories. ### When should I choose jailbreak-evaluation over agent-learning-kit? Choose jailbreak-evaluation over agent-learning-kit when Requirements: The tool depends on having PyTorch and FastChat installed; An API key from the OpenAI Platform is required for full functionality; Tags unique to jailbreak-evaluation: ai safety, evaluation tools, jailbreaks, language-models; When you need to assess whether an AI model can be manipulated to produce unpredictable or unintended outcomes through specific inputs, such as jailbreaking. ### When should I choose agent-learning-kit over jailbreak-evaluation? Choose agent-learning-kit over jailbreak-evaluation when Tags unique to agent-learning-kit: ai-agents, ci-cd, evaluation, ml; When you need comprehensive evaluation of your AI models including faithfulness checks using DeBERTa NLI model installed; More GitHub stars (118 vs 27) - visibility, not fit. ### When should I avoid jailbreak-evaluation? If your project does not involve assessing the security or integrity of how an AI model responds to manipulative input techniques designed to exploit design weaknesses. When you do not need dependencies on specific frameworks like PyTorch and FastChat, as jailbreak-evaluation requires these without automating their installation. ### When should I avoid agent-learning-kit? If your workflow does not align with the specific evaluation criteria and methods supported by agent-learning-kit. When you seek a framework that integrates with backend systems other than those provided as optional extras, such as MongoDB or DynamoDB instead of ChromaDB. ### Is jailbreak-evaluation or agent-learning-kit more popular on GitHub? agent-learning-kit has more GitHub stars (118 vs 27). Stars measure visibility, not whether either tool fits your constraints. ### Are jailbreak-evaluation and agent-learning-kit open source? Yes - both are open-source projects on GitHub (jailbreak-evaluation: Apache-2.0, agent-learning-kit: Apache-2.0). ### Where can I find alternatives to jailbreak-evaluation or agent-learning-kit? GraphCanon lists graph-backed alternatives at [jailbreak-evaluation alternatives](/tools/controllability-jailbreak-evaluation/alternatives) and [agent-learning-kit alternatives](/tools/future-agi-agent-learning-kit/alternatives) ([jailbreak-evaluation markdown twin](/tools/controllability-jailbreak-evaluation/alternatives.md), [agent-learning-kit markdown twin](/tools/future-agi-agent-learning-kit/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/controllability-jailbreak-evaluation-vs-future-agi-agent-learning-kit.md) mirrors this page for agents and LLM crawlers, with the same stats table and FAQ answers. ### Which is better maintained, jailbreak-evaluation or agent-learning-kit? jailbreak-evaluation: Dormant. agent-learning-kit: 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 jailbreak-evaluation and agent-learning-kit? GraphCanon publishes per-repo trust reports with dated maintenance, provenance, and scan summaries: [jailbreak-evaluation trust report](/tools/controllability-jailbreak-evaluation/trust); [agent-learning-kit trust report](/tools/future-agi-agent-learning-kit/trust). --- **Machine-readable endpoints** - JSON: [`/api/graphcanon/graph?tool=controllability-jailbreak-evaluation`](/api/graphcanon/graph?tool=controllability-jailbreak-evaluation) - 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/_