--- title: "agent-learning-kit vs agent-opt" type: "comparison" canonical_url: "https://www.graphcanon.com/compare/future-agi-agent-learning-kit-vs-future-agi-agent-opt" tools: ["future-agi-agent-learning-kit", "future-agi-agent-opt"] --- # agent-learning-kit vs agent-opt *GraphCanon updated Aug 4, 2026* ## Verdict 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; pick agent-opt if agent-opt is tailored for teams that require automated optimization of AI workflows and support for continuous integration/continuous delivery (CI/CD), relying on Python and specific library dependencies. [agent-learning-kit](https://futureagi.com) reports 118 GitHub stars, 43 forks, and 6 open issues, last pushed Aug 1, 2026. [agent-opt](https://app.futureagi.com) has 71 stars, 7 forks, and 0 open issues, last pushed Jun 30, 2026. Figures are from public GitHub metadata via [agent-learning-kit's repository](https://github.com/future-agi/agent-learning-kit) and [agent-opt's repository](https://github.com/future-agi/agent-opt). | | [agent-learning-kit](/tools/future-agi-agent-learning-kit.md) | [agent-opt](/tools/future-agi-agent-opt.md) | | --- | --- | --- | | Tagline | Evaluation Framework for all your AI related Workflows | Open Source Library for Automated Optimization of AI Agent Workflows | | Stars | 118 | 71 | | Forks | 43 | 7 | | Open issues | 6 | 0 | | Language | Python | Python | | 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. | Agent-opt is tailored for teams that require automated optimization of AI workflows and support for continuous integration/continuous delivery (CI/CD), relying on Python and specific library dependencies. | | Persona | - | - | | Runtime | - | - | | License | Apache-2.0 | Apache-2.0 | | Categories | Evaluation & Observability | AI Agents, Evaluation & Observability | ## Trust and health _Sourced signals - not a safety guarantee. No winner column._ | | [agent-learning-kit](/tools/future-agi-agent-learning-kit.md) | [agent-opt](/tools/future-agi-agent-opt.md) | | --- | --- | --- | | Maintenance | Very active (96%) | Steady (60%) | | Days since push | 0d | 35d | | Open issues (now) | 6 | 0 | | Full report | [trust report](/tools/future-agi-agent-learning-kit/trust.md) | [trust report](/tools/future-agi-agent-opt/trust.md) | ## Shared compatibility - **Python**: [agent-learning-kit](/tools/future-agi-agent-learning-kit.md) - Python runtime; [agent-opt](/tools/future-agi-agent-opt.md) - Python runtime ## 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. ## Decision facts: agent-opt - **Adopt for:** Agent-opt is tailored for teams that require automated optimization of AI workflows and support for continuous integration/continuous delivery (CI/CD), relying on Python and specific library dependencies. ## Choose when ### Choose agent-learning-kit if… - Tags unique to agent-learning-kit: ci-cd, ml. - When you need comprehensive evaluation of your AI models including faithfulness checks using DeBERTa NLI model installed. - More GitHub stars (118 vs 71) - visibility, not fit. ### Choose agent-opt if… - Tags unique to agent-opt: agent, aioptimization, automation, cicd. - Also covers AI Agents. - - When your project needs seamless CI/CD integration alongside automated optimization ## 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. ## When NOT to use agent-opt - - If your project does not require Python or if it cannot meet the specific requirement of having Python ≥ 3.10 - - In scenarios where CI/CD integration is not a priority for your AI workflow optimization ## Common questions ### What is the difference between agent-learning-kit and agent-opt? agent-learning-kit: Evaluation Framework for all your AI related Workflows. agent-opt: Open Source Library for Automated Optimization of AI Agent Workflows. See the comparison table for live GitHub stats and shared categories. ### When should I choose agent-learning-kit over agent-opt? Choose agent-learning-kit over agent-opt when Tags unique to agent-learning-kit: ci-cd, ml; When you need comprehensive evaluation of your AI models including faithfulness checks using DeBERTa NLI model installed; More GitHub stars (118 vs 71) - visibility, not fit. ### When should I choose agent-opt over agent-learning-kit? Choose agent-opt over agent-learning-kit when Tags unique to agent-opt: agent, aioptimization, automation, cicd; Also covers AI Agents; - When your project needs seamless CI/CD integration alongside automated optimization. ### 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. ### When should I avoid agent-opt? - If your project does not require Python or if it cannot meet the specific requirement of having Python ≥ 3.10 - In scenarios where CI/CD integration is not a priority for your AI workflow optimization ### Is agent-learning-kit or agent-opt more popular on GitHub? agent-learning-kit has more GitHub stars (118 vs 71). Stars measure visibility, not whether either tool fits your constraints. ### Are agent-learning-kit and agent-opt open source? Yes - both are open-source projects on GitHub (agent-learning-kit: Apache-2.0, agent-opt: Apache-2.0). ### Where can I find alternatives to agent-learning-kit or agent-opt? GraphCanon lists graph-backed alternatives at [agent-learning-kit alternatives](/tools/future-agi-agent-learning-kit/alternatives) and [agent-opt alternatives](/tools/future-agi-agent-opt/alternatives) ([agent-learning-kit markdown twin](/tools/future-agi-agent-learning-kit/alternatives.md), [agent-opt markdown twin](/tools/future-agi-agent-opt/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/future-agi-agent-learning-kit-vs-future-agi-agent-opt.md) mirrors this page for agents and LLM crawlers, with the same stats table and FAQ answers. ### Which is better maintained, agent-learning-kit or agent-opt? agent-learning-kit: Very active. agent-opt: 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 agent-learning-kit and agent-opt? GraphCanon publishes per-repo trust reports with dated maintenance, provenance, and scan summaries: [agent-learning-kit trust report](/tools/future-agi-agent-learning-kit/trust); [agent-opt trust report](/tools/future-agi-agent-opt/trust). --- **Machine-readable endpoints** - JSON: [`/api/graphcanon/graph?tool=future-agi-agent-learning-kit`](/api/graphcanon/graph?tool=future-agi-agent-learning-kit) - 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/_