--- title: "agent-learning-kit vs MiroFish-Offline" type: "comparison" canonical_url: "https://www.graphcanon.com/compare/future-agi-agent-learning-kit-vs-nikmcfly-mirofish-offline" tools: ["future-agi-agent-learning-kit", "nikmcfly-mirofish-offline"] --- # agent-learning-kit vs MiroFish-Offline *GraphCanon updated Sep 20, 2026* ## Verdict Pick agent-learning-kit if agent-learning-kit is a Python-based toolkit for evaluating and simulating AI workflows, particularly suited for AI agents. It offers optional extras for specific functionalities and a TypeScript SDK for broader language; pick MiroFish-Offline if miroFish-Offline is an offline simulation and prediction engine for multi-agent systems that uses Neo4j and Ollama framework locally. [agent-learning-kit](https://futureagi.com) reports 119 GitHub stars, 44 forks, and 19 open issues, last pushed Sep 18, 2026. [MiroFish-Offline](https://x.com/nikmcfly69/status/2033147482331390328) has 2.5k stars, 659 forks, and 49 open issues, last pushed Mar 24, 2026. Figures are from public GitHub metadata via [agent-learning-kit's repository](https://github.com/future-agi/agent-learning-kit) and [MiroFish-Offline's repository](https://github.com/nikmcfly/MiroFish-Offline). | | [agent-learning-kit](/tools/future-agi-agent-learning-kit.md) | [MiroFish-Offline](/tools/nikmcfly-mirofish-offline.md) | | --- | --- | --- | | Tagline | General Purpose Evaluation and Simulation Environment for all your AI related Workflows | Offline multi-agent simulation and prediction engine with Neo4j and Ollama local stack | | Stars | 119 | 2,526 | | Forks | 44 | 659 | | Open issues | 19 | 49 | | Language | Python | Python | | Adopt for | agent-learning-kit is a Python-based toolkit for evaluating and simulating AI workflows, particularly suited for AI agents. It offers optional extras for specific functionalities and a TypeScript SDK for broader language | MiroFish-Offline is an offline simulation and prediction engine for multi-agent systems that uses Neo4j and Ollama framework locally. | | Persona | - | - | | Runtime | - | - | | License | Other | AGPL-3.0 | | Categories | AI Agents, 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) | [MiroFish-Offline](/tools/nikmcfly-mirofish-offline.md) | | --- | --- | --- | | Maintenance | Very active (96%) | Slowing (36%) | | Days since push | 0d | 179d | | Open issues (now) | 19 | 49 | | Stars delta | +1 (30d) | +58 (30d) | | Open issues delta | +13 (30d) | -1 (30d) | | Owner type | Organization | User | | Full report | [trust report](/tools/future-agi-agent-learning-kit/trust.md) | [trust report](/tools/nikmcfly-mirofish-offline/trust.md) | ## Decision facts: agent-learning-kit - **Adopt for:** agent-learning-kit is a Python-based toolkit for evaluating and simulating AI workflows, particularly suited for AI agents. It offers optional extras for specific functionalities and a TypeScript SDK for broader language ## Decision facts: MiroFish-Offline - **Requirements:** Min 16 GB RAM; Requires Docker - **Adopt for:** MiroFish-Offline is an offline simulation and prediction engine for multi-agent systems that uses Neo4j and Ollama framework locally. ## Choose when ### Choose agent-learning-kit if… - License: agent-learning-kit is Other, MiroFish-Offline is AGPL-3.0. - Tags unique to agent-learning-kit: agentic-ai, ai-agents, cicd, evaluation. - When you need a comprehensive environment for evaluating and simulating AI workflows, especially for AI agents ### Choose MiroFish-Offline if… - License: MiroFish-Offline is AGPL-3.0, agent-learning-kit is Other. - Requirements: Min 16 GB RAM; Requires Docker. - Tags unique to MiroFish-Offline: ai, multi-agent, neo4j, offline. - MiroFish-Offline ships Docker support for self-hosted deployment. - Use MiroFish-Offline when you require simulations in an offline environment to predict behaviors of multi-agent systems with local data storage options using Neo4j. ## When NOT to use agent-learning-kit - If your project strictly requires a different programming language other than Python or TypeScript - When you need a tool that is already at a mature v1 release, as agent-learning-kit is still developing its TypeScript SDK and extras ## When NOT to use MiroFish-Offline - Avoid MiroFish-Offline if real-time agent interactions are necessary as this tool operates in an offline setup. - Do not use it when your hardware limitations fall below the recommended specifications, such as less than 32 GB RAM and less than 8 cores CPU, especially for efficient LLM inference tasks. ## Common questions ### What is the difference between agent-learning-kit and MiroFish-Offline? agent-learning-kit: General Purpose Evaluation and Simulation Environment for all your AI related Workflows. MiroFish-Offline: Offline multi-agent simulation and prediction engine with Neo4j and Ollama local stack. See the comparison table for live GitHub stats and shared categories. ### When should I choose agent-learning-kit over MiroFish-Offline? Choose agent-learning-kit over MiroFish-Offline when License: agent-learning-kit is Other, MiroFish-Offline is AGPL-3.0; Tags unique to agent-learning-kit: agentic-ai, ai-agents, cicd, evaluation; When you need a comprehensive environment for evaluating and simulating AI workflows, especially for AI agents. ### When should I choose MiroFish-Offline over agent-learning-kit? Choose MiroFish-Offline over agent-learning-kit when License: MiroFish-Offline is AGPL-3.0, agent-learning-kit is Other; Requirements: Min 16 GB RAM; Requires Docker; Tags unique to MiroFish-Offline: ai, multi-agent, neo4j, offline; MiroFish-Offline ships Docker support for self-hosted deployment; Use MiroFish-Offline when you require simulations in an offline environment to predict behaviors of multi-agent systems with local data storage options using Neo4j. ### When should I avoid agent-learning-kit? If your project strictly requires a different programming language other than Python or TypeScript When you need a tool that is already at a mature v1 release, as agent-learning-kit is still developing its TypeScript SDK and extras ### When should I avoid MiroFish-Offline? Avoid MiroFish-Offline if real-time agent interactions are necessary as this tool operates in an offline setup. Do not use it when your hardware limitations fall below the recommended specifications, such as less than 32 GB RAM and less than 8 cores CPU, especially for efficient LLM inference tasks. ### Is agent-learning-kit or MiroFish-Offline more popular on GitHub? MiroFish-Offline has more GitHub stars (2,526 vs 119). Stars measure visibility, not whether either tool fits your constraints. ### Are agent-learning-kit and MiroFish-Offline open source? Yes - both are open-source projects on GitHub (agent-learning-kit: Other, MiroFish-Offline: AGPL-3.0). ### Where can I find alternatives to agent-learning-kit or MiroFish-Offline? GraphCanon lists graph-backed alternatives at [agent-learning-kit alternatives](/tools/future-agi-agent-learning-kit/alternatives) and [MiroFish-Offline alternatives](/tools/nikmcfly-mirofish-offline/alternatives) ([agent-learning-kit markdown twin](/tools/future-agi-agent-learning-kit/alternatives.md), [MiroFish-Offline markdown twin](/tools/nikmcfly-mirofish-offline/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-nikmcfly-mirofish-offline.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 MiroFish-Offline? agent-learning-kit: Very active. MiroFish-Offline: Slowing. 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 MiroFish-Offline? 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); [MiroFish-Offline trust report](/tools/nikmcfly-mirofish-offline/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/_