--- title: "ECC vs semble" type: "comparison" canonical_url: "https://www.graphcanon.com/compare/affaan-m-ecc-vs-minishlab-semble" tools: ["affaan-m-ecc", "minishlab-semble"] --- # ECC vs semble *GraphCanon updated Jul 12, 2026* ## Verdict Pick ECC if eCC is a performance optimization system for AI agents built to enhance skills, instincts, memory, security, and development processes; pick semble if semble is a Python-based tool that facilitates fast and accurate code search for AI agents with up to 98% fewer tokens compared to traditional grep+read methods. [ECC](https://ecc.tools) reports 228k GitHub stars, 35k forks, and 93 open issues, last pushed Jul 9, 2026. [semble](https://minish.ai/packages/semble/introduction/) has 5.6k stars, 236 forks, and 8 open issues, last pushed Jul 8, 2026. Figures are from public GitHub metadata via [ECC's repository](https://github.com/affaan-m/ECC) and [semble's repository](https://github.com/MinishLab/semble). | | [ECC](/tools/affaan-m-ecc.md) | [semble](/tools/minishlab-semble.md) | | --- | --- | --- | | Tagline | The agent harness performance optimization system for AI agents | Fast and Accurate Code Search for Agents | | Stars | 228,395 | 5,581 | | Forks | 35,037 | 236 | | Open issues | 93 | 8 | | Language | JavaScript | Python | | Adopt for | ECC is a performance optimization system for AI agents built to enhance skills, instincts, memory, security, and development processes. | Semble is a Python-based tool that facilitates fast and accurate code search for AI agents with up to 98% fewer tokens compared to traditional grep+read methods. | | Persona | - | - | | Runtime | - | - | | License | MIT | MIT | | Categories | AI Agents, Developer Tools | AI Agents, Data & Retrieval | ## Trust and health _Sourced signals - not a safety guarantee. No winner column._ | | [ECC](/tools/affaan-m-ecc.md) | [semble](/tools/minishlab-semble.md) | | --- | --- | --- | | Days since push | 2d | 3d | | Open issues (now) | 93 | 8 | | Owner type | User | Organization | | Full report | [trust report](/tools/affaan-m-ecc/trust.md) | [trust report](/tools/minishlab-semble/trust.md) | ## Decision facts: ECC - **Hosting:** unknown - ECC requires JavaScript environment and is open-source, licensed under MIT. Specific setup details are not provided within repository data. - **Pricing:** freemium - Being open source with an MIT license, ECC itself is free to use, but additional features or support might incur costs outside of the core project. - **Adopt for:** ECC is a performance optimization system for AI agents built to enhance skills, instincts, memory, security, and development processes. ## Decision facts: semble - **Requirements:** Operating with Python, Semble does not require Docker for its operation. - **Adopt for:** Semble is a Python-based tool that facilitates fast and accurate code search for AI agents with up to 98% fewer tokens compared to traditional grep+read methods. ## Choose when ### Choose ECC if… - ECC is primarily JavaScript; semble is Python. - ECC requires JavaScript environment and is open-source, licensed under MIT. Specific setup details are not provided within repository data. - Pricing: Being open source with an MIT license, ECC itself is free to use, but additional features or support might incur costs outside of the core project.. - Tags unique to ECC: llm, productivity, claude, claude-code. - Also covers Developer Tools. - When you are specifically working with AI agents like Claude Code and Codex that require advanced performance tuning across multiple dimensions such as skills and memory management. ### Choose semble if… - semble is primarily Python; ECC is JavaScript. - Requirements: Operating with Python, Semble does not require Docker for its operation.. - Tags unique to semble: embeddings, agents, retrieval, mcp. - Also covers Data & Retrieval. - - Use Semble when you are specifically working with AI agents or models and require efficient, token-economical code search operations. ## When NOT to use ECC - For projects focusing solely on traditional software development workflows without AI components, ECC's specialized tools are not necessary. - In scenarios where you're working with closed-source or proprietary AI systems that do not allow for the same levels of customization as open platforms like those optimized by ECC. ## When NOT to use semble - - Avoid using Semble if your use case does not involve AI agents or the model-context-protocol (MCP). Competitor tools might offer better features tailored to non-agent-based code search. - - Not recommended in scenarios where token efficiency is not a concern, as competitors may provide more versatile functionalities without focusing on token reduction. ## Common questions ### What is the difference between ECC and semble? ECC: The agent harness performance optimization system for AI agents. semble: Fast and Accurate Code Search for Agents. See the comparison table for live GitHub stats and shared categories. ### When should I choose ECC over semble? Choose ECC over semble when ECC is primarily JavaScript; semble is Python; ECC requires JavaScript environment and is open-source, licensed under MIT. Specific setup details are not provided within repository data; Pricing: Being open source with an MIT license, ECC itself is free to use, but additional features or support might incur costs outside of the core project.; Tags unique to ECC: llm, productivity, claude, claude-code; Also covers Developer Tools; When you are specifically working with AI agents like Claude Code and Codex that require advanced performance tuning across multiple dimensions such as skills and memory management. ### When should I choose semble over ECC? Choose semble over ECC when semble is primarily Python; ECC is JavaScript; Requirements: Operating with Python, Semble does not require Docker for its operation.; Tags unique to semble: embeddings, agents, retrieval, mcp; Also covers Data & Retrieval; - Use Semble when you are specifically working with AI agents or models and require efficient, token-economical code search operations. ### When should I avoid ECC? For projects focusing solely on traditional software development workflows without AI components, ECC's specialized tools are not necessary. In scenarios where you're working with closed-source or proprietary AI systems that do not allow for the same levels of customization as open platforms like those optimized by ECC. ### When should I avoid semble? - Avoid using Semble if your use case does not involve AI agents or the model-context-protocol (MCP). Competitor tools might offer better features tailored to non-agent-based code search. - Not recommended in scenarios where token efficiency is not a concern, as competitors may provide more versatile functionalities without focusing on token reduction. ### Is ECC or semble more popular on GitHub? ECC has more GitHub stars (228,395 vs 5,581). Stars measure visibility, not whether either tool fits your constraints. ### Are ECC and semble open source? Yes - both are open-source projects on GitHub (ECC: MIT, semble: MIT). ### Where can I find alternatives to ECC or semble? GraphCanon lists graph-backed alternatives at [ECC alternatives](/tools/affaan-m-ecc/alternatives) and [semble alternatives](/tools/minishlab-semble/alternatives) ([ECC markdown twin](/tools/affaan-m-ecc/alternatives.md), [semble markdown twin](/tools/minishlab-semble/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/affaan-m-ecc-vs-minishlab-semble.md) mirrors this page for agents and LLM crawlers, with the same stats table and FAQ answers. ### Which is better maintained, ECC or semble? ECC: Very active. semble: 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 ECC and semble? GraphCanon publishes per-repo trust reports with dated maintenance, provenance, and scan summaries: [ECC trust report](/tools/affaan-m-ecc/trust); [semble trust report](/tools/minishlab-semble/trust). --- **Machine-readable endpoints** - JSON: [`/api/graphcanon/graph?tool=affaan-m-ecc`](/api/graphcanon/graph?tool=affaan-m-ecc) - 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/_