--- title: "hypertunity vs code-review-graph" type: "comparison" canonical_url: "https://www.graphcanon.com/compare/gdikov-hypertunity-vs-tirth8205-code-review-graph" tools: ["gdikov-hypertunity", "tirth8205-code-review-graph"] --- # hypertunity vs code-review-graph *GraphCanon updated Jul 11, 2026* ## Verdict Pick hypertunity when license: hypertunity is Apache-2.0, code-review-graph is MIT; pick code-review-graph when license: code-review-graph is MIT, hypertunity is Apache-2.0. [hypertunity](https://hypertunity.readthedocs.io) reports 137 GitHub stars, 10 forks, and 0 open issues, last pushed Jan 26, 2020. [code-review-graph](https://code-review-graph.com) has 19k stars, 2.1k forks, and 185 open issues, last pushed Jun 14, 2026. Figures are from public GitHub metadata via [hypertunity's repository](https://github.com/gdikov/hypertunity) and [code-review-graph's repository](https://github.com/tirth8205/code-review-graph). | | [hypertunity](/tools/gdikov-hypertunity.md) | [code-review-graph](/tools/tirth8205-code-review-graph.md) | | --- | --- | --- | | Tagline | A toolset for black-box hyperparameter optimisation. | Local-first code intelligence graph for MCP and CLI. Builds a persistent map of your codebase so AI coding tools read only what matters, with benchmarked context reductions on reviews and large-repo w | | Stars | 137 | 19,416 | | Forks | 10 | 2,078 | | Open issues | 0 | 185 | | Language | Python | Python | | Adopt for | - | - | | Persona | - | - | | Runtime | - | - | | License | Apache-2.0 | MIT | | Categories | Evaluation & Observability | Developer Tools, Evaluation & Observability, LLM Frameworks | ## Trust and health _Sourced signals - not a safety guarantee. No winner column._ | | [hypertunity](/tools/gdikov-hypertunity.md) | [code-review-graph](/tools/tirth8205-code-review-graph.md) | | --- | --- | --- | | Maintenance | Dormant (18%) | Active (82%) | | Days since push | 2358d | 26d | | Open issues (now) | 0 | 185 | | Security scan | No lockfile | No MCP manifest | | Full report | [trust report](/tools/gdikov-hypertunity/trust.md) | [trust report](/tools/tirth8205-code-review-graph/trust.md) | ## Choose when ### Choose hypertunity if… - License: hypertunity is Apache-2.0, code-review-graph is MIT. - Tags unique to hypertunity: bayesian-optimization, gpyopt, hyperparameter-optimization, python. - Leaner open-issue backlog (0). ### Choose code-review-graph if… - License: code-review-graph is MIT, hypertunity is Apache-2.0. - Tags unique to code-review-graph: ai-coding, claude, claude-code, code-review. - Also covers Developer Tools, LLM Frameworks. ## When NOT to use hypertunity - Last GitHub push was 2358 days ago (dormant maintenance, Jan 26, 2020). Validate activity before betting a new project on hypertunity. - Evaluation & Observability: Defer heavyweight eval infra only until you have real traffic - never skip it once users depend on answers. ## When NOT to use code-review-graph - Developer Tools: A gateway is overkill when you're pinned to a single provider and model. - Evaluation & Observability: Defer heavyweight eval infra only until you have real traffic - never skip it once users depend on answers. - LLM Frameworks: Avoid a framework for a single prompt-and-retrieve call; the abstraction can cost more than it saves. ## Common questions ### What is the difference between hypertunity and code-review-graph? hypertunity: A toolset for black-box hyperparameter optimisation.. code-review-graph: Local-first code intelligence graph for MCP and CLI. Builds a persistent map of your codebase so AI coding tools read only what matters, with benchmarked context reductions on reviews and large-repo w. See the comparison table for live GitHub stats and shared categories. ### When should I choose hypertunity over code-review-graph? Choose hypertunity over code-review-graph when License: hypertunity is Apache-2.0, code-review-graph is MIT; Tags unique to hypertunity: bayesian-optimization, gpyopt, hyperparameter-optimization, python; Leaner open-issue backlog (0). ### When should I choose code-review-graph over hypertunity? Choose code-review-graph over hypertunity when License: code-review-graph is MIT, hypertunity is Apache-2.0; Tags unique to code-review-graph: ai-coding, claude, claude-code, code-review; Also covers Developer Tools, LLM Frameworks. ### When should I avoid hypertunity? Last GitHub push was 2358 days ago (dormant maintenance, Jan 26, 2020). Validate activity before betting a new project on hypertunity. Evaluation & Observability: Defer heavyweight eval infra only until you have real traffic - never skip it once users depend on answers. ### When should I avoid code-review-graph? Developer Tools: A gateway is overkill when you're pinned to a single provider and model. Evaluation & Observability: Defer heavyweight eval infra only until you have real traffic - never skip it once users depend on answers. LLM Frameworks: Avoid a framework for a single prompt-and-retrieve call; the abstraction can cost more than it saves. ### Is hypertunity or code-review-graph more popular on GitHub? code-review-graph has more GitHub stars (19,416 vs 137). Stars measure visibility, not whether either tool fits your constraints. ### Are hypertunity and code-review-graph open source? Yes - both are open-source projects on GitHub (hypertunity: Apache-2.0, code-review-graph: MIT). ### Where can I find alternatives to hypertunity or code-review-graph? GraphCanon lists graph-backed alternatives at [hypertunity alternatives](/tools/gdikov-hypertunity/alternatives) and [code-review-graph alternatives](/tools/tirth8205-code-review-graph/alternatives) ([hypertunity markdown twin](/tools/gdikov-hypertunity/alternatives.md), [code-review-graph markdown twin](/tools/tirth8205-code-review-graph/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/gdikov-hypertunity-vs-tirth8205-code-review-graph.md) mirrors this page for agents and LLM crawlers, with the same stats table and FAQ answers. ### Which is better maintained, hypertunity or code-review-graph? hypertunity: Dormant. code-review-graph: 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 hypertunity and code-review-graph? GraphCanon publishes per-repo trust reports with dated maintenance, provenance, and scan summaries: [hypertunity trust report](/tools/gdikov-hypertunity/trust); [code-review-graph trust report](/tools/tirth8205-code-review-graph/trust). --- **Machine-readable endpoints** - JSON: [`/api/graphcanon/graph?tool=gdikov-hypertunity`](/api/graphcanon/graph?tool=gdikov-hypertunity) - 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/_