--- title: "Agent-Reach vs scikit-optimize" type: "comparison" canonical_url: "https://www.graphcanon.com/compare/panniantong-agent-reach-vs-scikit-optimize-scikit-optimize" tools: ["panniantong-agent-reach", "scikit-optimize-scikit-optimize"] --- # Agent-Reach vs scikit-optimize *GraphCanon updated Jul 11, 2026* ## Verdict Pick Agent-Reach when license: Agent-Reach is MIT, scikit-optimize is BSD-3-Clause; pick scikit-optimize when license: scikit-optimize is BSD-3-Clause, Agent-Reach is MIT. [Agent-Reach](https://github.com/Panniantong/Agent-Reach) reports 55k GitHub stars, 4.5k forks, and 144 open issues, last pushed Jul 10, 2026. [scikit-optimize](https://scikit-optimize.github.io) has 2.8k stars, 559 forks, and 318 open issues, last pushed Feb 23, 2024. Figures are from public GitHub metadata via [Agent-Reach's repository](https://github.com/Panniantong/Agent-Reach) and [scikit-optimize's repository](https://github.com/scikit-optimize/scikit-optimize). | | [Agent-Reach](/tools/panniantong-agent-reach.md) | [scikit-optimize](/tools/scikit-optimize-scikit-optimize.md) | | --- | --- | --- | | Tagline | Give your AI agent eyes to see the entire internet. Read & search Twitter, Reddit, YouTube, GitHub, Bilibili, XiaoHongShu — one CLI, zero API fees. | Sequential model-based optimization with a `scipy.optimize` interface | | Stars | 54,715 | 2,826 | | Forks | 4,509 | 559 | | Open issues | 144 | 318 | | Language | Python | Python | | Adopt for | - | - | | Persona | - | - | | Runtime | - | - | | License | MIT | BSD-3-Clause | | Categories | AI Agents, Developer Tools, LLM Frameworks | Developer Tools | ## Trust and health _Sourced signals - not a safety guarantee. No winner column._ | | [Agent-Reach](/tools/panniantong-agent-reach.md) | [scikit-optimize](/tools/scikit-optimize-scikit-optimize.md) | | --- | --- | --- | | Maintenance | Very active (96%) | Archived (8%) | | Days since push | 0d | 869d | | Archived on GitHub | No | Yes | | Open issues (now) | 144 | 318 | | Owner type | User | Organization | | Security scan | No MCP manifest | 17 low (17 low) | | Full report | [trust report](/tools/panniantong-agent-reach/trust.md) | [trust report](/tools/scikit-optimize-scikit-optimize/trust.md) | ## Choose when ### Choose Agent-Reach if… - License: Agent-Reach is MIT, scikit-optimize is BSD-3-Clause. - Tags unique to Agent-Reach: agent-infrastructure, ai-agent, ai-search, automation. - Also covers AI Agents, LLM Frameworks. ### Choose scikit-optimize if… - License: scikit-optimize is BSD-3-Clause, Agent-Reach is MIT. - Tags unique to scikit-optimize: bayesian-optimization, bayesopt, binder, hacktoberfest. ## When NOT to use Agent-Reach - AI Agents: Don't use an agent loop when a deterministic workflow would do; agents add latency, cost, and non-determinism. - Developer Tools: A gateway is overkill when you're pinned to a single provider and model. - LLM Frameworks: Avoid a framework for a single prompt-and-retrieve call; the abstraction can cost more than it saves. ## When NOT to use scikit-optimize - scikit-optimize is archived on GitHub. Prefer an active alternative unless you maintain a private fork or need a frozen dependency. - Developer Tools: A gateway is overkill when you're pinned to a single provider and model. ## Common questions ### What is the difference between Agent-Reach and scikit-optimize? Agent-Reach: Give your AI agent eyes to see the entire internet. Read & search Twitter, Reddit, YouTube, GitHub, Bilibili, XiaoHongShu — one CLI, zero API fees.. scikit-optimize: Sequential model-based optimization with a `scipy.optimize` interface. See the comparison table for live GitHub stats and shared categories. ### When should I choose Agent-Reach over scikit-optimize? Choose Agent-Reach over scikit-optimize when License: Agent-Reach is MIT, scikit-optimize is BSD-3-Clause; Tags unique to Agent-Reach: agent-infrastructure, ai-agent, ai-search, automation; Also covers AI Agents, LLM Frameworks. ### When should I choose scikit-optimize over Agent-Reach? Choose scikit-optimize over Agent-Reach when License: scikit-optimize is BSD-3-Clause, Agent-Reach is MIT; Tags unique to scikit-optimize: bayesian-optimization, bayesopt, binder, hacktoberfest. ### When should I avoid Agent-Reach? AI Agents: Don't use an agent loop when a deterministic workflow would do; agents add latency, cost, and non-determinism. Developer Tools: A gateway is overkill when you're pinned to a single provider and model. LLM Frameworks: Avoid a framework for a single prompt-and-retrieve call; the abstraction can cost more than it saves. ### When should I avoid scikit-optimize? scikit-optimize is archived on GitHub. Prefer an active alternative unless you maintain a private fork or need a frozen dependency. Developer Tools: A gateway is overkill when you're pinned to a single provider and model. ### Is Agent-Reach or scikit-optimize more popular on GitHub? Agent-Reach has more GitHub stars (54,715 vs 2,826). Stars measure visibility, not whether either tool fits your constraints. ### Are Agent-Reach and scikit-optimize open source? Yes - both are open-source projects on GitHub (Agent-Reach: MIT, scikit-optimize: BSD-3-Clause). ### Where can I find alternatives to Agent-Reach or scikit-optimize? GraphCanon lists graph-backed alternatives at [Agent-Reach alternatives](/tools/panniantong-agent-reach/alternatives) and [scikit-optimize alternatives](/tools/scikit-optimize-scikit-optimize/alternatives) ([Agent-Reach markdown twin](/tools/panniantong-agent-reach/alternatives.md), [scikit-optimize markdown twin](/tools/scikit-optimize-scikit-optimize/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/panniantong-agent-reach-vs-scikit-optimize-scikit-optimize.md) mirrors this page for agents and LLM crawlers, with the same stats table and FAQ answers. ### Which is better maintained, Agent-Reach or scikit-optimize? Agent-Reach: Very active. scikit-optimize: Archived. 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-Reach and scikit-optimize? GraphCanon publishes per-repo trust reports with dated maintenance, provenance, and scan summaries: [Agent-Reach trust report](/tools/panniantong-agent-reach/trust); [scikit-optimize trust report](/tools/scikit-optimize-scikit-optimize/trust). --- **Machine-readable endpoints** - JSON: [`/api/graphcanon/graph?tool=panniantong-agent-reach`](/api/graphcanon/graph?tool=panniantong-agent-reach) - 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/_