--- title: "chatgpt-plugin-eval vs Agent-Reach" type: "comparison" canonical_url: "https://www.graphcanon.com/compare/llm-platform-security-chatgpt-plugin-eval-vs-panniantong-agent-reach" tools: ["llm-platform-security-chatgpt-plugin-eval", "panniantong-agent-reach"] --- # chatgpt-plugin-eval vs Agent-Reach *GraphCanon updated Jul 11, 2026* ## Verdict Pick chatgpt-plugin-eval when chatgpt-plugin-eval is primarily HTML; Agent-Reach is Python; pick Agent-Reach when agent-Reach is primarily Python; chatgpt-plugin-eval is HTML. [chatgpt-plugin-eval](https://llm-platform-security.github.io/chatgpt-plugin-eval/) reports 29 GitHub stars, 7 forks, and 1 open issues, last pushed Jul 29, 2024. [Agent-Reach](https://github.com/Panniantong/Agent-Reach) has 55k stars, 4.5k forks, and 144 open issues, last pushed Jul 10, 2026. Figures are from public GitHub metadata via [chatgpt-plugin-eval's repository](https://github.com/llm-platform-security/chatgpt-plugin-eval) and [Agent-Reach's repository](https://github.com/Panniantong/Agent-Reach). | | [chatgpt-plugin-eval](/tools/llm-platform-security-chatgpt-plugin-eval.md) | [Agent-Reach](/tools/panniantong-agent-reach.md) | | --- | --- | --- | | Tagline | LLM Platform Security: Applying a Systematic Evaluation Framework to OpenAI's ChatGPT Plugins | Give your AI agent eyes to see the entire internet. Read & search Twitter, Reddit, YouTube, GitHub, Bilibili, XiaoHongShu — one CLI, zero API fees. | | Stars | 29 | 54,715 | | Forks | 7 | 4,509 | | Open issues | 1 | 144 | | Language | HTML | Python | | Adopt for | - | - | | Persona | - | - | | Runtime | - | - | | License | - | MIT | | Categories | Evaluation & Observability, Inference & Serving, LLM Frameworks | AI Agents, Developer Tools, LLM Frameworks | ## Trust and health _Sourced signals - not a safety guarantee. No winner column._ | | [chatgpt-plugin-eval](/tools/llm-platform-security-chatgpt-plugin-eval.md) | [Agent-Reach](/tools/panniantong-agent-reach.md) | | --- | --- | --- | | Maintenance | Dormant (18%) | Very active (96%) | | Days since push | 712d | 0d | | Open issues (now) | 1 | 144 | | Owner type | Organization | User | | Security scan | No lockfile | No MCP manifest | | Full report | [trust report](/tools/llm-platform-security-chatgpt-plugin-eval/trust.md) | [trust report](/tools/panniantong-agent-reach/trust.md) | ## Choose when ### Choose chatgpt-plugin-eval if… - chatgpt-plugin-eval is primarily HTML; Agent-Reach is Python. - Tags unique to chatgpt-plugin-eval: chatgpt, chatgpt-plugins, llm, llm-platform. - Also covers Evaluation & Observability, Inference & Serving. ### Choose Agent-Reach if… - Agent-Reach is primarily Python; chatgpt-plugin-eval is HTML. - Tags unique to Agent-Reach: agent-infrastructure, ai-agent, ai-search, automation. - Also covers AI Agents, Developer Tools. ## When NOT to use chatgpt-plugin-eval - Last GitHub push was 712 days ago (dormant maintenance, Jul 29, 2024). Validate activity before betting a new project on chatgpt-plugin-eval. - Evaluation & Observability: Defer heavyweight eval infra only until you have real traffic - never skip it once users depend on answers. - Inference & Serving: Self-hosting rarely beats a hosted API on cost until you have steady, high-volume traffic. - LLM Frameworks: Avoid a framework for a single prompt-and-retrieve call; the abstraction can cost more than it saves. ## 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. ## Common questions ### What is the difference between chatgpt-plugin-eval and Agent-Reach? chatgpt-plugin-eval: LLM Platform Security: Applying a Systematic Evaluation Framework to OpenAI's ChatGPT Plugins. 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.. See the comparison table for live GitHub stats and shared categories. ### When should I choose chatgpt-plugin-eval over Agent-Reach? Choose chatgpt-plugin-eval over Agent-Reach when chatgpt-plugin-eval is primarily HTML; Agent-Reach is Python; Tags unique to chatgpt-plugin-eval: chatgpt, chatgpt-plugins, llm, llm-platform; Also covers Evaluation & Observability, Inference & Serving. ### When should I choose Agent-Reach over chatgpt-plugin-eval? Choose Agent-Reach over chatgpt-plugin-eval when Agent-Reach is primarily Python; chatgpt-plugin-eval is HTML; Tags unique to Agent-Reach: agent-infrastructure, ai-agent, ai-search, automation; Also covers AI Agents, Developer Tools. ### When should I avoid chatgpt-plugin-eval? Last GitHub push was 712 days ago (dormant maintenance, Jul 29, 2024). Validate activity before betting a new project on chatgpt-plugin-eval. Evaluation & Observability: Defer heavyweight eval infra only until you have real traffic - never skip it once users depend on answers. Inference & Serving: Self-hosting rarely beats a hosted API on cost until you have steady, high-volume traffic. LLM Frameworks: Avoid a framework for a single prompt-and-retrieve call; the abstraction can cost more than it saves. ### 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. ### Is chatgpt-plugin-eval or Agent-Reach more popular on GitHub? Agent-Reach has more GitHub stars (54,715 vs 29). Stars measure visibility, not whether either tool fits your constraints. ### Are chatgpt-plugin-eval and Agent-Reach open source? Yes - both are open-source projects on GitHub. ### Where can I find alternatives to chatgpt-plugin-eval or Agent-Reach? GraphCanon lists graph-backed alternatives at [chatgpt-plugin-eval alternatives](/tools/llm-platform-security-chatgpt-plugin-eval/alternatives) and [Agent-Reach alternatives](/tools/panniantong-agent-reach/alternatives) ([chatgpt-plugin-eval markdown twin](/tools/llm-platform-security-chatgpt-plugin-eval/alternatives.md), [Agent-Reach markdown twin](/tools/panniantong-agent-reach/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/llm-platform-security-chatgpt-plugin-eval-vs-panniantong-agent-reach.md) mirrors this page for agents and LLM crawlers, with the same stats table and FAQ answers. ### Which is better maintained, chatgpt-plugin-eval or Agent-Reach? chatgpt-plugin-eval: Dormant. Agent-Reach: 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 chatgpt-plugin-eval and Agent-Reach? GraphCanon publishes per-repo trust reports with dated maintenance, provenance, and scan summaries: [chatgpt-plugin-eval trust report](/tools/llm-platform-security-chatgpt-plugin-eval/trust); [Agent-Reach trust report](/tools/panniantong-agent-reach/trust). --- **Machine-readable endpoints** - JSON: [`/api/graphcanon/graph?tool=llm-platform-security-chatgpt-plugin-eval`](/api/graphcanon/graph?tool=llm-platform-security-chatgpt-plugin-eval) - 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/_