--- title: "awesome-prompts vs Agent-Reach" type: "comparison" canonical_url: "https://www.graphcanon.com/compare/ai-boost-awesome-prompts-vs-panniantong-agent-reach" tools: ["ai-boost-awesome-prompts", "panniantong-agent-reach"] --- # awesome-prompts vs Agent-Reach *GraphCanon updated Jul 11, 2026* ## Verdict Pick awesome-prompts when license: awesome-prompts is GPL-3.0, Agent-Reach is MIT; pick Agent-Reach when license: Agent-Reach is MIT, awesome-prompts is GPL-3.0. [awesome-prompts](https://awesomegpt.vip) reports 8.4k GitHub stars, 798 forks, and 35 open issues, last pushed Jul 11, 2026. [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 [awesome-prompts's repository](https://github.com/ai-boost/awesome-prompts) and [Agent-Reach's repository](https://github.com/Panniantong/Agent-Reach). | | [awesome-prompts](/tools/ai-boost-awesome-prompts.md) | [Agent-Reach](/tools/panniantong-agent-reach.md) | | --- | --- | --- | | Tagline | Curated list of chatgpt prompts from the top-rated GPTs in the GPTs Store. Prompt Engineering, prompt attack & prompt protect. Advanced Prompt Engineering papers. | Give your AI agent eyes to see the entire internet. Read & search Twitter, Reddit, YouTube, GitHub, Bilibili, XiaoHongShu — one CLI, zero API fees. | | Stars | 8,440 | 54,715 | | Forks | 798 | 4,509 | | Open issues | 35 | 144 | | Language | - | Python | | Adopt for | - | - | | Persona | - | - | | Runtime | - | - | | License | GPL-3.0 | MIT | | Categories | LLM Frameworks | AI Agents, Developer Tools, LLM Frameworks | ## Trust and health _Sourced signals - not a safety guarantee. No winner column._ | | [awesome-prompts](/tools/ai-boost-awesome-prompts.md) | [Agent-Reach](/tools/panniantong-agent-reach.md) | | --- | --- | --- | | Open issues (now) | 35 | 144 | | Security scan | No lockfile | No MCP manifest | | Full report | [trust report](/tools/ai-boost-awesome-prompts/trust.md) | [trust report](/tools/panniantong-agent-reach/trust.md) | ## Choose when ### Choose awesome-prompts if… - License: awesome-prompts is GPL-3.0, Agent-Reach is MIT. - Tags unique to awesome-prompts: awesome, awesome-list, chatgpt, gpt4. - More recently updated (last pushed Jul 11, 2026). ### Choose Agent-Reach if… - License: Agent-Reach is MIT, awesome-prompts is GPL-3.0. - Tags unique to Agent-Reach: agent-infrastructure, ai-agent, ai-search, automation. - Also covers AI Agents, Developer Tools. ## When NOT to use awesome-prompts - 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 awesome-prompts and Agent-Reach? awesome-prompts: Curated list of chatgpt prompts from the top-rated GPTs in the GPTs Store. Prompt Engineering, prompt attack & prompt protect. Advanced Prompt Engineering papers.. 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 awesome-prompts over Agent-Reach? Choose awesome-prompts over Agent-Reach when License: awesome-prompts is GPL-3.0, Agent-Reach is MIT; Tags unique to awesome-prompts: awesome, awesome-list, chatgpt, gpt4; More recently updated (last pushed Jul 11, 2026). ### When should I choose Agent-Reach over awesome-prompts? Choose Agent-Reach over awesome-prompts when License: Agent-Reach is MIT, awesome-prompts is GPL-3.0; Tags unique to Agent-Reach: agent-infrastructure, ai-agent, ai-search, automation; Also covers AI Agents, Developer Tools. ### When should I avoid awesome-prompts? 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 awesome-prompts or Agent-Reach more popular on GitHub? Agent-Reach has more GitHub stars (54,715 vs 8,440). Stars measure visibility, not whether either tool fits your constraints. ### Are awesome-prompts and Agent-Reach open source? Yes - both are open-source projects on GitHub (awesome-prompts: GPL-3.0, Agent-Reach: MIT). ### Where can I find alternatives to awesome-prompts or Agent-Reach? GraphCanon lists graph-backed alternatives at [awesome-prompts alternatives](/tools/ai-boost-awesome-prompts/alternatives) and [Agent-Reach alternatives](/tools/panniantong-agent-reach/alternatives) ([awesome-prompts markdown twin](/tools/ai-boost-awesome-prompts/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/ai-boost-awesome-prompts-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, awesome-prompts or Agent-Reach? awesome-prompts: Very active. 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 awesome-prompts and Agent-Reach? GraphCanon publishes per-repo trust reports with dated maintenance, provenance, and scan summaries: [awesome-prompts trust report](/tools/ai-boost-awesome-prompts/trust); [Agent-Reach trust report](/tools/panniantong-agent-reach/trust). --- **Machine-readable endpoints** - JSON: [`/api/graphcanon/graph?tool=ai-boost-awesome-prompts`](/api/graphcanon/graph?tool=ai-boost-awesome-prompts) - 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/_