--- title: "Agent-Reach vs Learning-Prompt" type: "comparison" canonical_url: "https://www.graphcanon.com/compare/panniantong-agent-reach-vs-thinkingjimmy-learning-prompt" tools: ["panniantong-agent-reach", "thinkingjimmy-learning-prompt"] --- # Agent-Reach vs Learning-Prompt *GraphCanon updated Jul 11, 2026* ## Verdict Pick Agent-Reach when agent-Reach is primarily Python; Learning-Prompt is CSS; pick Learning-Prompt when learning-Prompt is primarily CSS; Agent-Reach is Python. [Agent-Reach](https://github.com/Panniantong/Agent-Reach) reports 55k GitHub stars, 4.5k forks, and 144 open issues, last pushed Jul 10, 2026. [Learning-Prompt](https://learningprompt.wiki) has 5.3k stars, 396 forks, and 16 open issues, last pushed Sep 17, 2023. Figures are from public GitHub metadata via [Agent-Reach's repository](https://github.com/Panniantong/Agent-Reach) and [Learning-Prompt's repository](https://github.com/thinkingjimmy/Learning-Prompt). | | [Agent-Reach](/tools/panniantong-agent-reach.md) | [Learning-Prompt](/tools/thinkingjimmy-learning-prompt.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. | Free prompt engineering online course. ChatGPT and Midjourney tutorials are now included! | | Stars | 54,715 | 5,319 | | Forks | 4,509 | 396 | | Open issues | 144 | 16 | | Language | Python | CSS | | Adopt for | - | - | | Persona | - | - | | Runtime | - | - | | License | MIT | Other | | Categories | LLM Frameworks, 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) | [Learning-Prompt](/tools/thinkingjimmy-learning-prompt.md) | | --- | --- | --- | | Maintenance | Very active (96%) | Dormant (18%) | | Days since push | 0d | 1028d | | Open issues (now) | 144 | 16 | | Security scan | No MCP manifest | No lockfile | | Full report | [trust report](/tools/panniantong-agent-reach/trust.md) | [trust report](/tools/thinkingjimmy-learning-prompt/trust.md) | ## Choose when ### Choose Agent-Reach if… - Agent-Reach is primarily Python; Learning-Prompt is CSS. - License: Agent-Reach is MIT, Learning-Prompt is Other. - Tags unique to Agent-Reach: agent-infrastructure, ai-search, bilibili, claude-code. - Also covers AI Agents. ### Choose Learning-Prompt if… - Learning-Prompt is primarily CSS; Agent-Reach is Python. - License: Learning-Prompt is Other, Agent-Reach is MIT. - Tags unique to Learning-Prompt: prompt-toolkit, css, prompt, prompt-engineering. ## When NOT to use Agent-Reach - LLM Frameworks: Avoid a framework for a single prompt-and-retrieve call; the abstraction can cost more than it saves. - 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. ## When NOT to use Learning-Prompt - Last GitHub push was 1029 days ago (dormant maintenance, Sep 17, 2023). Validate activity before betting a new project on Learning-Prompt. - LLM Frameworks: Avoid a framework for a single prompt-and-retrieve call; the abstraction can cost more than it saves. - 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 Learning-Prompt? 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.. Learning-Prompt: Free prompt engineering online course. ChatGPT and Midjourney tutorials are now included!. See the comparison table for live GitHub stats and shared categories. ### When should I choose Agent-Reach over Learning-Prompt? Choose Agent-Reach over Learning-Prompt when Agent-Reach is primarily Python; Learning-Prompt is CSS; License: Agent-Reach is MIT, Learning-Prompt is Other; Tags unique to Agent-Reach: agent-infrastructure, ai-search, bilibili, claude-code; Also covers AI Agents. ### When should I choose Learning-Prompt over Agent-Reach? Choose Learning-Prompt over Agent-Reach when Learning-Prompt is primarily CSS; Agent-Reach is Python; License: Learning-Prompt is Other, Agent-Reach is MIT; Tags unique to Learning-Prompt: prompt-toolkit, css, prompt, prompt-engineering. ### When should I avoid Agent-Reach? LLM Frameworks: Avoid a framework for a single prompt-and-retrieve call; the abstraction can cost more than it saves. 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. ### When should I avoid Learning-Prompt? Last GitHub push was 1029 days ago (dormant maintenance, Sep 17, 2023). Validate activity before betting a new project on Learning-Prompt. LLM Frameworks: Avoid a framework for a single prompt-and-retrieve call; the abstraction can cost more than it saves. Developer Tools: A gateway is overkill when you're pinned to a single provider and model. ### Is Agent-Reach or Learning-Prompt more popular on GitHub? Agent-Reach has more GitHub stars (54,715 vs 5,319). Stars measure visibility, not whether either tool fits your constraints. ### Are Agent-Reach and Learning-Prompt open source? Yes - both are open-source projects on GitHub (Agent-Reach: MIT, Learning-Prompt: Other). ### Where can I find alternatives to Agent-Reach or Learning-Prompt? GraphCanon lists graph-backed alternatives at [Agent-Reach alternatives](/tools/panniantong-agent-reach/alternatives) and [Learning-Prompt alternatives](/tools/thinkingjimmy-learning-prompt/alternatives) ([Agent-Reach markdown twin](/tools/panniantong-agent-reach/alternatives.md), [Learning-Prompt markdown twin](/tools/thinkingjimmy-learning-prompt/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-thinkingjimmy-learning-prompt.md) mirrors this page for agents and LLM crawlers, with the same stats table and FAQ answers. ### Which is better maintained, Agent-Reach or Learning-Prompt? Agent-Reach: Very active. Learning-Prompt: Dormant. 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 Learning-Prompt? GraphCanon publishes per-repo trust reports with dated maintenance, provenance, and scan summaries: [Agent-Reach trust report](/tools/panniantong-agent-reach/trust); [Learning-Prompt trust report](/tools/thinkingjimmy-learning-prompt/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/_