--- title: "AutoPrompt vs Agent-Reach" type: "comparison" canonical_url: "https://www.graphcanon.com/compare/eladlev-autoprompt-vs-panniantong-agent-reach" tools: ["eladlev-autoprompt", "panniantong-agent-reach"] --- # AutoPrompt vs Agent-Reach *GraphCanon updated Jul 11, 2026* ## Verdict Pick AutoPrompt when license: AutoPrompt is Apache-2.0, Agent-Reach is MIT; pick Agent-Reach when license: Agent-Reach is MIT, AutoPrompt is Apache-2.0. [AutoPrompt](https://github.com/Eladlev/AutoPrompt) reports 3.0k GitHub stars, 263 forks, and 23 open issues, last pushed Dec 2, 2025. [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 [AutoPrompt's repository](https://github.com/Eladlev/AutoPrompt) and [Agent-Reach's repository](https://github.com/Panniantong/Agent-Reach). | | [AutoPrompt](/tools/eladlev-autoprompt.md) | [Agent-Reach](/tools/panniantong-agent-reach.md) | | --- | --- | --- | | Tagline | A framework for prompt tuning using Intent-based Prompt Calibration | Give your AI agent eyes to see the entire internet. Read & search Twitter, Reddit, YouTube, GitHub, Bilibili, XiaoHongShu — one CLI, zero API fees. | | Stars | 2,988 | 54,715 | | Forks | 263 | 4,509 | | Open issues | 23 | 144 | | Language | Python | Python | | Adopt for | - | - | | Persona | - | - | | Runtime | - | - | | License | Apache-2.0 | MIT | | Categories | LLM Frameworks | LLM Frameworks, AI Agents, Developer Tools | ## Trust and health _Sourced signals - not a safety guarantee. No winner column._ | | [AutoPrompt](/tools/eladlev-autoprompt.md) | [Agent-Reach](/tools/panniantong-agent-reach.md) | | --- | --- | --- | | Maintenance | Slowing (36%) | Very active (96%) | | Days since push | 220d | 0d | | Open issues (now) | 23 | 144 | | Security scan | No lockfile | No MCP manifest | | Full report | [trust report](/tools/eladlev-autoprompt/trust.md) | [trust report](/tools/panniantong-agent-reach/trust.md) | ## Choose when ### Choose AutoPrompt if… - License: AutoPrompt is Apache-2.0, Agent-Reach is MIT. - Tags unique to AutoPrompt: synthetic-dataset-generation, python, prompt-tuning, prompt-engineering. - Leaner open-issue backlog (23). ### Choose Agent-Reach if… - License: Agent-Reach is MIT, AutoPrompt is Apache-2.0. - Tags unique to Agent-Reach: agent-infrastructure, ai-search, bilibili, claude-code. - Also covers AI Agents, Developer Tools. ## When NOT to use AutoPrompt - Last GitHub push was 221 days ago (slowing maintenance, Dec 2, 2025). Validate activity before betting a new project on AutoPrompt. - 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 - 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. ## Common questions ### What is the difference between AutoPrompt and Agent-Reach? AutoPrompt: A framework for prompt tuning using Intent-based Prompt Calibration. 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 AutoPrompt over Agent-Reach? Choose AutoPrompt over Agent-Reach when License: AutoPrompt is Apache-2.0, Agent-Reach is MIT; Tags unique to AutoPrompt: synthetic-dataset-generation, python, prompt-tuning, prompt-engineering; Leaner open-issue backlog (23). ### When should I choose Agent-Reach over AutoPrompt? Choose Agent-Reach over AutoPrompt when License: Agent-Reach is MIT, AutoPrompt is Apache-2.0; Tags unique to Agent-Reach: agent-infrastructure, ai-search, bilibili, claude-code; Also covers AI Agents, Developer Tools. ### When should I avoid AutoPrompt? Last GitHub push was 221 days ago (slowing maintenance, Dec 2, 2025). Validate activity before betting a new project on AutoPrompt. 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? 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. ### Is AutoPrompt or Agent-Reach more popular on GitHub? Agent-Reach has more GitHub stars (54,715 vs 2,988). Stars measure visibility, not whether either tool fits your constraints. ### Are AutoPrompt and Agent-Reach open source? Yes - both are open-source projects on GitHub (AutoPrompt: Apache-2.0, Agent-Reach: MIT). ### Where can I find alternatives to AutoPrompt or Agent-Reach? GraphCanon lists graph-backed alternatives at [AutoPrompt alternatives](/tools/eladlev-autoprompt/alternatives) and [Agent-Reach alternatives](/tools/panniantong-agent-reach/alternatives) ([AutoPrompt markdown twin](/tools/eladlev-autoprompt/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/eladlev-autoprompt-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, AutoPrompt or Agent-Reach? AutoPrompt: Slowing. 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 AutoPrompt and Agent-Reach? GraphCanon publishes per-repo trust reports with dated maintenance, provenance, and scan summaries: [AutoPrompt trust report](/tools/eladlev-autoprompt/trust); [Agent-Reach trust report](/tools/panniantong-agent-reach/trust). --- **Machine-readable endpoints** - JSON: [`/api/graphcanon/graph?tool=eladlev-autoprompt`](/api/graphcanon/graph?tool=eladlev-autoprompt) - 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/_