RRepoGEO

REPOGEO 报告 · LITE

the-open-engine/zeroshot

默认分支 main · commit 0b51c602 · 扫描时间 2026/6/16 22:31:26

星标 1,508 · Fork 129

AI 可见性总分
33 /100
亟需修复
品类召回
0 / 2
在所有问题中均未被推荐
规则结果
通过 2 · 警告 0 · 失败 0
客观元数据检查
AI 认识你的名字
2 / 3
直接询问时,AI 是否点名你的仓库
如何阅读这份报告

行动计划告诉你下一步要做什么——按影响力排序、可直接复制粘贴的修改。品类可见性是真正的 GEO 测试:当用户向 AI 提一个不带品牌、本应让 the-open-engine/zeroshot 浮出水面的问题时,AI 是真的推荐了你,还是推荐了你的竞品?客观检查验证 AI 引擎最先权衡的那些元数据信号。自指检查判断 AI 是否还认识你的名字。

行动计划 — 可复制粘贴的修复

3 条由 gemini-2.5-flash 生成、按优先级排序的修改。修完后请把对应条目标记为完成。

整体方向
  • highreadme#1
    Reposition the README's core value proposition

    原因:

    当前
    # zeroshot CLI
    
    > 🎉 New in v5.4: Now supports **OpenCode** CLI! Use Claude, Codex, Gemini, or OpenCode as your AI provider. Also supports **GitHub, GitLab, Jira, and Azure DevOps** as issue backends. See [Providers](#providers) and [Multi-Platform Issue Support](#multi-platform-issue-support).
    复制粘贴的修复
    # zeroshot CLI: Your Autonomous Engineering Team
    
    > Zeroshot is an open-source AI coding agent orchestration CLI that runs multi-agent workflows to autonomously implement, review, test, and verify production-grade code changes. Built for tasks where correctness matters more than speed.
    
    > 🎉 New in v5.4: Now supports **OpenCode** CLI! Use Claude, Codex, Gemini, or OpenCode as your AI provider. Also supports **GitHub, GitLab, Jira, and Azure DevOps** as issue backends. See [Providers](#providers) and [Multi-Platform Issue Support](#multi-platform-issue-support).
  • mediumreadme#2
    Add a 'Why Zeroshot?' or 'Comparison' section to the README

    原因:

    复制粘贴的修复
    ## Why Zeroshot? (vs. Generic AI Agents)
    
    While many AI agent frameworks exist (e.g., Auto-GPT, CrewAI, LangChain), Zeroshot is purpose-built as an **autonomous engineering team in a CLI** focused specifically on **production-grade code implementation, review, testing, and verification**. Unlike broader frameworks, Zeroshot emphasizes:
    
    - **Verified Changes:** Loops until changes are verified or rejected with actionable, reproducible failures, prioritizing correctness over speed.
    - **Isolated Environments:** Runs implementers and validators in isolated workspaces (local, worktree, or Docker) for robust testing.
    - **Production-Grade Focus:** Designed for tasks where the integrity and quality of the generated code are paramount.
    - **CLI-Native Experience:** Seamlessly integrates into developer workflows from the command line.
  • lowtopics#3
    Remove non-standard 'vibecoding' topic

    原因:

    当前
    agent-orchestration, agentic-workflow, ai-agent, ai-agents, autonomous-agents, claude, cli, codex, coding-assistant, developer-tools, gemini, generative-ai, github-automation, llm, llm-ops, llm-tools, multi-agent, vibecoding
    复制粘贴的修复
    agent-orchestration, agentic-workflow, ai-agent, ai-agents, autonomous-agents, claude, cli, codex, coding-assistant, developer-tools, gemini, generative-ai, github-automation, llm, llm-ops, llm-tools, multi-agent

本次扫描解析到的品类 GEO 通道:google/gemini-2.5-flash, deepseek/deepseek-v4-flash

品类可见性 — 真正的 GEO 测试

向 google/gemini-2.5-flash 提出的不带品牌问题。AI 推荐了你,还是推荐了别人?

各模型使用同一组问题 — 切换标签对比回答与排名。

召回
0 / 2
0% 的问题里出现了 the-open-engine/zeroshot
平均排名
越小越好。#1 表示首位推荐。
声量占比
0%
在所有被点名的工具中,你占了多少?
头号对手
Cursor
在 2 个问题中被推荐 1 次
竞品排行
  1. Cursor · 被推荐 1 次
  2. Continue.dev · 被推荐 1 次
  3. aider · 被推荐 1 次
  4. OpenAI API · 被推荐 1 次
  5. Anthropic API · 被推荐 1 次
  • 品类问题
    How can I automate fixing code issues using an AI agent from the command line?
    你:未被推荐
    AI 推荐顺序:
    1. Cursor
    2. Continue.dev
    3. aider
    4. OpenAI API
    5. Anthropic API
    6. GitHub Copilot CLI
    7. Cody (Sourcegraph) CLI

    AI 推荐了 7 个替代方案,却始终没点名 the-open-engine/zeroshot。这就是要补上的差距。

    查看 AI 完整回答
  • 品类问题
    Looking for a CLI tool that orchestrates multiple AI agents for verified code implementation.
    你:未被推荐
    AI 推荐顺序:
    1. Auto-GPT
    2. BabyAGI
    3. CrewAI
    4. LangChain CLI / LangServe
    5. Open Interpreter
    6. AgentOps

    AI 推荐了 6 个替代方案,却始终没点名 the-open-engine/zeroshot。这就是要补上的差距。

    查看 AI 完整回答

客观检查

针对 AI 引擎最看重的元数据信号的规则审计。

  • Metadata completeness
    pass

  • README presence
    pass

自指检查

当被直接问到你时,AI 是否还知道你的仓库存在?

  • Compared to common alternatives in this category, what is the core differentiator of the-open-engine/zeroshot?
    pass
    AI 明确点名了 the-open-engine/zeroshot

    AI 的回答可能信誓旦旦却是错的。请按事实核对:技术栈、目标人群、差异化点是不是和你实际的对得上?

  • If a team adopts the-open-engine/zeroshot in production, what risks or prerequisites should they evaluate first?
    pass
    AI 明确点名了 the-open-engine/zeroshot

    AI 的回答可能信誓旦旦却是错的。请按事实核对:技术栈、目标人群、差异化点是不是和你实际的对得上?

  • In one sentence, what problem does the repo the-open-engine/zeroshot solve, and who is the primary audience?
    pass
    AI 未点名 the-open-engine/zeroshot —— 很可能在说另一个项目

    AI 的回答可能信誓旦旦却是错的。请按事实核对:技术栈、目标人群、差异化点是不是和你实际的对得上?

嵌入你的 GEO 徽章

把这个徽章贴进 the-open-engine/zeroshot 的 README。每次重新扫描都会自动更新,并跳到最新报告——是「我在乎 AI 可发现性」最简单的公开证明。

RepoGEO badge preview实时预览
MARKDOWN(README)
[![RepoGEO](https://repogeo.com/badge/the-open-engine/zeroshot.svg)](https://repogeo.com/zh/r/the-open-engine/zeroshot)
HTML
<a href="https://repogeo.com/zh/r/the-open-engine/zeroshot"><img src="https://repogeo.com/badge/the-open-engine/zeroshot.svg" alt="RepoGEO" /></a>
Pro

订阅 Pro,解锁深度诊断

the-open-engine/zeroshot — 轻量扫描仍免费;本卡列出 Pro 相对轻量的深度额度。

  • 深度报告每月 10 次
  • 无品牌品类查询5,轻量 2
  • 优先行动项8,轻量 3