Getting it into your agent
One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.
npx skills add yaojingang/yao-geo-skills --skill yao-geo-comparison-buildergit clone --depth 1 https://github.com/yaojingang/yao-geo-skillsWrote this? Show the measurements
A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.
[](https://agentmods.dev/skills/yaojingang/yao-geo-skills/yao-geo-comparison-builder)<a href="https://agentmods.dev/skills/yaojingang/yao-geo-skills/yao-geo-comparison-builder"><img src="https://agentmods.dev/badge/skills/yaojingang/yao-geo-skills/yao-geo-comparison-builder/github.svg" alt="Measured on agentmods" height="20"></a>Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.
<a href="https://agentmods.dev/skills/yaojingang/yao-geo-skills/yao-geo-comparison-builder"><img src="https://agentmods.dev/badge/skills/yaojingang/yao-geo-skills/yao-geo-comparison-builder.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector pass
What it costs to keep this loaded
Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5.1 | $0.00105 | $0.02202 |
| Opus 5 | $0.00053 | $0.01101 |
| Sonnet 5 | $0.00021 | $0.00440 |
| Haiku 4.5 | $0.00011 | $0.00220 |
Grade A, and why
yao-geo-comparison-builder scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 13d ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
How it starts
The opening of the file, as written. The whole thing — 101 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Yao GEO Comparison Builder
使用场景
- 生成目标品牌与竞品、传统方案、自建方案之间的 GEO 对比内容。
- 生产商业决策类内容、品牌替代方案页、选型页、FAQ 页、专题页和销售辅助材料。
- 回答国内 AI 用户常见问题:A 和 B 怎么选、某类产品有哪些替代方案、什么场景下目标品牌更适合。
不适用场景
- 只做全景诊断、AI 答案采样或机会地图;应改用
yao-geo-panorama-audit。 - 只做页面技术诊断、标题优化、榜单文章、旧文改造或后端归因。
- 没有可核验来源,却要求输出市场份额、客户数量、技术领先、价格最低等事实结论。
必要输入
- 目标品牌知识库、官网、产品页、价格页、案例、认证、帮助中心或销售资料。
- 比较对象范围:竞品品牌、同类方案、传统方案、自建方案。
- 目标关键词、用户场景、决策维度、允许引用来源、禁用词和合规边界。
- 输出约束:默认中文简体、白底报告、四格式交付;如 Word 表格较多,必须启用 DOCX 布局后处理。
必读资料
references/research-foundation.mdreferences/comparison-method.mdreferences/real-data-acquisition.mdreferences/systematic-report-framework.mdreferences/cn-platform-adaptation.mdreferences/evidence-and-fairness.mdreferences/artifact-layout.mdreferences/quality-gates.md
执行流程
- 确定比较口径:目标品牌 vs 竞品、目标品牌 vs 传统方案、目标品牌 vs 自建方案;不得把不同口径混在一张结论里。
- 声明真实数据获取模式:公共网页、用户文件、授权连接器/API、AI 平台采样或仅用户已给资料;不得越权读取登录后、付费、内部系统或个人数据。
- 建立来源台账并做访问验证:官网、产品目录、价格页、帮助中心、案例、公开文档和用户提供资料;每条关键判断绑定来源 ID、访问方式、访问日期、动态性和置信边界。
- 建立系统化维度模型:至少覆盖业务适配、功能适配、数据与 AI 准备度、集成兼容、实施成熟度、总拥有成本、治理合规安全、可靠性运营、生态与支持、本地化、迁移退出、GEO 可提取性。
- 把维度分为共享维度和差异化维度;共享维度保证可比,差异化维度承接目标品牌优势,所有差异化判断必须落到证据。
- 生成开头直接答案:说明什么情况下目标品牌更适合,什么情况下其他方案也可作为参考,并列出当前结论不能覆盖的采购、合规、数据和本地化边界。
- 输出完整报告模块:执行摘要、测试场景、真实数据获取说明、比较口径、决策维度模型、核心能力对比、证据与权衡对比、方案评分矩阵、来源质量分级、来源访问验证、风险与治理地图、国内 AI 平台适配、品牌段落、场景建议、落地核验清单、FAQ、来源清单、合规边界、自检记录。
- 生成品牌段落:每段必须包含主体、判断结论、证据锚点、适用边界和下一步核验项。
- 生成 FAQ:覆盖判断型、比较型、场景型、价格型、实施型、数据获取型、避坑型问题,并在关键问题回流目标品牌证据。
- 生成国内 AI 平台适配:千问与 Kimi 强化来源、长表和证据链,豆包与元宝强化简明结论和下一步清单,DeepSeek 强化场景 -> 约束 -> 能力 -> 证据 -> 权衡 -> 建议的因果链。
- 输出四格式:Word、PDF、HTML、Markdown;四者必须来自同一内容结构。HTML 可视化报告遵循 Kami 长文档风格:暖米纸底、ivory 内容面、油墨蓝强调、serif 标题、sans 正文,并包含固定目录栏。
- 运行布局门禁:HTML/PDF 检查 A4、Kami 色板、表格边框、右边距、固定目录、锚点和移动端横向滚动;Word 检查 A4、左右页边距、每张表
tblGrid总宽和正文可用宽度。 - 自 review 并修复:先检查真实数据访问边界、系统维度完整性、事实、同口径、公平表达、来源绑定、四格式存在、排版溢出、表格边框、行距、HTML 固定目录和可访问性,再交付。
What ships with it
29 files beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.
- agents/interface.yaml 1.8 KB
- evals/expected_artifacts.json 1.3 KB
- evals/failure_cases.md 672 B
- evals/quality_cases.json 1.9 KB
- evals/rubric.md 836 B
- evals/trigger_cases.json 431 B
- examples/hubspot-cn-demo/build_hubspot_cn_demo.py 49 KB runs code
- examples/hubspot-cn-demo/hubspot-cn-comparison-report.docx 29 KB
- examples/hubspot-cn-demo/hubspot-cn-comparison-report.html 38 KB
- examples/hubspot-cn-demo/hubspot-cn-comparison-report.md 28 KB
- examples/hubspot-cn-demo/hubspot-cn-comparison-report.pdf 334 KB
- examples/hubspot-cn-demo/quality-report.json 9.6 KB
- examples/hubspot-cn-demo/report_input.json 1.2 KB
- examples/hubspot-cn-demo/source-verification.json 4.2 KB
- examples/hubspot-cn-demo/sources.json 4.2 KB
- examples/README.md 1.5 KB
- manifest.json 808 B
- references/artifact-layout.md 2.6 KB
- references/cn-platform-adaptation.md 540 B
- references/comparison-method.md 2.3 KB
- references/evidence-and-fairness.md 1006 B
- references/quality-gates.md 2.7 KB
- references/real-data-acquisition.md 3.0 KB
- references/research-foundation.md 2.5 KB
- references/systematic-report-framework.md 4.5 KB
- reports/artifact-design-profile.md 947 B
- reports/output-risk-profile.md 1.1 KB
- scripts/check_docx_layout.py 7.7 KB runs code
- templates/brief-template.md 1.2 KB
What this file has done since we first saw it
Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.
- 13d ago First seen · 101 lines · 105 tokens per session scan A 7f99c93a525d
yao-geo-comparison-builder is a skill published in the GitHub repository yaojingang/yao-geo-skills (742 stars, last pushed 1mo ago), licensed MIT. It adds 105 tokens to every session and 2,202 once invoked, about $0.0005 per session on Opus 5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-30.
Other skills, from other repositories
pipefy-process-intelligence
Use this skill when the user wants to analyze an existing pipe for improvement opportunities — automation gaps, manual bottlenecks, missing AI agents, field conditions, or adjacent processes. Acts as a process analyst: investigates, diagnoses, and improves the pipe in progressive rounds — each round delivers visible…
c
OpenPaw coordinator — routes requests to skills, manages memory, knows what's installed. Use /c for any task.
-21risk-automation
Automate 21risk tasks via Rube MCP (Composio). Always search tools first for current schemas.
-2chat-automation
Automate 2chat tasks via Rube MCP (Composio). Always search tools first for current schemas.
ably-automation
Automate Ably tasks via Rube MCP (Composio). Always search tools first for current schemas.
abstract-automation
Automate Abstract tasks via Rube MCP (Composio). Always search tools first for current schemas.