Agent skill

Yao Geo Effect Monitor

by yaojingang in yaojingang/yao-geo-skills

A skill your agent uses when designing a GEO Signal Monitor, AI answer monitoring system, citation tracking plan, brand-fact correction loop, GEO monthly report, alert rules, dashboard fields, or…

MITAuto-check passedDevOps & Cloud

Install Yao Geo Effect Monitor

skills CLI
$ npx skills add yaojingang/yao-geo-skills --skill yao-geo-effect-monitor -a claude-code

Project install by default; add -g for ~/.claude/skills/.

GitHub CLI
$ gh skill install yaojingang/yao-geo-skills yao-geo-effect-monitor --agent claude-code

Project scope by default; add --scope user for a personal install. Needs GitHub CLI 2.90.0 or later (public preview).

Manual copy
$ git clone --depth 1 https://github.com/yaojingang/yao-geo-skills.git skills-src && mkdir -p .claude/skills && cp -r skills-src/skills/yao-geo-effect-monitor .claude/skills/yao-geo-effect-monitor && rm -rf skills-src

Use ~/.claude/skills/ instead of .claude/skills for a personal install. The folder must contain SKILL.md.

Claude Code skills documentation · loads skills from .claude/skills/

Facts

Skill name
yao-geo-effect-monitor
GitHub stars
871
Token cost
~799 tokens
SKILL.md length
141 words
Files
39 (incl. references)
Skills in repo
24
Repo updated
First seen
Licence
MIT

At a glance

A skill your agent uses when designing a GEO Signal Monitor, AI answer monitoring system, citation tracking plan, brand-fact correction loop, GEO monthly report, alert rules, dashboard fields, or…

  • Works in 12 steps: 统一监测对象:品牌名、别名、产品名、竞品名、官网域名、公众号、文档站、媒体稿、社区… → 做权威参考扫描:先收集官网、官方文档、投资者/监管/标准资料、研究论文和可信第三方… → 做公司测试场景发现:从公开事实提炼产品线、客户场景、AI/新功能、价格边界、集成生… → …
  • Designing a GEO Signal Monitor
  • SKILL.md covers When To Use, Do Not Use, Required Inputs and Required Reading, plus 3 more sections
  • Instructions only: no scripts, shell commands, URLs or credentials in SKILL.md

What it does

Yao Geo Effect Monitor is an agent skill from yaojingang/yao-geo-skills. Use when designing a GEO Signal Monitor, AI answer monitoring system, citation tracking plan, brand-fact correction loop, GEO monthly report, alert rules, dashboard fields, or cautious attribution framework for DeepSeek, Doubao, Qianwen, Kimi, Tencent Yuanbao, and similar answer engines.

Its SKILL.md is about 800 tokens, which your agent loads only when the skill is triggered. The skill folder holds 43 other files, including reference files (for example `agents/interface.yaml`, `evals/expected_artifacts.json` and `evals/failure_cases.md`).

It sits in DevOps & Cloud, covering Monitoring and alerting, Product analytics and Citation management. It works with DeepSeek and Kimi. The repository describes itself as: An open-source Skill collection for GEO content and workflows, continuously updated. The licence is MIT.

When your agent uses it

  • Designing a GEO Signal Monitor
  • AI answer monitoring system
  • Citation tracking plan
  • Brand-fact correction loop

Example prompts

  • “/yao-geo-effect-monitor”

Workflow steps

12 steps, taken from the first numbered list in SKILL.md.

  1. 统一监测对象:品牌名、别名、产品名、竞品名、官网域名、公众号、文档站、媒体稿、社区和视频号。
  2. 做权威参考扫描:先收集官网、官方文档、投资者/监管/标准资料、研究论文和可信第三方来源,建立来源账本,再进入分析。
  3. 做公司测试场景发现:从公开事实提炼产品线、客户场景、AI/新功能、价格边界、集成生态、中文资料可得性和竞品/替代品,再映射到 Prompt 组。
  4. 建立 Prompt 库:按 推荐、比较、替代、价格、风险、品牌验证、场景问法 七组组织,每组保留核心问法、长尾问法、对照问法和追问问法。
  5. 建立五平台独立采样口径:DeepSeek 记录结论稳定性和证据链;豆包记录口语问答和图文输出;千问记录引用源和追问;Kimi 记录深度研究与长文引用;元宝记录微信生态来源和公众号内容表现。
  6. 选择数据接入模式:按 合成回放、人工真实样本、授权 API/连接器、浏览器辅助合规采样、CRM/转化数据导入 分级,先确认权限、频率、证据和隐私边界。
  7. 执行采样并记录环境:平台、时间、设备、账号状态、地区、联网状态、Prompt 版本、答案原文、引用链接、截图、导出文件、接口日志或其他可审计证据。
  8. 做真实数据可用性判定:没有原始答案、截图/导出、采样环境和来源记录时,不得把结果标成真实采样;只能标成合成样例、推断或待复核。
  9. 按六层模型分析:覆盖可见性、事实性、证据性、稳定性、竞争性和治理/归因,不允许只输出单维度指标。
  10. 计算指标:品牌出现率、候选率、推荐率、排序、竞品出现率、负面表述率、描述准确率、事实错误率、引用召回率、引用准确率、引用类型覆盖、答案稳定性。
  11. 做引用源追踪:区分官网、公众号、媒体、百科、社区、视频号、文档站、评测站、聚合页和竞品页面,并判断引用是否支持对应说法。
  12. 做谨慎归因:设置基线窗口、观察窗口、处理 Prompt、对照 Prompt、竞品对照和外部事件记录;默认使用 观察相关,只有证据充分才提高归因置信度。

What it can do on your machine

Read from SKILL.md and the folder at commit d21bfc1. It shows what the files ask for, not the result of running them.

  • Tool permissions

    Pre-approves nothing: there is no allowed-tools line, so your agent's usual permission prompts apply.

    From allowed-tools in the SKILL.md frontmatter.

  • Runs code

    No scripts in the folder and no shell commands in SKILL.md.

    From the folder's file list and the shell code blocks in SKILL.md.

  • Network

    Links to these hosts (documentation or services it may open):

    • x.com

    From URLs in SKILL.md, links to its own repository left out.

  • Credentials

    Names no API keys, tokens, secrets or passwords.

    From names ending in _API_KEY, _TOKEN, _SECRET, _KEY or _PASSWORD in SKILL.md.

Context cost

Yao Geo Effect Monitor loads about 799 tokens when it runs, and up to ~6.1k if it reads all its reference files. Until then it costs about 78 tokens; SKILL.md has 141 words of instructions outside code blocks.

Always · name and description, kept in context so the agent knows when to use it
~78
When it runs · the whole SKILL.md, loaded when a task matches
~799
With references · SKILL.md plus every file in references/, read only if the agent opens them
~6.1k

Estimates: characters ÷ 4, the usual rule of thumb; real counts depend on the model's tokenizer. Scripts and assets cost tokens only if the agent reads them.

Safety

Auto-check passed

The automated check found no risky patterns in SKILL.md.

Automated static check — not a guarantee. Review scripts before installing. It scans the text of SKILL.md for risky patterns (piping downloads into a shell, reading credential files, hidden Unicode, destructive commands); files beside SKILL.md are not scanned.

SKILL.md

The full file from yaojingang/yao-geo-skills at commit d21bfc1, republished under its MIT licence (© yaojingang). 141 words, ~799 tokens.

Download SKILL.mdSave it as .claude/skills/yao-geo-effect-monitor/SKILL.md (or your agent's skills folder). This skill also uses 38 other files; get the full folder from GitHub.
name
yao-geo-effect-monitor
description
Use when designing a GEO Signal Monitor, AI answer monitoring system, citation tracking plan, brand-fact correction loop, GEO monthly report, alert rules, dashboard fields, or cautious attribution framework for DeepSeek, Doubao, Qianwen, Kimi, Tencent Yuanbao, and similar answer engines.
<!--
Copyright © 2026 姚金刚. All rights reserved.
Project: yao-geo-effect-monitor
Created by: 姚金刚
Date: 2026-05-16
X: https://x.com/yaojingang
-->

Yao GEO Effect Monitor

When To Use

  • 为 GEO 长期运营建立 AI 答案监测、引用源追踪、品牌表述纠偏和效果归因闭环。
  • 面向客户月报、内容迭代、页面优化、外部信源建设或品牌事实纠偏输出后端监测方案。
  • 覆盖国内平台:DeepSeek、豆包、千问、Kimi、元宝,并为每个平台建立独立采样口径。
  • 默认交付 Word、PDF、HTML、Markdown 四格式报告,要求白底、表格边框、对齐、换行和页面溢出可控。

Do Not Use

  • 一次性 GEO 战略诊断,优先用 yao-geo-panorama-audit。
  • 只做 CRM 字段、表单和转化追踪,不需要 AI 答案监测,优先用 yao-geo-tracking。
  • 需要绕过平台限制、批量滥采、模拟真人登录或违反服务条款。
  • 只需要内容生产或文章改写,不需要监测闭环。

Required Inputs

最少输入:品牌名、目标平台、监测目标或报告周期。可选输入包括意图拓词 Prompt 库、竞品名、目标页面、内容清单、基线数据、发布日期、更新记录、CRM 或转化数据、外部信源清单、历史 AI 答案样本、设备、账号、地区、联网状态和合规限制。

Required Reading

  • references/research-basis.md
  • references/monitoring-method.md
  • references/cn-platform-sampling.md
  • references/data-acquisition.md
  • references/metrics-attribution.md
  • references/correction-loop.md
  • references/dashboard-data-model.md
  • references/report-completeness-model.md
  • references/artifact-layout.md
  • references/quality-gates.md

Workflow

  1. 统一监测对象:品牌名、别名、产品名、竞品名、官网域名、公众号、文档站、媒体稿、社区和视频号。
  2. 做权威参考扫描:先收集官网、官方文档、投资者/监管/标准资料、研究论文和可信第三方来源,建立来源账本,再进入分析。
  3. 做公司测试场景发现:从公开事实提炼产品线、客户场景、AI/新功能、价格边界、集成生态、中文资料可得性和竞品/替代品,再映射到 Prompt 组。
  4. 建立 Prompt 库:按 推荐、比较、替代、价格、风险、品牌验证、场景问法 七组组织,每组保留核心问法、长尾问法、对照问法和追问问法。
  5. 建立五平台独立采样口径:DeepSeek 记录结论稳定性和证据链;豆包记录口语问答和图文输出;千问记录引用源和追问;Kimi 记录深度研究与长文引用;元宝记录微信生态来源和公众号内容表现。
  6. 选择数据接入模式:按 合成回放、人工真实样本、授权 API/连接器、浏览器辅助合规采样、CRM/转化数据导入 分级,先确认权限、频率、证据和隐私边界。
  7. 执行采样并记录环境:平台、时间、设备、账号状态、地区、联网状态、Prompt 版本、答案原文、引用链接、截图、导出文件、接口日志或其他可审计证据。
  8. 做真实数据可用性判定:没有原始答案、截图/导出、采样环境和来源记录时,不得把结果标成真实采样;只能标成合成样例、推断或待复核。
  9. 按六层模型分析:覆盖可见性、事实性、证据性、稳定性、竞争性和治理/归因,不允许只输出单维度指标。
  10. 计算指标:品牌出现率、候选率、推荐率、排序、竞品出现率、负面表述率、描述准确率、事实错误率、引用召回率、引用准确率、引用类型覆盖、答案稳定性。
  11. 做引用源追踪:区分官网、公众号、媒体、百科、社区、视频号、文档站、评测站、聚合页和竞品页面,并判断引用是否支持对应说法。
  12. 做谨慎归因:设置基线窗口、观察窗口、处理 Prompt、对照 Prompt、竞品对照和外部事件记录;默认使用 观察相关,只有证据充分才提高归因置信度。
  13. 生成纠偏闭环:把错误事实、缺失证据、弱页面、负面表达和引用缺口映射到知识库、内容改造、页面设计、外部发布或销售口径。
  14. 输出系统、详细、完整的报告:必须包含来源账本、数据接入声明、分析边界、指标体系、平台差异、引用质量、风险治理、纠偏路线图、仪表盘/API 和附录。

Output Contract

  • GEO 后端监测方案
  • 权威参考与来源账本
  • 五平台采样口径
  • 真实数据接入模式与证据等级
  • 公司测试场景发现表
  • 监测 Prompt 库
  • 指标体系与计算口径
  • 引用源追踪规则
  • 答案差异分析与谨慎归因
  • 纠偏任务表
  • 月报模板
  • 阈值告警规则
  • 复盘节奏
  • 仪表盘字段说明
  • 数据库表结构和 API 草案
  • 治理、合规、数据质量和置信度说明
  • 真实数据可用性判断:可用、部分可用、不可用、合成演示
  • 附录:Prompt 全表、指标字典、来源账本、采样记录字段
  • 风险、合规与置信度说明
  • 默认四件套:Word、PDF、HTML、Markdown

Validation Checklist

  • 四个示例或交付文件真实存在,并能被 file、文本抽取或浏览器打开校验。
  • HTML、Word、PDF、Markdown 来源一致,章节和关键表格一致。
  • 报告为白底,表格边框完整,列宽、换行、行距和页边距不溢出。
  • 五个平台都有独立采样口径,不混用一个平台结论。
  • 必须明确 sample_mode 和证据等级;没有可审计原始样本时,不得声称拿到真实平台数据。
  • 不只看品牌出现率,也计算候选率、推荐率、描述准确率和引用质量。
  • 引用质量同时检查召回和准确,不把引用链接数量等同于可信度。
  • 归因必须有基线、观察窗口、对照 Prompt、竞品对照和混杂因素记录。
  • 采样方式不违反平台服务条款;批量自动化必须写频率、权限和人工复核边界。

© yaojingang, MIT. Rendered from Markdown: HTML in the file is shown as text, images as links, and headings moved down two levels. Raw file

Files

SKILL.md and 38 other files (references) in skills/yao-geo-effect-monitor of yaojingang/yao-geo-skills.

  • SKILL.md
  • agents/interface.yaml
  • evals/expected_artifacts.json
  • evals/failure_cases.md
  • evals/rubric.md
  • evals/trigger_cases.json
  • examples/README.md
  • examples/hubspot-cn-signal-monitor/html-head.html
  • examples/hubspot-cn-signal-monitor/hubspot-cn-effect-monitor.docx
  • examples/hubspot-cn-signal-monitor/hubspot-cn-effect-monitor.html
  • examples/hubspot-cn-signal-monitor/hubspot-cn-effect-monitor.md
  • examples/hubspot-cn-signal-monitor/hubspot-cn-effect-monitor.pdf
  • examples/hubspot-cn-signal-monitor/quality-report.json
  • examples/hubspot-cn-signal-monitor/report_input.json
  • examples/synthetic-demo/README.md
  • examples/synthetic-demo/html-head.html
  • … and 23 more

Open the folder on GitHubat commit d21bfc1

Compare with similar skills

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Works with

Questions about Yao Geo Effect Monitor

What does Yao Geo Effect Monitor do?

A skill your agent uses when designing a GEO Signal Monitor, AI answer monitoring system, citation tracking plan, brand-fact correction loop, GEO monthly report, alert rules, dashboard fields, or…. Yao Geo Effect Monitor is an agent skill from yaojingang/yao-geo-skills. Use when designing a GEO Signal Monitor, AI answer monitoring system, citation tracking plan, brand-fact correction loop, GEO monthly report, alert rules, dashboard fields, or cautious attribution framework for DeepSeek, Doubao, Qianwen, Kimi, Tencent Yuanbao, and similar answer engines.

When should I use Yao Geo Effect Monitor?

Yao Geo Effect Monitor fits situations like: designing a GEO Signal Monitor; AI answer monitoring system; citation tracking plan; brand-fact correction loop.

How do I install Yao Geo Effect Monitor in Claude Code?

Run `npx skills add yaojingang/yao-geo-skills --skill yao-geo-effect-monitor -a claude-code`. Or copy the skill folder (skills/yao-geo-effect-monitor in yaojingang/yao-geo-skills) into .claude/skills/yao-geo-effect-monitor in your project. Claude Code loads it when a task matches its description.

How do I install Yao Geo Effect Monitor in Codex?

Run `npx skills add yaojingang/yao-geo-skills --skill yao-geo-effect-monitor -a codex`. Or copy the skill folder (skills/yao-geo-effect-monitor in yaojingang/yao-geo-skills) into .agents/skills/yao-geo-effect-monitor in your project. Codex loads it when a task matches its description.

Can I use Yao Geo Effect Monitor in Cursor, Gemini CLI or GitHub Copilot?

Cursor, Gemini CLI, GitHub Copilot and OpenCode also load SKILL.md folders. With the skills CLI, run `npx skills add yaojingang/yao-geo-skills --skill yao-geo-effect-monitor -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/yao-geo-effect-monitor, .gemini/skills/yao-geo-effect-monitor, .github/skills/yao-geo-effect-monitor and .opencode/skills/yao-geo-effect-monitor in your project.

What does Yao Geo Effect Monitor need to run?

SKILL.md names no scripts, command-line tools or credentials: Yao Geo Effect Monitor is instructions for the agent only.

Does Yao Geo Effect Monitor access the network?

SKILL.md names 1 domain. As links in the text: x.com. This is read from the text; nothing was executed.

Is Yao Geo Effect Monitor safe to install?

Our automated static check of SKILL.md found no risky patterns, such as piping downloads into a shell, reading credential files or hidden Unicode. It is not a guarantee. Review the folder before installing.

What licence does Yao Geo Effect Monitor use?

Yao Geo Effect Monitor is published under the MIT licence (the repository's licence). It allows redistribution, so the full SKILL.md is shown on this page.

How many tokens does Yao Geo Effect Monitor use?

About 799 tokens (SKILL.md is roughly 3.2k characters). Agents keep only the skill's name and description in context until a task matches; then they load SKILL.md in full. Its references folder adds about 5.3k tokens, read only when the agent opens those files.

What are the alternatives to Yao Geo Effect Monitor?

Skills that share tags, products or a category with Yao Geo Effect Monitor: Operate Pi Dispatch (edgehero/pi-dispatch, 179 stars), Tianji Read-Only Data Queries (msgbyte/tianji, 3.1k stars), Add React Analytics (gotempsh/temps, 833 stars) and Claude Maintain Models (Kiln-AI/Kiln, 5.2k stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.

Who maintains Yao Geo Effect Monitor?

yaojingang (a GitHub user) maintains it in yaojingang/yao-geo-skills, which has 871 GitHub stars. The repository holds 24 skills in this directory. The repository was last updated on October 1, 2026.

Source: yaojingang/yao-geo-skills on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.