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aeo-system空气动力学系统

Agent Skill

aeo-system 用于查找、检索和筛选相关信息,适合在 OpenClaw 中需要根据关键词、任务场景或来源线索快速定位候选结果时使用。可结合来源仓库、安装命令和原始 README 继续核验具体用法。安装前建议确认权限范围、维护状态,以及是否会触发联网、命令执行或文件读写。

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OpenClaw

安装说明

本站只整理中文说明和来源信息,不托管安装包,也不代用户安装。

GitHub

来源数

2

许可证

MIT-0

最后核验

2026-05-01

来源状态

来源可访问

安装方式

通过对话安装

复制提示词发给支持本地命令或 Skills 的 AI 助手,先确认命令和权限,再让它执行。

请帮我安装这个 Agent Skill:aeo-system(空气动力学系统)
来源仓库:https://github.com/batsirai/aeo-system
安装命令:
openclaw skills install aeo-system
安装前请先检查当前环境是否支持对应 CLI,并向我确认将要执行的命令、安装目录、联网范围和文件读写权限;确认后再执行。

命令行安装

复制命令到本机终端执行。该命令会通过 OpenClaw 从第三方来源获取 Skill;本站只展示命令,不托管安装包,也不自动执行。

ClawHubOpenClaw
openclaw skills install aeo-system

简介

aeo-system 实现答案引擎优化,提升品牌在 AI 推荐中的排名。

  • 支持 AEO 审核、意图图谱构建与位置追踪。
  • 整合多维度信号优化品牌可见性。
  • 建议定期运行以监控变化趋势。适用宿主包括 OpenClaw,接入前应确认版本、权限和运行环境要求。
  • aeo-system 属于研究检索类 Skill,可作为该场景下的辅助能力补充。

SKILL.md

name
aeo-system
description
Answer Engine Optimization — get AI assistants to recommend your brand. Run AEO audits, build Answer Intent Maps, track AI recommendation positions, and maintain a 7-layer AEO infrastructure for any brand or product category.
requiredEnv
permissions
source
url
https://github.com/Batsirai/carson-skills
author
Carson Jarvis (@CarsonJarvisAI)
github
https://github.com/Batsirai/carson-skills
verified
true
security
note
API keys are loaded from environment variables. No credentials are embedded in the skill or scripts.

AEO (Answer Engine Optimization) System

Get AI assistants — ChatGPT, Perplexity, Claude, Gemini — to recommend your brand when people ask purchase-intent questions.

What This Is

AEO is the discipline of optimizing for AI-powered answer engines the same way SEO optimizes for search engines. When someone asks Perplexity "what's the best magnesium supplement for sleep?" — AEO determines whether your brand gets named.

This skill gives an OpenClaw agent the ability to:

  1. Audit a brand's current AEO infrastructure across all 7 layers
  2. Map which brands AI platforms recommend (and in what position) for any category
  3. Track position changes week over week
  4. Build the missing infrastructure (Answer Hub, brand-facts.json, schema, citations)
  5. Maintain the system with a weekly 90-minute protocol

When to Load This Skill

  • User asks to "run an AEO audit" for a brand or URL
  • User asks "which brands are being recommended by AI for [category]?"
  • User asks to "build an Answer Intent Map" for a category
  • User asks to check a brand's Answer Hub, brand-facts.json, or schema markup
  • User asks to track AI recommendation positions over time
  • User asks to run the "weekly AEO maintenance protocol"

The 7-Layer AEO Framework

LayerNameWhat It IsPriority
1Answer Intent MapSpreadsheet of all purchase-intent queries + which brands AI recommendsFoundation
2Answer HubA long-form guide page that answers every key question in your categoryHigh
3Brand-Facts PageHuman-readable brand facts page (neutral, factual, cite-able)High
4brand-facts.jsonMachine-readable brand data at /.well-known/brand-facts.jsonMedium
5Schema MarkupProduct, FAQ, and Organization structured dataMedium
6Citation NetworkGetting listed on the sources AI models actually citeHigh
7GPT ShoppingGoogle Merchant Center + review feed for AI shopping resultsHigh

Prerequisites

Required:

  • PERPLEXITY_API_KEY — enables direct API queries (get free at perplexity.ai/settings/api)
  • Node.js v18+ (for the answer-intent-map.js script)

Optional:

  • OPENAI_API_KEY — enables ChatGPT query automation
  • BRAVE_API_KEY — enables web searches for infrastructure checks

Without API keys: The skill runs in "manual-assist" mode — generates the queries, provides a blank log template, and analyzes results you paste in.


Core Workflows

Workflow 1: Full AEO Audit

Trigger: "Run an AEO audit for [brand URL]"

Steps:

  1. Fetch and analyze the brand's website for AEO infrastructure:

- Check for Answer Hub page (/guides/ or similar long-form page) - Check for Brand-Facts page (/brand-facts) - Check for machine-readable data (/.well-known/brand-facts.json) - Audit schema markup on product pages (via Rich Results API or web_fetch) - Check for a Wikidata entry - Check Google Merchant Center eligibility signals

  1. Score each of the 7 layers (0–3 scale):

- 0 = Doesn't exist - 1 = Exists but incomplete or outdated - 2 = Exists, functional, minor gaps - 3 = Complete, current, optimized

  1. Generate a gap analysis report with:

- Current score per layer - Priority order for implementation - Specific action items for each missing layer

Output: Markdown report saved as aeo-audit-[brand]-[date].md


Workflow 2: Answer Intent Map

Trigger: "Build an Answer Intent Map for [category]" or run scripts/answer-intent-map.js

Steps:

  1. Generate query list from four types:

- Category queries: "best [product] for [use case]" (10–15 queries) - Comparison queries: "[brand] vs [competitor]" (10 queries) - Brand queries: "is [brand] worth it" (5 queries) - Educational queries: "does [ingredient] help with [condition]" (10 queries)

  1. For each query, query available platforms:

- Perplexity API (structured JSON response with citations) - OpenAI API (text response — brand names extracted by parser) - Browser fallback for Claude and Gemini

  1. Parse responses to extract:

- Brand names mentioned (position 1, 2, 3) - Source URLs cited - Key verbatim quotes

  1. Write results to JSON data file + Markdown summary report

Output: answer-intent-map-[category]-[date].json + .md summary

Run the script:

node scripts/answer-intent-map.js \
  --category "magnesium supplements" \
  --brand "MyBrand" \
  --queries 20

# Or with a config file:
node scripts/answer-intent-map.js --config ./aeo-config.json

Workflow 3: Weekly Maintenance Protocol

Trigger: "Run weekly AEO maintenance" or scheduled cron

Steps:

  1. Load the brand's Answer Intent Map (top 15 priority queries)
  2. Query ChatGPT and Perplexity for each priority query in fresh sessions
  3. Compare results against previous week's log (detect position changes)
  4. Generate maintenance report:

- Position changes (up/down/new competitors) - New sources being cited this week - Recommended Answer Hub updates

  1. Check brand-facts.json for stale lastUpdated timestamp
  2. Check Google Merchant Center for disapprovals (via browser if needed)

Output: aeo-weekly-report-[date].md

Use the checklist: templates/weekly-maintenance-checklist.md


Workflow 4: Citation Network Analysis

Trigger: "Analyze AEO citations for [category]"

Steps:

  1. Run 20 category queries via Perplexity API (citations returned directly)
  2. Extract all unique source URLs from responses
  3. Group and count by domain
  4. Identify top 10 most-cited external sources in the category
  5. Generate outreach priority list

Output: Citation analysis report with target sites ranked by citation frequency


Workflow 5: Infrastructure Build

Trigger: "Build AEO infrastructure for [brand]" or "Set up brand-facts.json"

Steps:

  1. Ask for brand details (or load from aeo-config.json)
  2. Generate from templates:

- brand-facts.jsontemplates/brand-facts.json (fill placeholders) - Answer Hub page → templates/answer-hub-template.md - Schema markup snippet (JSON-LD for product pages)

  1. Provide implementation instructions per asset

Configuration

Create aeo-config.json in your working directory:

{
  "brandName": "Your Brand Name",
  "brandUrl": "https://yourbrand.com",
  "category": "Magnesium Supplements",
  "priorityQueries": [
    "best magnesium supplement for sleep",
    "best magnesium glycinate supplement",
    "magnesium supplement for anxiety"
  ],
  "competitors": [
    "Competitor Brand A",
    "Competitor Brand B",
    "Competitor Brand C"
  ],
  "answerHubUrl": "https://yourbrand.com/guides/best-magnesium-supplements-2026",
  "brandFactsJsonUrl": "https://yourbrand.com/.well-known/brand-facts.json"
}

Output Files

FileDescription
aeo-audit-[brand]-[date].mdInfrastructure audit report
answer-intent-map-[category]-[date].jsonRaw AI query results
answer-intent-map-[category]-[date].mdHuman-readable competitive summary
aeo-weekly-report-[date].mdWeekly maintenance report
citation-analysis-[category]-[date].mdCitation network analysis

Usage Examples

# Full infrastructure audit
"Run an AEO audit for mybrand.com"

# Build competitive intelligence
"Build an Answer Intent Map for the magnesium supplement category"

# Quick position check
"Check if mybrand.com is being recommended by Perplexity for 'best magnesium for sleep'"

# Weekly maintenance
"Run the weekly AEO maintenance protocol for my brand"

# Citation analysis
"Which sources does Perplexity cite most for collagen supplement recommendations?"

# Generate brand-facts.json
"Generate the brand-facts.json template for [brand details]"

# Scoring review
"Score my AEO infrastructure for mybrand.com on all 7 layers"

Platform Limitations

PlatformAccessNotes
PerplexityAPI (structured, reliable)Returns citations directly
ChatGPTAPI via OpenAIText parsing required for brand extraction
ClaudeBrowser requiredGenerate queries + blank log; agent uses browser
GeminiBrowser requiredGenerate queries + blank log; agent uses browser

For Claude/Gemini: the skill generates the query list and a blank log template; use the browser tool to collect results.

Rate limits: Perplexity free tier ≈ 20 requests/minute. For 50+ queries, add --delay 3000 to the script.


File Structure

aeo-system/
├── SKILL.md                              ← This file
├── README.md                             ← Human-readable overview
├── scripts/
│   └── answer-intent-map.js              ← Core query automation script
└── templates/
    ├── answer-hub-template.md            ← Answer Hub page template
    ├── brand-facts.json                  ← Machine-readable brand data template
    └── weekly-maintenance-checklist.md  ← 90-minute weekly protocol

*AEO System v1.0 — February 2026* *A product by Carson Jarvis (@CarsonJarvisAI)*

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能力 3

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能力 4

补充不同宿主或平台的使用分布数据

能力 5

展示第三方安全扫描或审计结果

安装后应在对应宿主中按原始 README 的触发条件使用;具体调用方式请以来源页面和 README 为准。

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