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AI Prompt Researcher

作者 GEOLY AI · GitHub ↗ · v1.0.1
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在 OpenClaw 中安装
/install geo-prompt-researcher
功能描述
Discover high-value AI search prompts your target audience uses on ChatGPT, Perplexity, Gemini, and Claude. Research and generate comprehensive prompt lists...
使用说明 (SKILL.md)

AI Prompt Researcher

Methodology by GEOly AI (geoly.ai) — in AI search, prompts are the new keywords.

Research and generate AI search prompts that your target audience uses when seeking products, services, or information in your category.

Quick Start

Generate a prompt research report:

python scripts/research_prompts.py --category "\x3Ccategory>" --brand "\x3Cbrand>" --output report.md

Example:

python scripts/research_prompts.py --category "project management software" \
  --brand "Asana" \
  --competitors "Monday.com,Notion,Trello" \
  --output asana-prompts.md

Why Prompt Research Matters

In traditional SEO, we optimize for keywords. In AI search (GEO), we optimize for prompts.

Key differences:

  • Keywords: Short, fragmented (best crm)
  • Prompts: Natural language questions (what's the best CRM for a 10-person sales team?)

Understanding the prompts your audience uses helps you:

  • Create content that answers those specific questions
  • Monitor brand visibility across AI platforms
  • Identify content gaps vs. competitors

The 5 Prompt Types

Type Pattern Example
Discovery "best [category] for [use case]" "best GEO tool for e-commerce brands"
Comparison "[brand A] vs [brand B]" "Notion vs Asana for project management"
How-To "how to [achieve outcome]" "how to get my brand mentioned by ChatGPT"
Definition "what is [term/concept]" "what is Share of Model in AI search"
Recommendation "recommend a [product] for [need]" "recommend a CRM for real estate agents"

Full taxonomy: See references/prompt-taxonomy.md

Research Methodology

Step 1: Gather Context

Collect from user:

  • Brand name: Your company/product
  • Category: Industry/product category
  • Target audience: Who buys your product
  • Core use cases: Primary jobs-to-be-done
  • Competitors: 3-5 main alternatives
  • Key features: Differentiating capabilities

Step 2: Generate Prompts

Create prompts across 4 awareness stages:

Stage User Mindset Example Prompts
Problem-aware "I have a problem" "how to manage remote teams", "why are projects always late"
Solution-aware "I need a solution" "best project management software", "tools for team collaboration"
Product-aware "I'm considering options" "Asana vs Monday.com", "Notion for project management"
Brand-aware "I know about you" "Asana pricing", "does Asana have time tracking"

Step 3: Score & Prioritize

Each prompt gets scored on:

Dimension Scale Factors
Intent Info → Commercial Likelihood to convert
Volume Low → High Estimated query frequency
Competition Low → High Difficulty to rank
Value Low → High Business impact if won

Priority tiers:

  • 🔴 High: Commercial intent + high value
  • 🟡 Medium: Mixed intent + moderate value
  • 🔵 Low: Informational + awareness building

Step 4: Cluster by Theme

Group related prompts into clusters:

Pricing Cluster
├── "asana pricing"
├── "asana vs monday.com cost"
├── "is asana free"
└── "asana enterprise pricing"

Integration Cluster
├── "asana slack integration"
├── "asana google calendar sync"
└── "asana api documentation"

Output Format

Research Report Structure

# AI Prompt Research Report

**Brand**: [Name]  
**Category**: [Industry]  
**Date**: [YYYY-MM-DD]

## Executive Summary

- Total prompts researched: [N]
- High priority: [N]
- Medium priority: [N]
- Low priority: [N]
- Topic clusters: [N]

## 🔴 High Priority Prompts

| # | Prompt | Type | Intent | Best Platform |
|---|--------|------|--------|---------------|
| 1 | "best [category] for [use case]" | Discovery | Commercial | ChatGPT, Perplexity |
| 2 | "[brand] vs [competitor]" | Comparison | Commercial | Perplexity, Gemini |

## 🟡 Medium Priority Prompts

[Table of informational/commercial mixed prompts]

## 🔵 Low Priority Prompts

[List of awareness-stage prompts]

## Topic Clusters

### Cluster: [Theme]
- [Prompt 1]
- [Prompt 2]
- ...

### Cluster: [Theme]
...

## Platform-Specific Insights

### ChatGPT
- Prompt types that perform well: [list]
- Content format preferences: [description]

### Perplexity
- Prompt types that perform well: [list]
- Citation behavior: [description]

### Gemini
- Prompt types that perform well: [list]
- Unique characteristics: [description]

## Recommended Actions

1. [Action item 1]
2. [Action item 2]
3. [Action item 3]

## Monitoring Setup

Add these prompts to your GEO monitoring dashboard:
- [Tool recommendation]
- [Tracking methodology]

Advanced Usage

Competitor Prompt Analysis

Research what prompts mention competitors but not you:

python scripts/competitor_prompts.py --brand "YourBrand" \
  --competitors "CompetitorA,CompetitorB" \
  --category "your category"

Trending Prompts

Identify emerging prompt patterns:

python scripts/trending_prompts.py --category "your category" --days 30

Prompt Monitoring

Set up ongoing monitoring:

python scripts/monitor_prompts.py --prompts-file prompts.json --frequency weekly

Tools & Resources

  • Google "People also ask": Real user questions
  • AnswerThePublic: Query visualization
  • AlsoAsked: PAA expansion
  • Perplexity: Test how prompts are answered
  • ChatGPT: Explore prompt variations

See Also

安全使用建议
This skill appears to do what it says: generate and cluster prompt lists and output a markdown report. Before installing, note that SKILL.md mentions extra scripts (competitor_prompts.py, trending_prompts.py, monitor_prompts.py) that are not included — ask the publisher whether those tools are intentionally omitted or will be added. Also consider: the shipped Python script is local and does not call external services or require credentials, but if missing monitoring scripts are later added they might contact external endpoints — review any added scripts for network calls or API keys. If you plan to run the script, run it in a controlled environment and inspect any new files before giving it broader privileges.
功能分析
Type: OpenClaw Skill Name: geo-prompt-researcher Version: 1.0.1 The skill bundle is designed to generate AI search prompt research reports. The `SKILL.md` instructs the AI agent to execute a local Python script (`scripts/research_prompts.py`) with user-provided arguments. The Python script uses only standard libraries, performs string formatting and list manipulation, and writes the generated report to a user-specified local file. There is no evidence of network communication, access to sensitive system resources, use of dangerous functions (e.g., `eval`, `exec`, `os.system` for arbitrary commands), or prompt injection attempts with malicious intent. The documentation files are purely informational. The absence of other mentioned scripts (`competitor_prompts.py`, etc.) is a functional limitation, not a security concern within the provided files.
能力评估
Purpose & Capability
The name/description (AI prompt research) aligns with the included assets: SKILL.md, a prompt-generation Python script, and extensive reference docs and templates. The Python code produces prompt lists, clusters, and a markdown report — exactly what the skill claims to do.
Instruction Scope
SKILL.md gives concrete instructions and expects the agent to collect brand/category/audience input and run provided scripts. However, the documentation and examples reference additional scripts (scripts/competitor_prompts.py, scripts/trending_prompts.py, scripts/monitor_prompts.py) that are not present in the file manifest. That mismatch is an inconsistency: the instructions advertise functionality that is not shipped. Otherwise, the instructions do not ask the agent to read unrelated system files or access secrets.
Install Mechanism
No install spec is declared (instruction-only + one included script). Nothing is downloaded or written by an install step. The included Python script uses only standard library imports (argparse, json, sys, datetime) and does not pull remote code at install time.
Credentials
The skill declares no required environment variables, no credentials, and no config paths. The provided code likewise does not reference any environment variables or secret material. The level of access requested is proportional to the stated purpose.
Persistence & Privilege
Flags show always:false and default autonomous invocation allowed (normal). The skill does not request permanent system presence or attempt to modify other skills or system-wide settings in the shipped files.
如何使用
  1. 确保已安装 OpenClaw(本地或 Docker 部署)
  2. 在对话框中输入安装命令:/install geo-prompt-researcher
  3. 安装完成后,直接呼叫该 Skill 的名称或使用 /geo-prompt-researcher 触发
  4. 根据 Skill 的参数说明提供必要输入,即可获得结构化输出
版本历史
v1.0.1
- Expanded the documentation with detailed research methodology, prompt generation, and output formatting guidelines. - Added support for Claude as a target AI platform. - Introduced CLI research workflow and advanced usage examples (competitor/monitoring/trending). - Included new reference materials: prompt taxonomy, templates, platform guide, and example reports. - Enhanced explanation of prompt types, audience targeting, and clustering. - Added scripts and evaluation files to automate prompt research and scoring.
v1.0.0
Initial release: Discover high-value AI search prompts for your brand, GEOly AI methodology
元数据
Slug geo-prompt-researcher
版本 1.0.1
许可证
累计安装 0
当前安装数 0
历史版本数 2
常见问题

AI Prompt Researcher 是什么?

Discover high-value AI search prompts your target audience uses on ChatGPT, Perplexity, Gemini, and Claude. Research and generate comprehensive prompt lists... 它是一个面向 Claude Code / OpenClaw 的 AI Agent Skill 插件,目前累计下载 390 次。

如何安装 AI Prompt Researcher?

在 OpenClaw 或 Claude Code 对话框中运行命令「/install geo-prompt-researcher」即可一键安装,无需额外配置。

AI Prompt Researcher 是免费的吗?

是的,AI Prompt Researcher 完全免费(开源免费),可自由下载、安装和使用。

AI Prompt Researcher 支持哪些平台?

AI Prompt Researcher 跨平台运行,可在任意部署了 OpenClaw / Claude Code 的环境中使用(cross-platform)。

谁开发了 AI Prompt Researcher?

由 GEOLY AI(@geoly-geo)开发并维护,当前版本 v1.0.1。

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