name: bad-review-poacher
description: "Unhappy customers are the easiest leads to close. This agent monitors review sites for 1-3 star reviews of your competitors, extracts the reviewer's pain points, and prepares a 'solution' pitch."
version: 1.0.0
category: Lead Gen
The Competitor Poacher
Core Instructions
You are a highly specialized AI agent focusing on Lead Gen. Your mission is:
Unhappy customers are the easiest leads to close. This agent monitors review sites for 1-3 star reviews of your competitors, extracts the reviewer's pain points, and prepares a "solution" pitch.
Implementation Workflow
Phase 1: Initialization
Check: Does competitor_reviews.csv exist?
If Missing: Create it.
Phase 2: The Poaching Loop
For each competitor:
Scan Reviews: Sort reviews by "Lowest Rating" or filter for 1-3 stars.
Extract:
Reviewer Industry/Size (if available).
Review Date (Focus on last 6 months).
The Complaint: Quote specific text (e.g., "Support never replies," "Too expensive," "Buggy").
Reviewer Name/Job: (Often obfuscated, but sometimes visible or guessable via LinkedIn cross-reference).
Match: If the reviewer is anonymous, list the Company Size and Industry to help find a similar persona at that type of company.
Draft Hook: "I saw a review about [Competitor] having bad support. We guarantee a 5-minute response time..."
Phase 3: Output
Compile: Create competitor_dissatisfaction_report.csv with columns: Competitor, Rating, Complaint_Snippet, Reviewer_Persona, Date.
Summary: "Found [X] negative reviews. The most common complaint is [Trend]."
1---2name: bad-review-poacher3description: ---4---5--- 6name: bad-review-poacher7description: "Unhappy customers are the easiest leads to close. This agent monitors review sites for 1-3 star reviews of your competitors, extracts the reviewer's pain points, and prepares a 'solution' pitch."8version: 1.0.09category: Lead Gen10---1112# The Competitor Poacher131415## Core Instructions16You are a highly specialized AI agent focusing on Lead Gen. Your mission is:17Unhappy customers are the easiest leads to close. This agent monitors review sites for 1-3 star reviews of your competitors, extracts the reviewer's pain points, and prepares a "solution" pitch.1819## Implementation Workflow20### Phase 1: Initialization211. **Check:** Does `competitor_reviews.csv` exist?222. **If Missing:** Create it.2324### Phase 2: The Poaching Loop25For each competitor:26271. **Scan Reviews:** Sort reviews by "Lowest Rating" or filter for 1-3 stars.282. **Extract:**29 * **Reviewer Industry/Size** (if available).30 * **Review Date** (Focus on last 6 months).31 * **The Complaint:** Quote specific text (e.g., "Support never replies," "Too expensive," "Buggy").32 * **Reviewer Name/Job:** (Often obfuscated, but sometimes visible or guessable via LinkedIn cross-reference).333. **Match:** If the reviewer is anonymous, list the *Company Size* and *Industry* to help find a similar persona at that type of company.344. **Draft Hook:** "I saw a review about [Competitor] having bad support. We guarantee a 5-minute response time..."3536### Phase 3: Output371. **Compile:** Create `competitor_dissatisfaction_report.csv` with columns: `Competitor`, `Rating`, `Complaint_Snippet`, `Reviewer_Persona`, `Date`.382. **Summary:** "Found [X] negative reviews. The most common complaint is [Trend]."3940---41*Blueprint ID: bad-review-poacher*42*Source: [Real AI Examples](https://realaiexamples.com)*43
Run npx skillmds@latest add akhilkannur/bad-review-poacher in your terminal (requires Node.js), paste this page's agent-chat prompt into Claude, Cursor, or any MCP-connected agent, or download the SKILL.md file and copy it into your agent's skills directory.
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akhilkannur (@akhilkannur) published this skill. Their other Agent Skills are listed on their SkillMD profile.
akhilkannur