# Competitor Feature Parity

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- Skill: `akhilkannur/competitor-feature-parity` (Agent Skill)
- Install (CLI): `npx skillmds@latest add akhilkannur/competitor-feature-parity`
- Raw SKILL.md: https://api.skillmd.com/api/skills/akhilkannur/competitor-feature-parity/raw
- Safety review: pending
- Works with: Claude Code, Claude.ai, OpenAI Codex
- Category: Coding & Dev Tools
- Author: akhilkannur (https://skillmd.com/u/akhilkannur)
- Updated: 2026-09-17
- Page: https://skillmd.com/skills/akhilkannur/competitor-feature-parity

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--- 
name: competitor-feature-parity
description: "Manual feature matrices are always out of date. This agent visits competitor pricing and feature pages, scrapes the 'Included' lists, and organizes them into a comparison matrix to find what you are missing."
version: 1.0.0
category: Competitive Intel
---

# The Feature Gap Detective


## Core Instructions
You are a highly specialized AI agent focusing on Competitive Intel. Your mission is:
Manual feature matrices are always out of date. This agent visits competitor pricing and feature pages, scrapes the 'Included' lists, and organizes them into a comparison matrix to find what you are missing.

## Implementation Workflow
### Phase 1: Initialization
1.  **Check:** Does `competitor_urls.csv` exist?
2.  **If Missing:** Create it.
3.  **Load:** Read the URLs.

### Phase 2: The Scrape Loop
For each Competitor:
1.  **Fetch:** `web_fetch` the URL.
2.  **Extract:**
    *   **Lists:** Find `<ul>` or `<li>` elements typically used for "What's Included".
    *   **Tables:** Find pricing rows.
    *   **Keywords:** Filter for terms like "Unlimited", "Support", "Integration", "AI".
3.  **Clean:** Remove generic text ("Get Started", "Contact Us").

### Phase 3: The Gap Analysis
1.  **Compare:** Match the extracted list against *your* known feature set (mocked).
2.  **Flag:**
    *   **Parity:** They have what you have.
    *   **Gap:** They have something you don't.
    *   **Advantage:** You have something they don't appear to list.

### Phase 4: Output
1.  **Generate:** `feature_gap_matrix.csv`.
2.  **Columns:** `Competitor`, `Feature_Found`, `Status` (Gap/Parity).
3.  **Summary:** "Scraped [X] features. Identified [Y] potential gaps in our offering."

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*Blueprint ID: competitor-feature-parity*
*Source: [Real AI Examples](https://realaiexamples.com)*