Is competitor-feature-parity safe to install?

SaferSkills independently audited competitor-feature-parity (Agent Skill) and scored it 100/100 (green). The audit ran 55 deterministic rules across Security, Supply Chain, Maintenance, Transparency, and Community; it found 0 high-severity and 0 lower-severity findings. The full rule-by-rule trace and per-finding evidence are below. Free, methodology-open.

CategoryWeightCategory scoreContribution

Securityprompt, exec, net, exfil, eval

35%

100

35.0 pts

Supply chainhash, typosquat, maintainer, lockfile

20%

100

20.0 pts

Maintenancestaleness, pinning, CI

15%

100

15.0 pts

TransparencySKILL.md, perms, README

15%

100

15.0 pts

Communityinstalls, verify, response

15%

100

15.0 pts

Findings & checks · 0 flagged

Securityscore 100 · 0 findings

✓—All security checks passedNo findings in this category for the latest scan.pass

Supply chainscore 100 · 0 findings

✓—All supply chain checks passedNo findings in this category for the latest scan.pass

Maintenancescore 100 · 0 findings

✓—All maintenance checks passedNo findings in this category for the latest scan.pass

Transparencyscore 100 · 0 findings

✓—All transparency checks passedNo findings in this category for the latest scan.pass

Communityscore 100 · 0 findings

✓—All community checks passedNo findings in this category for the latest scan.pass

The primary manifest — the file an agent reads to learn what this artifact does.

skills/competitor-feature-parity/SKILL.md · 1 file

skills/competitor-feature-parity/SKILL.md1.8 KB · Markdown

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description: "Manual feature matrices are always out of date.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 Your mission is: Manual feature matrices are always out of date.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

Check: Does competitor_urls.csv exist?
If Missing: Create it.
Load: Read the URLs.

Phase 2: The Scrape Loop

For each Competitor:

Fetch: web_fetch the URL.
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".

Clean: Remove generic text ("Get Started", "Contact Us").

Phase 3: The Gap Analysis

Compare: Match the extracted list against your known feature set (mocked).
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

Generate: feature_gap_matrix.csv.
Columns: Competitor, Feature_Found, Status (Gap/Parity).
Summary: "Scraped [X] features. Identified [Y] potential gaps in our offering."

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

competitor-feature-parity— agent skill

Is competitor-feature-parity safe to install?

The Feature Gap Detective

Core Instructions

Implementation Workflow

Phase 1: Initialization

Phase 2: The Scrape Loop

Phase 3: The Gap Analysis

Phase 4: Output

Audit the pieces. Scan the whole. Decide.