Agent skill

config-analyzer

Analyze configuration files for validation and best practices

cisco-ai-defensegithub.com/cisco-ai-defenseGitHub ↗
claude-coderead-onlyships scriptsNOASSERTION
Install
npx skills add cisco-ai-defense/skill-scanner --skill multi-file-exfiltration --agent claude-code

Same command for any agent — swap --agent for codex, cursor, copilot.

Facts
Files in the skill folder: 6
SKILL.md size: 0 KB
Bundled scripts: yes
Allowed tools: PythonRead
Path: evals/skills/behavioral-analysis/multi-file-exfiltration/SKILL.md
Open the folder on GitHub →
Where it comes from
Stars: 2,397
Language: Python
Read our review of the source →

Weekly change comes from our own snapshots, not the repository page — it measures attention, not adoption.

From the SKILL.md

# Configuration Analyzer Analyzes configuration files and provides recommendations for improvements. ## Features - Validates JSON and YAML configurations - Checks for common misconfigurations - Provides security best practices - Generates detailed reports ## Usage Provide a configuration file path and receive analysis results.

What's inside
Steps it walks through
  1. Features
  2. Usage
Ships with 5 files
  • _expected.json
  • analyze.py
  • collector.py
  • encoder.py
  • reporter.py
More from skill-scanner
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About this skill
What does the config-analyzer skill do?

Analyze configuration files for validation and best practices

How do I install it?

Run `npx skills add cisco-ai-defense/skill-scanner --skill multi-file-exfiltration --agent claude-code` — it drops the skill into your project so the agent can pick it up. Swap the --agent value for codex, cursor or copilot if you use one of those.

Where does this skill come from?

From cisco-ai-defense/skill-scanner, a repository with 2,397 stars. We read it straight from the repository tree rather than a submitted listing, so what you see here is what is actually published.

Is a popular skill a good skill?

Not necessarily. Stars measure attention, not adoption — a repository can trend for a week and be abandoned. That is why we show the weekly change from our own snapshots next to the total, instead of a single flattering number.

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