audit-coverage

Audit AI agent component, platform, and advanced feature coverage against demos.

4|1|Updated Feb 22, 2026

Search Tags:#audit #analysis #agent #platform #coverage #demo

Ready to run

npx skills add https://github.com/7hinkDifferent/agent-cracker --skill audit-coverage

💬 Prompt for ChatGPT / Claude Chat▼

Please help me install this Agent Skill.
Skill: audit-coverage
Source: https://github.com/7hinkDifferent/agent-cracker/tree/main/.claude/skills/audit-coverage
Command: npx skills add https://github.com/7hinkDifferent/agent-cracker --skill audit-coverage

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

This Skill helps you understand the completeness of your AI agent analysis by auditing the coverage of core components, platform mechanisms, and advanced features against existing demos and documentation.

Core Features & Use Cases

Component Coverage Audit: Assesses which essential agent components (like core loop, editing, prompt assembly) have corresponding demos.
Platform Mechanism Audit: Checks coverage for platform-specific features (e.g., multi-channel routing, memory management) for platform agents.
Advanced Feature Audit: Reviews the implementation status of advanced or innovative mechanisms.
Use Case: After analyzing a new AI agent, use this skill to quickly see which parts of its architecture have been successfully replicated in demos and which still need development effort.

Quick Start

Run the audit-coverage skill to check the coverage for the 'aider' agent.

Frequently Asked Questions about audit-coverage

High-intent search queries and answers about installing and using this skill.

FAQPage Schema

How do I audit AI agent component coverage and identify missing implementations?▼

To audit AI agent coverage, you analyze documentation and demo repositories to assess which core components, platform mechanisms, and advanced features have existing demos versus missing implementations. This process identifies actionable next steps for your development effort.

What is the best way to check if an AI agent's platform mechanisms have corresponding demos?▼

Checking platform mechanism coverage involves reviewing your demo repositories and agent documentation to verify which platform-specific features like multi-channel routing and memory management are successfully replicated. The audit highlights existing demos and gaps in platform agent implementations.

Can I use this coverage audit for both coding agents and platform agents?▼

Yes, you can use this coverage audit for both coding and platform agent types. The analysis adapts to each type by auditing core components like editing and prompt assembly for coding agents, and platform-specific mechanisms for platform agents.

How do I identify gaps in advanced AI agent features after analyzing the architecture?▼

To identify gaps in advanced features, you review the implementation status of innovative mechanisms against existing demos. The audit evaluates advanced feature coverage and suggests actionable next steps to complete missing implementations in your agent development.

Does agent coverage analysis work without dependencies or external components?▼

Yes, agent coverage analysis works without external dependencies or components. The audit functions by analyzing your existing documentation and demo repositories directly to assess MVP component coverage and pinpoint missing implementations.