| name | forge-ai-audit |
| description | Review AI/LLM integrations - client configurations, prompt quality, and fallback safety. Trigger when user types /forge-ai-audit or requests an AI audit/review.
|
/forge-ai-audit
Review AI/LLM integrations, prompts, and configurations using AI reasoning.
Command
/forge-ai-audit [path] [--quick|--deep] [--markdown|--json] [--verbose]
Options
[path] — Target directory (default: current directory)--quick — Fast scan, focus on critical issues only--deep — Thorough scan, check all patterns--markdown — Output as markdown (default)--json — Output as JSON--verbose — Include detailed evidence
Purpose
Analyze source code for:
- AI Client SDK configuration issues (temperature, max_tokens, retry policies, error-handling)
- Prompt quality, formatting, Socratic Tutor pitfalls, and output parsing safety
- Fallback mechanisms and content security/filtering for LLM responses
Workflow
Step 1: Understand Project
Use shared/analyzer/ to detect:
- Repository type
- Primary language
- Framework
- Project structure
Step 2: Run AI Integration Analysis
Execute analysis prompts in order:
- Client SDK Configuration (
prompts/client-config.md)
- Prompt Quality & Format (
prompts/prompt-quality.md)
- Fallback & Content Security (
prompts/fallback-safety.md)
Step 3: Classify Findings
For each finding:
- Assign severity: Critical, High, Medium, Low, Info
- Assign confidence: High, Medium, Low
- Include evidence (file, line, code snippet)
Step 4: Generate Report
Use shared/report/ to generate:
- AI Integration Score (0-100)
- Severity-grouped findings
- Recommendations for AI/LLM stability and accuracy
Output Format
Follow the markdown report format generated by shared/report/markdown.ts. It MUST use the following layout:
AI Integration Audit Report
Project: [Project Name]
Path: [Project Path]
Language: [Primary Language]
Framework: [Detected Framework (optional)]
Date: [Timestamp]
Score
[Score]/100 (Grade: [Grade])
| Severity | Count |
|---|
| 🔴 Critical | [count] |
| 🟠 High | [count] |
| 🟡 Medium | [count] |
| 🔵 Low | [count] |
| ⚪ Info | [count] |
Executive Summary
Found [total] issues: [count] critical, [count] high, [count] medium, [count] low, [count] info.
🔍 Detailed Findings
[Severity Group (e.g. 🟠 High)]
| Title | Location | Description | Impact |
|---|
| [Finding Title] | [file-name]:[line] | [Description] | [Impact] |
📂 Code Evidence
Finding #[number]: [Finding Title]
[code snippet]
