Ai Debt Detector

Overview

AI agents generate code that passes the happy path but hides debt: missing error handling, orphaned resources, ignored failure modes, hallucinated packages, silent architectural drift. This skill forces a targeted audit for the exact patterns AI agents get wrong.

When to Use

• After any AI code generation session (agent wrote 20+ lines)
• Before merging AI-generated PRs
• When code "works" but something feels off
• After vibe-coding sprints — debt accumulates fastest here
• When you find yourself saying "the agent said it's done"

Process

After ANY code generation, scan for these AI-specific debt patterns:

1. FAILURE MODES — What happens when this fails?
   - Network timeout? Disk full? Permission denied? Null input?
   - Is there a try/catch? Does it catch SPECIFIC errors or swallow everything?
   - Are resources cleaned up on failure? (streams closed, connections returned, temp files deleted)

2. ORPHANS — What gets created but never cleaned up?
   - Temp files, event listeners, intervals, subscriptions, connections
   - Are there corresponding cleanup/dispose/close calls for every open/create?
   - In React: does every addEventListener have a removeEventListener in cleanup?

3. EDGE CASES — What inputs break this?
   - Empty array/string? null/undefined? Very large input? Unicode? Concurrent calls?
   - Does the code assume the happy path? (hint: AI almost always does)

4. HALLUCINATED DEPS — Do all imports actually exist?
   - Is every package in package.json/requirements.txt?
   - Are API methods real? (AI invents plausible-sounding methods that don't exist)
   - Check: does this library's latest version still export this function?

5. ARCHITECTURAL DRIFT — Does this match the project's patterns?
   - Same error handling style as existing code?
   - Uses the project's established utilities (not reinventing)?
   - Follows the file structure convention?
   - Matches naming patterns (camelCase vs snake_case, etc.)

Red Flags (stop and fix IMMEDIATELY)

• catch (e) {} or catch (e) { console.log(e) } — swallowed error
• No finally block when resources were opened
• // TODO: handle error — AI's way of punting
• Import from a path that doesn't exist in the project
• Timeout set but no abort/cleanup on timeout
• Database connection opened but never released back to pool
• File opened but no close in error path

Common Mistakes

• Trusting that "it compiled" means "it works" (compilation checks syntax, not logic)
• Reviewing only the diff without checking what the AI DIDN'T generate (missing error paths)
• Assuming the AI used the right library version (it often uses deprecated APIs)
• Skipping the orphan check because "garbage collection handles it" (it doesn't for connections, listeners, timers)

Rationalizations (countered)

| Excuse | Reality | |--------|---------| | "It works in testing" | Testing only covers happy path. Production has failures. | | "I'll add error handling later" | You won't. And you'll forget which parts need it. | | "The framework handles cleanup" | Does it? Which framework, which version, which method? Verify. | | "It's just a prototype" | Prototypes become production. Debt compounds from day one. | | "The AI generated it, it's probably fine" | AI generates 1.7x more issues than human code (CodeRabbit, 2026). |

Persistence

ACTIVE after every code generation session. Scan silently. Report only actual findings. Don't generate false positives — only flag patterns that genuinely indicate hidden debt.

Depth Levels

| Change Size | Audit Depth | |-------------|-------------| | "It works" is not "it's done." Agent code often passes the happy path and dies on edge cases you haven't thought of yet.

Source & license

This open-source skill is cataloged on AgentStack and links to its original source — we do not rehost the code.

• Author: Adit-Jain-srm
• Source: Adit-Jain-srm/skill-forge
• License: MIT
• Homepage: https://github.com/Adit-Jain-srm/skill-forge#quick-start

Install and usage instructions live in the source repository linked above.