Agent skill · writing content · jeremylongshore
cursor-debug-bundle
Debug AI suggestion quality, context issues, and code generation problems
Why this skill is useful
Provides domain-specific debugging workflows and context management strategies for AI code generation that the AI wouldn't reliably generate on its own.
What it needs
About 5k tokens when loaded. Last updated 2026-08-07. 2,604 stars on the source repository.
What this skill does
Cursor Debug Bundle Overview Collect a minimal, redacted reproduction for a Cursor issue involving context, rules, indexing, model behavior, or extensions. Debug material may contain proprietary code or prompts, so scope and retention matter as much as reproducibility. Prerequisites A named issue owner, Cursor version, affected workspace, and approved bug-report destination. Permission to inspect logs and settings, plus redaction rules for code, prompts, paths, tokens, and user data. A minimal reproducer that does not require customer data or production credentials. Instructions 1. Start with the smallest reproducible prompt, file set, rule set, and model configuration. 2. Record versions, active context, indexing state, extensions, and redacted console errors. 3. Remove proprietary code, credentials, identifiers, and full prompt/output text before sharing externally. 4. Test the proposed resolution in a non-sensitive workspace and document its result before closing the issue. Diagnose and fix AI suggestion quality issues in Cursor. Covers why AI generates wrong code, how to improve context, and systematic debugging workflows. Diagnostic Framework When AI suggestions are wrong, the cause is almost always one of these: Debugging by Symptom AI Uses Wrong API or Library Version Symptom: Generated code uses React.createClass, old Express syntax, or deprecated patterns. Root cause: Model training data includes old code. No project rules specifying versions. Fix: AI Generates Code That Doesn't Match Your Patterns Symptom: Generated code uses different naming, structure, or patterns than your codebase. Root cause: AI does not have your existing code as context. Fix: Reference your existing patterns explicitly: AI Hallucinates Non-Existent Functions Symptom: AI calls functions or uses imports that do not exist in your project or in the library. Root cause: Model confuses similar libraries or invents plausible-sounding APIs. Fix: 1. …
How to use it
Reference it in AdaL, Claude Code, Cursor or any coding agent — nothing to install:
@skills jeremylongshore/cursor-debug-bundle