consult-chatgpt

This skill automates a cached consultation workflow with ChatGPT for debugging guidance. Provide your goal, context, evidence, what you've tried, and your question; the skill formats a standardized prompt, computes a fingerprint, checks the cache, and queries ChatGPT only if needed—eliminating redundant calls and speeding up repeated consultations.

Yes. This skill accepts structured input—goal, context, evidence, tried approaches, and question—to produce consistent ChatGPT prompts for architecture critiques. It enforces input validation and returns a structured summary of likely causes, discriminating tests, and suggested approaches.

Caching stores ChatGPT responses by fingerprint so identical or near-identical questions retrieve the cached answer instead of making a new API call. This reduces latency, costs, and back-and-forth delays when you ask the same debugging or architecture question multiple times.

This skill parses a five-part payload: goal (what you're trying to achieve), context (your environment or setup), evidence (data or logs supporting the issue), tried (what you've already attempted), and question (what you need to know). It formats these into a standardized prompt and queries ChatGPT for expert guidance.

The skill validates input, enforces secret handling to avoid exposing credentials, limits snippet size, and structures responses consistently. These constraints ensure safe, repeatable interactions and prevent accidental leakage of sensitive information in ChatGPT queries.

Use this skill when you need repeatable expert guidance on debugging, architecture, or best practices and want to avoid redundant API calls. Caching is most valuable when you revisit the same problem, share consultations across a team, or run automated workflows that require consistent advice.