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Diagnose and fix Groq API errors with real error codes and solutions.
Passed 20 of 22 test cases with the skill, and 18 of 22 without it.
2 fixed18 passed either way2 still failing0 broke
Tokens, turns and time describe resource use, not a dollar price.
One of 2 test cases the skill fixed. Same model, same prompt, with and without the skill.
Write a shell snippet using curl and jq to list all currently supported Groq model IDs in alphabetical order.
| Checked | Without skill | With skill |
|---|---|---|
| Uses curl to query https://api.groq.com/openai/v1/models with GROQ_API_KEY authentication. | Passed | Passed |
| Pipes output to jq '.data[].id' and sort. | Missed | Passed |
The instructions your model reads when the skill loads.
Comprehensive reference for Groq API error codes, their root causes, and proven fixes. Groq returns standard HTTP status codes with structured error bodies and rate-limit headers. This skill walks the diagnosis from raw error string to fix, then hands off to the full per-status reference for depth.
Every Groq error body follows one shape — read the code and type first:
{
"error": {
"message": "Rate limit reached for model `llama-3.3-70b-versatile`...",
"type": "tokens",
"code": "rate_limit_exceeded"
}
}
GROQ_API_KEY exported in the environment (keys start with gsk_).curl and jq available for the diagnostic probes below.groq-sdk (TypeScript) or groq (Python) installed.Capture the failing status and body. Read the raw error response — the HTTP status plus the code/type fields determine the whole diagnosis path.
Confirm the key works before assuming anything deeper:
set -euo pipefail
# Verify API key is valid — expect a model count, not an auth error
curl -s https://api.groq.com/openai/v1/models \
-H "Authorization: Bearer $GROQ_API_KEY" | jq '.data | length'
Confirm the model still exists. Many 400s are deprecated model IDs — list the live models and Grep your codebase for any stale ID:
curl -s https://api.groq.com/openai/v1/models \
test cases passed, vs 18 / 22 without
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