What engineers usually see
- •Requests fail but tokens are still charged
- •Retries incur additional costs
- •Cannot tell which failures cost money
- •Bill includes charges for unsuccessful work
Why this is hard to debug
Providers charge for partial processing even on failures. You can't distinguish between successful, failed, and retried request costs. Receipts show cost per attempt regardless of outcome.
Minimal repro
curl https://aibadgr.com/v1/chat/completions \
-H "Authorization: Bearer YOUR_OPENAI_KEY" \
-H "Content-Type: application/json" \
-d '{
"model": "gpt-4o-mini",
"messages": [{"role": "user", "content": "test"}]
}'This request routes through AI Badgr and returns a stable request ID that links to an execution record.
Note: AI Badgr is OpenAI-compatible and works as a drop-in proxy. No SDK changes required — only the base_url changes.
What a per-request execution record makes visible
- Cost of failed requests
- Cost per retry attempt
- Total waste from failures
- Success rate vs cost
- Failure cost trends
Run 1 request → get receipt
Change your base URL to https://aibadgr.com/v1 and run your request.
The response includes an X-Badgr-Request-Id header that links to a receipt showing latency, retries, tokens, cost, and failure stage for that specific execution.
Not the engineer?
Share this page with your dev and ask them to run one request through AI Badgr. That's all that's needed to get the receipt.
This kind of thing only makes sense when you can actually see what happened to a single request from start to finish, instead of trying to piece it together from scattered logs.