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modell.halowerk.com Trace Grade
x402
modell.halowerk.com Trace Grade is a paid API for AI agents from modell.halowerk.com, paid per call via x402, $0.002/call, status unknown (last checked 2026-09-15).
Analyzes an AI agent run's step trace to produce a scored quality report detecting loops, failure streaks, wasted calls, and per-step cost attribution.
Price / call$0.002
Success—
StatusUnknown
How this service works
Takes the steps of one agent run and returns a scored report. It counts identical tool calls (same tool, same arguments) as loops, finds the longest run of consecutive failures, marks calls whose result was empty or null as wasted, and attributes cost per step and per tool so the expensive part is visible. Cost is taken from your figures when supplied, otherwise computed from token counts against the model price table.
Output
A structured scored report containing: detected loop instances (identical tool+arguments pairs), the longest consecutive failure streak, a list of wasted calls (empty or null results), per-step cost attribution, per-tool cost attribution, and an overall quality score for the agent run.
Example use cases
Debugging a looping agent run
“My agent seems to have gotten stuck calling the same search tool over and over — can you analyze this trace and show me exactly where the loops are and how many times each repeated call happened?”
Auditing agent cost after an expensive run
“This agent run cost way more than expected — can you break down the cost per step and per tool from this trace so I can see what drove up the bill?”
Identifying wasted calls before optimizing prompts
“Before I rewrite my agent's system prompt, can you score this run trace and flag any tool calls that returned null or empty results so I know what's being wasted?”
Technical details
Endpoint
POSThttps://modell.halowerk.com/v1/trace-gradeWhen to prefer
Choose this endpoint when you need a post-hoc audit of a completed agent run — specifically when you want loop detection, failure streak analysis, wasted-call identification, and cost attribution all in one scored report. Prefer it over generic logging tools when you need machine-readable quality scores tied to individual tool calls rather than raw logs.
Side effects
- Missing or malformed steps array causes validation error
- Unrecognized model name falls back to token-count-based pricing if token counts provided, or fails if neither cost nor tokens supplied
- Empty trace (zero steps) may return trivial or error response
- Malformed tool argument shapes prevent loop detection accuracy
- Rate limiting or payment failure for the $0.002 USDC per-call fee
Input
Schema · Request body
| Field | Type | Description |
|---|---|---|
| model | string | Model id used, to price token counts when cost_usd is absent. |
| steps | array | The steps of the run, in order. |
| loop_threshold | integer | From how many identical calls on it counts as a loop. |
Tags
x402
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