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Tool Argument Validator
x402
Tool Argument Validator is a paid API for AI agents from modell.halowerk.com, paid per call via x402, $0.002/call, status unknown (last checked 2026-09-13).
Validates tool call arguments against a JSON Schema and flags semantic anomalies like placeholder values, suspicious numbers, destructive flags, and checksum failures.
Price / call$0.002
Success—
StatusUnknown
How this service works
Two checks in one. First the arguments are validated against the tool input schema and every violation is reported with its path and a sentence saying what to change. Second, values that satisfy the schema but look wrong are flagged: an unset required field filled with a placeholder like "string" or "TODO", a number at a suspicious order of magnitude, an address that fails its checksum shape, a destructive flag set to true, an empty string where content was expected.
Output
A structured report listing: (1) schema violations with JSON path, the broken rule, and a plain-English fix suggestion; (2) semantic anomalies such as unfilled placeholder strings ('string', 'TODO'), numbers at a suspicious order of magnitude, addresses failing checksum shape, destructive flags set to true, and empty strings where content was expected — each with its field path and a description of what looks wrong.
Example use cases
Pre-flight check before tool execution
“Before running the 'send_payment' tool with these arguments, validate them against its schema and tell me if anything looks wrong — especially if there's a placeholder value, a suspicious amount, or a destructive flag enabled.”
Catching placeholder values in agent pipeline
“I'm building an agentic pipeline and I want to make sure my LLM isn't passing dummy values like 'string' or 'TODO' into tool calls — can you run a semantic check on these tool arguments and report any that look like unfilled placeholders?”
Debugging malformed tool call from agent
“My agent just produced a tool call but the downstream API rejected it. Can you validate these arguments against the tool's JSON schema and tell me exactly which fields are wrong, what rule they break, and what I'd need to change to fix them?”
Technical details
Endpoint
POSThttps://modell.halowerk.com/v1/tool-arg-validateWhen to prefer
Use this endpoint when you need both structural schema validation AND semantic sanity checking of tool arguments in a single call — especially in agentic pipelines where LLMs may fill required fields with placeholder text or set dangerous flags inadvertently. Prefer it over pure JSON Schema validators when you care about catching 'technically valid but obviously wrong' values before a tool is invoked.
Side effects
- Missing or malformed tool input schema returns a schema-parse error
- Arguments payload that is not valid JSON returns a parse error
- Ambiguous schema definitions (e.g. oneOf without discriminator) may reduce anomaly detection accuracy
- Checksum-style checks are heuristic and may produce false positives for non-standard address formats
- Numeric order-of-magnitude checks depend on field naming heuristics and may miss domain-specific ranges
Input
Schema · Request body
| Field | Type | Description |
|---|---|---|
| schema | object | The tool input schema. |
| arguments | object | The arguments about to be sent. |
| tool_name | string | Name of the tool, carried into the report. |
| irreversible | boolean | Mark the call as irreversible. Raises every warning one level. |
| expected_magnitude | object | Optional per-field order-of-magnitude hint, e.g. {"amount": 100}. A value more than 100x off is flagged. |
Tags
x402
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