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HALOWERK: Check tool arguments against their schema before an expensive or irreversible ca

tool_arg_validate
Read-only

Validate tool arguments against their schema before expensive or irreversible calls, catching violations and suspicious values that could lead to mistakes.

Instructions

Check tool arguments against their schema before an expensive or irreversible call, and get warnings for values that pass the schema but look like mistakes.

Kostenpflichtig: 0.002 USDC je Aufruf. Bezahlt per x402 auf Base, ohne Konto. Hoechstens 0.002 USDC je Aufruf.

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. Fields whose names suggest an irreversible effect — amounts, recipients, deletion and force flags — are held to the stricter standard. Warnings are heuristics and can be wrong in both directions: treat them as a prompt to look, not a verdict, and never as a substitute for the tool own checks. Preis 0.002 USDC je Aufruf, Abrechnung über x402.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
schemaYesThe tool input schema.
argumentsYesThe arguments about to be sent.
tool_nameNoName of the tool, carried into the report.
irreversibleNoMark the call as irreversible. Raises every warning one level.
expected_magnitudeNoOptional per-field order-of-magnitude hint, e.g. {"amount": 100}. A value more than 100x off is flagged.
Behavior5/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

The description discloses the two-stage behavioral process (schema validation and heuristic warnings) and importantly notes that warnings can be wrong in both directions, which is critical for interpretation. This goes beyond the readOnlyHint annotation by explaining how results should be used. It also adds pricing and x402 payment details, providing operational context.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness3/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is front-loaded with its main purpose, but it contains redundant pricing information in both German and English, duplicating the same cost details. The structure is organized around the two checks, but the repetition and mixed-language content reduce efficiency.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness4/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

For a tool with 5 parameters and no output schema, the description adequately covers its purpose, behavioral details, limitations, and usage context. It explains what the tool does, when to use it, and its caveats. It doesn't detail the return format, but this is acceptable given the absence of an output schema and the presence of annotations.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters4/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

The schema already has 100% coverage with descriptions for all 5 parameters, so the baseline is 3. The description adds value by explaining that fields suggesting irreversible effects are held to stricter standards, which gives additional meaning to parameters like 'irreversible' and helps the agent understand how field names might trigger heuristics. This slightly enhances the schema's semantics.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose5/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the tool's function with a specific verb ('Check') and resource ('tool arguments against their schema'). It also adds the usage context of expensive/irreversible calls, which distinguishes it from sibling tools like output_validate.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines4/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description explicitly says to use it 'before an expensive or irreversible call,' providing clear usage context. It also includes a caution that warnings are heuristics and not a substitute for the tool's own checks, which implies when not to fully trust it. However, it does not explicitly name alternative tools or state strict exclusion criteria.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

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