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validate.batch

Validate up to 100 mixed identifiers in one deterministic call. Each result shows validity and type-specific fields, with errors isolated to the offending item.

Instructions

Validate up to 100 mixed identifiers in one deterministic call. Pass items=[{type,value}] with type one of iban, gtin, aba, lei, bic, gln, sscc, isin, cusip. Each result (in input order, with index + type) carries valid/reason plus the same type-specific fields the single endpoints return. One bad value or unsupported type degrades to that item only. Collapses a whole record of checksum checks into one round-trip.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
itemsYesIdentifiers to validate; each {type, value}.
Behavior4/5

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

Without annotations, the description provides key behavioral details: deterministic, supports up to 100 items, error isolation ('One bad value... degrades to that item only'), output order, index+type, and type-specific fields. It does not discuss authentication or rate limits, but it is thorough for a validation tool.

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

Conciseness5/5

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

The description is four succinct sentences, each serving a purpose: capacity and determinism, input format and types, output and error behavior, and summary benefit. No redundancy or irrelevant information.

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

Completeness5/5

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

Given no output schema and a single parameter, the description fully covers input, output, error handling, and usage context. It explains how the tool differs from sibling single validators and how results are structured, making it complete for an agent.

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 description adds context beyond the schema: it explains the input format (items=[{type,value}]), lists allowed types, and describes the output structure (index+type, valid/reason, type-specific fields). With 100% schema coverage, this provides actionable usage details.

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 'Validate up to 100 mixed identifiers in one deterministic call,' specifying the action, resource, and capacity. It explicitly lists the supported types, distinguishing it from sibling single-validator tools like validate.iban.

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?

It indicates when to use: for batch validation instead of multiple round-trips, and mentions 'Collapses a whole record of checksum checks into one round-trip.' It does not explicitly exclude single identifiers or name alternatives, but the sibling context implies the alternative single validators.

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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