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validate.batch

Batch-validate up to 100 mixed identifiers (IBAN, GTIN, ABA, LEI, BIC, GLN, SSCC, ISIN, CUSIP) in one call, returning per-item validity and specific reason fields.

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}.

Schema Changelog

Changes observed during successful MCP inspections. Dates show when Glama detected each change.

  1. Addedv1.77.0
  2. Removedv1.76.0
  3. First observedv1.0.0

TDQS

A4.6/5.0
Behavior5/5

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

Despite no annotations, the description fully discloses behavior: deterministic, returns results in input order with index and type, each result has valid/reason plus type-specific fields, and error handling degrades per item only. This is comprehensive.

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?

Three sentences, no wasted words. Front-loaded with purpose, then input/output structure, then error behavior. Every sentence earns its place.

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?

The description covers capacity, input format, output structure, and error handling. With no output schema, it provides sufficient context. Minor omission: no mention of what happens if input array is empty or entirely invalid, but overall complete.

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 input schema already covers the structure with 100% coverage, but the description adds value by enumerating the allowed types, explaining the output fields, and clarifying that errors affect only the bad item.

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 validates up to 100 mixed identifiers in one call, lists the supported types, and explicitly distinguishes it from single-endpoint validators by mentioning it collapses checksum checks into one round-trip.

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 explains when to use (batch validation with up to 100 mixed identifiers) and implies it saves round trips, but does not explicitly state when not to use it or mention alternatives like single-validate tools.

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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