check_pint_ae_fields

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

No annotations are provided, so the description must carry behavioral disclosure. It does reveal the non-destructive evaluation nature (returns statuses, completion %, gaps), which implies it does not modify the invoice. However, it does not state whether validation requires network access, whether it follows the full PINT AE business rules or only the field presence matrix, or what happens on invalid input beyond the statuses. Average transparency for an evaluator tool.

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

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

A single, information-dense sentence front-loads the action, the target, and the output format. Every clause adds value: 'Evaluate invoice JSON', '51-field UAE e-invoice / PINT AE mandatory field matrix', and the return values. Nothing is wasted and no filler is present.

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

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

Given one parameter with a nested schema and a clear output description, the tool definition gives enough for an agent to understand the input and the returned statuses. There is no output schema, so the description's mention of present/missing/invalid/not_applicable and completion % covers the return contract well. Missing details are the exact 51 fields and how to interpret 'not_applicable' (e.g., credit notes vs invoices), but these are not necessary for a basic call.

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

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

Schema description coverage is 0%, so the description must compensate. The sole parameter invoiceData is clearly described as 'invoice JSON' and the description's mention of the 51-field matrix and per-field statuses implies the nested structure. The schema itself already provides the nested fields, so the description adds the meaning of the parameter as the input subject of evaluation. Some deeper semantics—such as whether the tool accepts partial invoices or expects the full invoice object—are not spelled out, so slightly below a 5.

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

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

The description clearly identifies a specific verb ('Evaluate'), a specific resource ('invoice JSON'), and a precise scope ('51-field UAE e-invoice / PINT AE mandatory field matrix'). It also distinguishes the output (per-field status, completion %, gaps), so an agent can understand exactly what this validation tool does and how it differs from generic compliance checks.

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

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

The description states what the tool evaluates but does not explicitly say when to use it versus sibling tools such as check_invoice_compliance or generate_pint_ae_xml. However, the phrase 'mandatory field matrix' plus the explicit output of missing/invalid/not_applicable status makes it clear this is a field-level pre-validation step before XML generation. It lacks explicit exclusions but provides enough context for an agent to select it.

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