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generate_documents

Create teacher verification documents like employment letters, teacher IDs, and teaching licenses. Provide teacher and school details to generate high-resolution PNGs for 13 countries.

Instructions

Generate teacher verification documents (employment letter, teacher ID, teaching license).

Args: country: Country code from list_countries (e.g. 'us', 'uk'). first_name / last_name: The teacher's name. school_name: Exact or partial school name (matched against that country's school list). position: Teaching position/title. date_of_birth: Display date of birth string (shown on the teacher ID). gender: 'Random', 'Male', or 'Female' — selects which photo pool is used. document_types: Which documents to render. Omit for all. e.g. ['employment_letter', 'teacher_id']. output_dir: Where to save PNGs (relative to project root). Defaults to 'output'.

Returns: Dict with 'files' (absolute paths), 'count', and 'output_dir'.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
genderNoRandom
countryYes
positionYes
last_nameYes
first_nameYes
output_dirNo
school_nameYes
date_of_birthYes
document_typesNo

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.1.0

TDQS

A4.6/5.0
Behavior4/5

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

With no annotations provided, the description carries the full burden and does well: it states that PNGs are saved, output_dir is relative to project root, gender selects a photo pool, and the return value is a dict with files/count/output_dir. Minor gaps remain around overwrite behavior and directory creation, but the key behavioral profile is disclosed.

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 organized into a one-line summary followed by a clean Args list and a Returns line. Every sentence contributes necessary behavior or parameter information; there is no filler or redundancy.

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?

For a 9-parameter tool with no annotations and no output schema, the description is remarkably complete: it covers every parameter, the output format, the file type, defaults, and the relationship to sibling list tools. An agent has enough information to call the tool correctly with minimal risk.

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

Parameters5/5

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

Schema description coverage is 0%, so every parameter must be explained in the description, and it is: country is tied to list_countries, school_name is matched against a school list, date_of_birth appears on the teacher ID, gender selects photo pools, and document_types can be omitted for all. It even adds defaults beyond the schema, such as output_dir defaulting to 'output'.

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 opens with a specific verb and resource: 'Generate teacher verification documents' and lists the three concrete document types (employment letter, teacher ID, teaching license). It also references sibling tools by name ('list_countries', 'school list'), so an agent can distinguish this generation tool from the list/helper tools without opening any schema.

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 gives clear usage context: country codes should come from list_countries, school_name is matched against the country's school list, and document_types can be omitted for all. It does not explicitly say when not to use the tool, but the prerequisites and relationship to the sibling data-lookup tools are clear.

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