Skip to main content
Glama
HorizunGroup

Horizun PBI MCP

Official
by HorizunGroup

pbi_check_contract

Read-only

Validate an incoming file before loading or the active model against the port contract: detect missing columns, incompatible types, absent keys, and receive suggested critical fields.

Instructions

Valida contra el contrato del puerto: un archivo entrante o el modelo.

Con source_path (+ dataset): el export de Revit/Navisworks/Project ANTES de cargarlo — columnas que faltan, tipos incompatibles, llave ausente. Chequeo ESTRUCTURAL y honesto: unicidad y huerfanas de la llave exigen los datos completos, y eso es pbi_diagnose_data con la tabla ya cargada; la respuesta lo dice en not_checked.

Sin source_path: el MODELO activo contra el contrato entero, y el circulo que cierra todo: suggested_critical_fields — las llaves del puerto listas para pbi_define_brief, de modo que el diagnostico las trate como criticas del dueño sin teclearlas dos veces.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
datasetNo
request_idNo
source_pathNo

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes
Behavior5/5

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

Annotations declare readOnlyHint=true, and the description adds context: it is a structural and honest check, explicitly stating that key uniqueness/orphans are not checked when data are incomplete, and that the response communicates this via `not_checked`. It also reveals the output field `suggested_critical_fields`, providing behavior beyond the annotation.

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

Conciseness4/5

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

The description is structured into two clear mode-based paragraphs, with the main purpose front-loaded. It is somewhat dense but every sentence contributes meaning, referencing related tools and limitations without fluff.

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?

Given the two-mode complexity and the existence of an output schema, the description covers the main use cases, limitations, and integration with pbi_diagnose_data and pbi_define_brief. It does not explain `request_id`, which is a minor completeness gap, but overall it provides sufficient context for an agent to invoke the tool correctly.

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

Parameters3/5

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

Schema coverage is 0%, so the description must explain parameters. It clarifies `source_path` as the mode selector and `dataset` as an add-on to `source_path`, but it does not mention `request_id` at all. This leaves one of three parameters undocumented, a notable gap.

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 it validates against the port contract, either an incoming file or the active model. It distinguishes itself from pbi_diagnose_data by explaining the different scope (pre-load structural checks vs. full data checks). The verb 'Valida' is specific and the resource is well-defined.

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

Usage Guidelines5/5

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

It gives explicit usage conditions: with `source_path` (+ `dataset`) for pre-load file validation, without `source_path` for model validation. It also names an alternative (pbi_diagnose_data) for key uniqueness/orphans and the follow-up tool pbi_define_brief, forming a clear workflow.

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

Install Server

Other Tools

Latest Blog Posts

MCP directory API

We provide all the information about MCP servers via our MCP API.

curl -X GET 'https://glama.ai/api/mcp/v1/servers/HorizunGroup/horizun-pbi-mcp'

If you have feedback or need assistance with the MCP directory API, please join our Discord server