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berthelius

Frihet MCP Server

Search Invoices

search_invoices
Read-onlyIdempotent

Search and filter invoices by status, date range, and text query across client names and invoice content.

Instructions

Search and filter invoices. Supports filtering by status and date range. The query parameter searches across client names and invoice content. Example: query='Acme', status='paid', from='2026-01-01', to='2026-03-31' / Busca y filtra facturas. Soporta filtrado por estado y rango de fechas. El parametro query busca en nombres de clientes y contenido de facturas.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
toNoEnd date filter (YYYY-MM-DD) / Fecha fin
fromNoStart date filter (YYYY-MM-DD) / Fecha inicio
afterNoCursor for cursor-based pagination (document ID) / Cursor para paginacion
limitNoMax results (1-100) / Resultados maximos
queryNoSearch text (client name, etc.) / Texto de busqueda
fieldsNoComma-separated field names to return / Campos a devolver
offsetNoOffset / Desplazamiento
statusNoFilter by status / Filtrar por estado

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
dataYes
limitYes
totalYes
offsetYes
nextCursorNo
Behavior2/5

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

Annotations already declare readOnlyHint=true, idempotentHint=true, destructiveHint=false, so the description adds minimal behavioral context beyond restating these traits. The description does not explain return behavior, pagination handling, or other operational details that would increase transparency.

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 concise, front-loaded with English followed by Spanish, and includes a helpful example using all five main parameters. Every sentence is useful, with no redundancy or waste.

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

Completeness3/5

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

While the tool has 8 parameters and an output schema, the description omits details about pagination (cursor, offset, limit) and field selection. The example is good but does not cover all aspects of the tool's functionality, leaving some gaps for a comprehensive agent usage.

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?

Schema coverage is 100% with each parameter described, but the description adds value by clarifying the query parameter's role ('searches across client names and invoice content') and providing a concrete example that combines parameters, which aids understanding beyond the schema alone.

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's purpose ('Search and filter invoices') with specific capabilities (filtering by status and date range, query across client names and invoice content). It distinguishes from sibling tools like list_invoices by its filtering and search focus.

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

Usage Guidelines3/5

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

Usage is implied through the description of filtering and search functionality, but there is no explicit guidance on when to use this tool versus alternatives like list_invoices or other search tools. No when-not or alternative recommendations are provided.

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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