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Frihet-io

Frihet MCP Server

by Frihet-io

Create Bank Categorization Rule

frihet_bank_rule_create

Automatically categorize bank transactions by creating rules with conditions (AND logic) and actions to assign categories, tags, or clients.

Instructions

Create a new bank auto-categorization rule. Rules apply automatically to matching incoming transactions. A rule has conditions (AND logic) and actions (assign category, tag, or client). Example: name='Mercadona groceries', condition description contains 'MERCADONA', action category='groceries'. / Crea una nueva regla de categorizacion automatica de transacciones bancarias. Las reglas aplican condiciones (logica AND) y acciones (categoria, etiqueta, cliente).

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
nameYesRule name for identification / Nombre de la regla
actionsYesActions to apply when rule matches / Acciones a aplicar cuando la regla se cumple
isActiveNoWhether the rule is active (default true) / Si la regla esta activa (por defecto true)
conditionsYesRule conditions (AND logic — all must match) / Condiciones (logica AND — todas deben cumplirse)

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Behavior4/5

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

Annotations already indicate mutation (readOnlyHint=false) and non-destructiveness. The description adds that rules apply automatically and use AND logic, providing helpful behavioral context beyond annotations.

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 with three sentences and an example. It is front-loaded with purpose. The bilingual version adds no harm but is not essential. Every part serves a purpose.

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 presence of an output schema and full parameter descriptions, the description covers the essential logic and provides an example. It does not mention prerequisites or error cases, but overall is sufficient for use.

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?

With 100% schema description coverage, baseline is 3. The description adds an example and explains the AND logic for conditions, enhancing understanding beyond schema fields.

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 creates a bank auto-categorization rule. It distinguishes from siblings like 'frihet_bank_rules_list' by focusing on creation. The example illustrates the purpose well.

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 explicitly states when to use the tool (to create a rule) and provides an example. It does not discuss when not to use or alternatives, but the context is clear.

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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