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lapin7771n

Wallet BudgetBakers MCP

by lapin7771n

get_record_rules

Retrieve auto-categorization rules that automatically assign categories to matching transactions. Filter by rule ID, name, or date to pinpoint specific rules.

Instructions

Get auto-categorization rules for records.

These rules automatically assign categories/labels to matching transactions.

Args: ctx: MCP context limit: Items per page (1-100, default 30) offset: Items to skip rule_id: Filter by exact rule ID name: Filter by rule name (use prefix: eq., contains., contains-i.) created_at: Filter by creation date (e.g. "gte.2025-01-01") updated_at: Filter by last update date (e.g. "gte.2025-01-01")

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
nameNo
limitNo
offsetNo
rule_idNo
created_atNo
updated_atNo

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes
Behavior3/5

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

With no annotations, the description carries the full burden. It discloses pagination parameters (limit/offset) and filter syntax, which is useful. However, it doesn't mention sorting, combination rules, or other operational behaviors beyond basic parameter ranges.

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 front-loaded with a clear purpose, followed by a structured Args list where every line adds value. It's a bit lengthy but not wasteful; no unnecessary filler.

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?

For a 6-parameter read-only list tool, the description covers parameter semantics, pagination, and filtering well. The output schema exists to describe return shape, so not explaining it is fine. Minor gaps like sorting or filter combination rules exist, but overall it's sufficient for an agent to select and invoke this tool.

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?

The input schema has zero descriptions, but the tool description compensates fully. It explains limit range/default, offset semantics, rule_id exact matching, name filter prefixes (eq., contains., contains-i.), and date filter formats with examples—significantly more than the schema provides.

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

Purpose4/5

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

The description clearly states the tool 'gets auto-categorization rules for records' and explains what those rules do. This is a specific verb+resource pairing, though it doesn't explicitly distinguish itself from sibling tools like get_categories or get_labels.

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?

The description implies the tool is used when retrieving auto-categorization rules, but gives no explicit guidance about when to use it versus alternatives, nor any when-not examples. The context is implied rather than spelled out.

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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