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udaysrinu

ExpensifyAI

by udaysrinu

Resolve Category

resolve_category

Resolve an expense category name by fuzzy matching, returning matching categories and subcategories with IDs, names, and match scores for accurate expense classification.

Instructions

Fuzzy-match an expense category by name (e.g. "food", "utilities"). Returns matches with id, name, and match_score. Searches subcategories too.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
queryYes
thresholdNo

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.2.0

TDQS

B3.4/5.0
Behavior2/5

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

With no annotations provided, the description carries the full burden of disclosing behavior. It does mention 'fuzzy-match' and 'searches subcategories,' which are useful behavioral traits, but it does not explicitly state that the operation is read-only or describe any side effects, error behavior, or limitations. For a tool that likely performs a safe lookup, this omission is a significant gap.

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—two sentences with no filler. It front-loads the core purpose and adds the subcategory detail efficiently. Every sentence contributes to understanding the tool.

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?

The output schema exists, so return value details are not required. However, the tool has two parameters, and the threshold is unexplained. The description also lacks guidance on when to use this tool versus alternatives. For a moderate-complexity tool, this falls short of complete contextual guidance.

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

Parameters2/5

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

Schema description coverage is 0%, so the description must compensate for explaining parameters. It indirectly explains the 'query' parameter by saying 'by name,' but it does not mention the 'threshold' parameter at all—its meaning, default behavior, or how it affects matching. This leaves a required parameter's semantics entirely undocumented beyond the schema.

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: fuzzy-match an expense category by name, returns id, name, and match_score, and searches subcategories. It distinguishes from sibling tools like get_categories (which likely lists all categories) and resolve_friend/resolve_group by specifying the entity type and the fuzzy matching behavior.

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 usage when you have a category name to resolve, but it does not explicitly state when to use this vs alternatives like get_categories, or when not to use it. It lacks guidance on prerequisites or exclusion criteria, leaving the agent to infer the appropriate context.

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