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baonpNexle

AI_SYNC MCP Server

by baonpNexle

findStore

Search for relevant stores under a merchant using natural language queries to locate products or specific store information.

Instructions

Search for relevant stores under a merchant using a natural language query.

Args:
    merchantID: The merchant class to search under (e.g., "Tnc").
    queryText: A natural language description of the desired product or store.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
queryTextYes

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes
Behavior2/5

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

No annotations are provided, so the description carries the full burden of behavioral disclosure. It describes the tool as a search operation, which implies it's read-only and non-destructive, but doesn't explicitly state this or cover other traits like authentication needs, rate limits, or response format. The description adds minimal context beyond the basic operation, failing to compensate for the lack of annotations.

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 appropriately sized and front-loaded: the first sentence clearly states the tool's purpose. The Args section adds necessary details but includes an extraneous parameter ('merchantID') not in the schema, slightly reducing efficiency. Overall, it's concise with minimal waste, though the inconsistency detracts from perfect structure.

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?

Given the tool's moderate complexity (a search operation with 1 parameter) and the presence of an output schema (which should cover return values), the description is somewhat complete. It explains the purpose and parameter semantics but lacks behavioral details (e.g., read-only nature, error handling) and has a parameter inconsistency. This makes it adequate but with clear gaps, especially in compensating for the absence of annotations.

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?

The input schema has 1 parameter ('queryText') with 0% description coverage, meaning the schema provides no details. The description adds semantics by explaining 'queryText' as 'A natural language description of the desired product or store,' which clarifies its purpose. However, it also mentions 'merchantID' in the Args section, which is not in the schema, creating confusion. This inconsistency reduces the score, as it doesn't fully compensate for the schema's lack of coverage.

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's purpose: 'Search for relevant stores under a merchant using a natural language query.' It specifies the verb ('Search'), resource ('stores under a merchant'), and method ('natural language query'). However, it doesn't explicitly differentiate from sibling tools like 'findAllStores' (which might list all stores without search) or 'addNewStore' (a write operation), so it falls short of a perfect score.

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 context by mentioning 'under a merchant' and 'natural language query,' suggesting it's for search scenarios. However, it lacks explicit guidance on when to use this tool versus alternatives like 'findAllStores' (e.g., for filtered vs. unfiltered results) or 'addNewStore' (for creation vs. search). No exclusions or prerequisites are stated, leaving room for ambiguity.

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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