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identity_resolve

Converts product identifiers between LS-style codes, customer styles, UPCs, and material codes. Provide a value, source system, and target system to match identities across systems.

Instructions

F3 — đổi mã giữa các hệ: LS-style ↔ style khách ↔ UPC ↔ mã vật tư.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
valueYes
marketNo
customerNo
to_systemYes
from_systemYes

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes

Schema Changelog

Changes observed during successful MCP inspections. Dates show when Glama detected each change.

  1. First observedv0.1.0

TDQS

D1.9/5.0
Behavior1/5

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

Annotations are completely absent, so the description carries full responsibility for behavioral disclosure. It does not mention whether the operation is read-only, what happens on failure, any side effects, or response format. The description adds nothing beyond the bare conversion statement.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness2/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is a single short sentence, which is concise but critically under-specified. It front-loads the core purpose but omits all essential operational details. This is not efficient conciseness; it is insufficient specification.

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

Completeness1/5

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

With 5 parameters (3 required) and no schema descriptions or annotations, the description is grossly incomplete. It does not clarify the expected input values, the meaning of market/customer, or the output structure. Even though an output schema exists, the description fails to provide any context needed to call the tool correctly.

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

Parameters1/5

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

Schema description coverage is 0%, and the description does not explain any of the five parameters (value, from_system, to_system, market, customer). The description only lists system names, giving no clue about expected value formats or the role of optional parameters. It fails to compensate for the missing schema descriptions.

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 states a specific action: converting codes between systems (LS-style, customer style, UPC, material code). It names the exact resource types, which clearly distinguishes it from file/Excel siblings. However, it does not explicitly contrast with any alternative, so it falls short of a 5.

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

Usage Guidelines1/5

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

There is no guidance on when to use this tool versus alternatives, no prerequisites, and no mention of which systems are supported or any constraints. The one-line description only states the core function, leaving the agent to infer usage context.

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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