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Taokeh MCP server

Find product

resolve_product
Read-only

Resolve a product by name or SKU for an invoice line. Returns id, sku, name, unit and the default sell price the form would use. Plain names or SKUs work best. Statuses: resolved / ambiguous (candidates) / none — never guess among candidates.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
queryYes

Schema Changelog

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

  1. First observed

TDQS

A4.8/5.0
Behavior5/5

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

The description discloses return fields (id, sku, name, unit, default sell price), statuses (resolved/ambiguous/none), and the critical rule 'never guess among candidates.' This goes well beyond the readOnlyHint annotation by explaining how ambiguity is handled.

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 three sentences with no fluff: purpose, return values, and behavior. It is front-loaded with the core action and immediately useful details.

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

Completeness5/5

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

For a simple lookup tool with one parameter and no output schema, the description is complete. It specifies input semantics, output fields, statuses, and a safety rule against guessing, making the tool's behavior fully transparent.

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?

With 0% schema description coverage, the description fully compensates by explaining that 'query' accepts a product name or SKU, and that plain forms work best. This gives the agent the semantic meaning needed to invoke the tool correctly.

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 'Resolve a product by name or SKU for an invoice line,' using a specific verb and resource. It distinguishes from sibling tools like resolve_customer and resolve_vendor by explicitly targeting products.

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 phrase 'for an invoice line' provides clear usage context, and 'Plain names or SKUs work best' offers practical input guidance. However, it does not explicitly name alternatives or state when not to use this tool, so it falls short of a 5.

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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