systemlink-mcp

query_specs

Retrieve specification limits (min, typical, max, unit) for a product using its ID, with an optional preview limit to cap the number of specs returned.

Instructions

Query specification limits for a product (min / typical / max, unit).

product_id: Product id or, in simulation, the part number used as product_id. preview_limit: Max specs to include (capped at 50).

Tool call template

Replace each placeholder with a value matching the input schema. Only required parameters are included; add optional parameters as needed.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {
      "product_id": "<product_id>"
    },
    "name": "query_specs"
  }
}

Input Schema

Name	Required	Description	Default
`product_id`	Yes
`preview_limit`	No

Output Schema

Name	Required	Description	Default
No arguments

Schema Changelog

Changes observed during successful MCP inspections.

First observedv0.1.0Aug 21, 2026

TDQS

A4.3/5.0

Behavior4/5

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

With no annotations provided, the description carries the burden of behavioral disclosure. It adds useful context beyond the schema by explaining that product_id can be a simulation part number and that preview_limit is capped at 50. It does not mention error handling or permissions, but the query nature and output scope are reasonably transparent.

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 compact and front-loaded with the core purpose in the first sentence. The parameter explanations are brief and directly useful, with no filler or redundancy. Every sentence earns its place.

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?

Given the low complexity, the presence of an output schema, and the clear parameter explanations, the description is largely complete. It covers purpose, parameter behavior, and a key constraint (cap at 50). It could be slightly stronger with explicit guidance on when to choose this over sibling query tools, but overall it is sufficient.

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?

Schema description coverage is 0%, so the description must compensate, and it does. Both parameters are explained: product_id is defined as 'Product id or, in simulation, the part number used as product_id,' and preview_limit is described as 'Max specs to include (capped at 50).' This adds meaningful semantics beyond the raw 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 function: 'Query specification limits for a product' with specifics about the output (min / typical / max, unit). It distinguishes itself from siblings like query_products and query_results by focusing on specification limits rather than general product data or results.

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 when to use the tool: when you need specification limits for a product. However, it does not explicitly contrast with sibling tools like query_products or summarize_measurement, nor does it state when not to use it. The context is clear but the exclusion/alternative guidance is absent.

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

Deploy Server