systemlink-mcp

query_results

Query test results to return counts and a bounded preview of the newest matching records. Filter by part number, program, serial, status, or time range.

Instructions

Query test results and return counts plus a bounded recent preview.

Does not dump the full result set. Counts use Test Monitor return_count; the preview is the newest matching results only.

part_number: Product revision / part number. program_name: Test program or sequence name. serial_number: DUT serial. status: Optional status.statusType filter (PASSED, FAILED, ERRORED, ...). started_after: Inclusive ISO-8601 UTC start. started_before: Inclusive ISO-8601 UTC end. preview_limit: Max result rows to include (capped at 50).

Tool call template

This tool declares no required parameters. Add optional parameters from the input schema as needed.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {},
    "name": "query_results"
  }
}

Input Schema

Name	Required	Description	Default
`status`	No
`part_number`	No
`program_name`	No
`preview_limit`	No
`serial_number`	No
`started_after`	No
`started_before`	No

Output Schema

Name	Required	Description	Default
No arguments

Schema Changelog

Changes observed during successful MCP inspections.

First observedv0.1.0Aug 21, 2026

TDQS

A4.4/5.0

Behavior4/5

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

With no annotations, the description carries the transparency burden. It discloses that results are bounded, the preview is newest-only, preview_limit caps at 50, and date filters are inclusive ISO-8601 UTC. This provides solid behavioral context for a query tool, though it omits edge cases like empty-result behavior.

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 tightly structured: a one-sentence summary, two critical behavioral constraints, then concise parameter bullets. Every sentence provides necessary information without redundancy.

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?

The tool has a rich output schema, so return-value explanation is unnecessary. Given the 7 optional parameters and no required inputs, the description fully covers input semantics, behavioral boundaries, and the core query purpose.

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?

Even though schema description coverage is 0%, the description documents all 7 parameters with practical meaning and constraints: status filter examples, inclusive date semantics, and preview_limit cap. This adds significant value beyond the raw schema definitions.

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 a specific action ('Query test results') and defines the exact return shape ('counts plus a bounded recent preview'). It differentiates itself by noting it 'does not dump the full result set', distinguishing it from potentially broader query tools.

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 a summary plus limited preview is needed, and explicitly warns against expecting full result dumps. However, it never names alternative tools or provides explicit when-to-use vs when-not-to-use guidance against the sibling tools.

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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