systemlink-mcp

summarize_yield

Summarize pass/fail yield from test results using filters for part number, program name, serial, status, and time range. Optionally group yield by part, program, or serial.

Instructions

Summarize pass/fail yield for test results.

Uses Test Monitor result-level status, not CMMS work-order counts. Filters are pushed to the server as Dynamic LINQ (partNumber, programName, serialNumber, status.statusType, startedAt). Yield is passed / (passed + failed).

part_number: Product revision / part number, e.g. PN-5164-B. program_name: Test program or sequence name, e.g. BoardFunctional.seq. serial_number: DUT serial. status: Optional status.statusType filter (PASSED, FAILED, ERRORED, ...). started_after: Inclusive ISO-8601 UTC start, e.g. 2026-01-01T00:00:00Z. started_before: Inclusive ISO-8601 UTC end. group_by: Break yield down by part_number, program_name, serial_number, or none.

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": "summarize_yield"
  }
}

Input Schema

Name	Required	Default
`status`	No
`group_by`	No	none
`part_number`	No
`program_name`	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?

Notes that it uses Test Monitor result-level status rather than CMMS work-order counts and mentions server-side Dynamic LINQ filtering, adding context beyond basic operation.

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?

Well-structured with a brief intro and parameter list, but the explanations are somewhat repetitive without being bloated; still efficient.

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?

Covers filtering, grouping, and data source, and the output schema exists, so no need to explain return values; lacks explicit edge-case or error handling info but is adequate.

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?

Provides clear explanations and examples for all 7 parameters, covering meaning, format, and usage, which significantly supplements the bare 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?

Clearly states it summarizes pass/fail yield for test results and distinguishes from CMMS work-order counts, making its purpose unambiguous.

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?

Implies usage via the filter parameters and the yield summary function, but does not explicitly contrast with sibling tools like query_results or summarize_measurement.

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

Deploy Server