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Explain how matching works

explain_matching
Read-onlyIdempotent

Explains how PreShiftIQ computes matches: disqualification first, then measured-fit scoring, with every match recorded immutably. Includes the live tier thresholds and the fit-index note. Use this when a user asks how matches are computed or what a match score means.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
vertical_idNo

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
tiersYes
summaryYes
how_it_works_urlYes
boundary_statementYes
additive_index_noteYes
immutable_record_noteYes
disqualification_firstYes

Schema Changelog

Changes observed during successful MCP inspections.

  1. Changed1 schema field changed
    • changedInput schema / properties / vertical_id / enum
      Previous value: -[
      -  "tms",
      -  "dock-scheduling",
      -  "eld",
      -  "carrier-vetting",
      -  "fleet-management"
      -]New value: +[
      +  "tms",
      +  "dock-scheduling",
      +  "eld",
      +  "carrier-vetting",
      +  "fleet-management",
      +  "supply-chain-procurement",
      +  "yard-management"
      +]
  2. First observed

TDQS

A3.8/5.0
Behavior4/5

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

Annotations already cover the safety profile (readOnly, idempotent, non-destructive, non-open-world). The description adds domain behavior beyond annotations by noting that the explanation includes live tier thresholds and that matches are recorded immutably, which helps the agent understand what content the tool produces.

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, front-loaded with the core purpose, then content details, then usage guidance. Every sentence adds distinct value with no redundancy.

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?

With an output schema present and annotations covering safety, the description focuses appropriately on what the tool explains and when to use it. The main gap is the unexplained vertical_id parameter, but for a simple read-only explain tool the definition is otherwise complete.

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

Parameters2/5

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

The single parameter vertical_id has 0% schema description coverage, so the description must compensate but does not mention the parameter at all. The enum values hint at meaning, but the description adds no guidance on how vertical_id selects or filters the explanation.

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 verb and resource ('Explains how PreShiftIQ computes matches') and details the content covered: disqualification, measured-fit scoring, immutability, tier thresholds, and the fit-index note. This clearly distinguishes it from retrieval tools like my_matches or broad overview tools like describe_platform, though no sibling is named explicitly.

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?

It provides an explicit trigger: 'Use this when a user asks how matches are computed or what a match score means.' That is clear context for invocation, but it does not list when not to use it or name alternative tools for adjacent questions.

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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