Ready APIs

Location Intelligence Score

location_score

Read-onlyIdempotent

Composite hiring-location score (0-100) for a US ZIP, weighted by role profile (engineering, sales, operations, warehouse, retail, remote). Joins Census ACS demographics, FEMA flood, IECC climate, FAA airport, BEA cost-of-living, and state income tax into one tuned signal. Returns overall score, tier, verdict, and six sub-scores with notes.

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": {
      "zip": "<zip>"
    },
    "name": "location_score"
  }
}

Input Schema

Name	Required	Description	Default
`zip`	Yes	U.S. ZIP code, for example 10001.
`role`	No	Role profile that tunes the sub-score weights.	engineering
`year`	No
`filing_status`	No		single

Schema Changelog

Changes observed during successful MCP inspections.

First observedAug 14, 2026

TDQS

A3.7/5.0

Behavior4/5

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

Annotations already declare the tool read-only, non-destructive, and idempotent; the description is consistent with these. The description adds valuable behavioral context by naming the joined data sources (Census, FEMA, IECC, FAA, BEA, state tax) and the exact return components. It does not cover error or edge-case behavior, but the annotations already supply the safety profile.

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?

Two dense sentences pack purpose, inputs, data sources, and returns without redundant phrases. The key scoping constraint (US ZIP, role weighting) is front-loaded before the data-join details. No word is wasted.

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

Completeness3/5

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

For a medium-complexity tool with no output schema, the description gives enough for basic invocation: required ZIP, optional role, and return shape. However, it omits the meaning of year and filing_status, possible invalid-ZIP behavior, and how the score relates to nearby sibling tools. Overall viable but with identifiable gaps.

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

Parameters3/5

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

Schema description coverage is 50%: zip and role are described, and the description reinforces both (US ZIP, role-tuned weights). Year and filing_status remain semantically unexplained in both the schema and the description, despite their likely impact on state-income-tax calculations. The description partially compensates but does not fully close the gap.

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?

States a specific verb and resource: produces a composite hiring-location score (0-100) for a US ZIP with role-based weighting. The output details (overall score, tier, verdict, six sub-scores) make the purpose unmistakable among siblings. It does not explicitly call out a sibling alternative, so it stops short of a 5.

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 the tool is for evaluating a location for hiring based on role profile, but it never states when to prefer it over related tools like geo_zip_lookup, hiring_signal, jobs_concentration, or remote_hire_cost. No exclusions or alternative conditions are given. This is usable but relies on inference.

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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