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American Default Research

get_county_scorecard

Read-onlyIdempotent

Fetch a county's County Distress Index (CDI) scorecard by 5-digit FIPS code. Returns the 0-100 score (the share of the other U.S. counties with a lower composite, rounded down; field composite_score), score label, national + state rank (national_rank_ordinal is filled only for the top and bottom 100, where the site prints it), 5-domain breakdown (Delinquency, Default & Legal, Debt Burden, Labor, Safety Net & Buffer), key findings, and pre-baked APA / MLA / Chicago / news-copy citations. Accepts 4-digit FIPS with implicit leading zero. 3,144 counties available.

Input Schema

NameRequiredDescriptionDefault
fipsYesThe 5-digit numeric county FIPS code as a string (e.g., '13063' for Clayton County, GA). 4-digit values are zero-padded internally. 3,144 counties available.

Schema Changelog

Changes observed during successful MCP inspections.

  1. Changed1 schema field changed
    • addedInput schema / properties / fips / description
      Added value: +"The 5-digit numeric county FIPS code as a string (e.g., '13063' for Clayton County, GA). 4-digit values are zero-padded internally. 3,144 counties available."
  2. First observed

TDQS

A4.2/5.0
Behavior5/5

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

Annotations already declare readOnly, idempotent, non-destructive behavior, and the description adds substantial context beyond them: the meaning of the 0-100 score, that national_rank_ordinal is only populated for the top/bottom 100, the five domain breakdown, and citation formats. This is exactly the behavioral detail an agent needs to interpret results correctly.

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?

The description is front-loaded with purpose and packed with useful return-value detail. It is dense rather than bloated, though the closing '3,144 counties available' repeats schema content and the return-field list could be structured more scannably.

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?

With no output schema, the description carries the burden of explaining return values, and it does so thoroughly: score meaning, rank behavior, domain breakdown, findings, and citations. Combined with annotations covering safety, nothing essential is missing for correct invocation.

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 coverage is 100% and the single parameter already documents the 5-digit string format, zero-padding, and county count. The description restates the 4-digit acceptance and availability, adding little beyond the schema, so baseline 3 is appropriate.

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 states a specific verb (Fetch), resource (a county's County Distress Index scorecard), and access key (5-digit FIPS code). It is clearly distinguishable from sibling indicator and composite tools without needing to open the schema.

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?

Usage is implied by the precise resource description, but there is no explicit when-to-use guidance, no exclusions, and no routing to alternatives such as get_adi_composite or get_indicator. An agent can infer the use case, but the description does not actively guide selection.

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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