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Medicare Fqhc Gaf

medicare_fqhc_gaf
Read-onlyIdempotent

What is the FQHC Geographic Adjustment Factor (GAF) for a place, and what does Medicare pay a Federally Qualified Health Center per visit THERE? Returns the official CMS FQHC PPS GAF for a Medicare locality and calendar year, and the GAF-adjusted per-visit rate (national base rate x GAF). Answers "FQHC PPS GAF for Orlando, Florida 2025", "CY2026 FQHC geographic adjustment Rest of California", "what is the FQHC PPS rate in Alaska". The GAF is CMS's own published number per locality (adapted from the work and practice-expense GPCIs, with the 1.0 floor), not something this tool estimates. A state returns all its localities; a city is not a locality, so name the locality or pick from the list (Florida has Fort Lauderdale, Miami and Rest of Florida). Complements medicare_fqhc_pps_rate (national base rate) and medicare_gpci_lookup (the underlying GPCIs). Years 2024-2026 loaded. Sourced from the CMS FQHC PPS geographic adjustment factor tables.

Input Schema

NameRequiredDescriptionDefault
yearNoCalendar year, 2024-2026. Omit for the newest loaded year (stated in the response).
localityNoState code ("FL"), state name ("Florida"), or Medicare locality name ("Fort Lauderdale", "Rest of Florida"). A bare state returns all of its localities.
locality_numberNoOptional Medicare locality number, e.g. "99"; with a state it pins one locality.

Output Schema

NameRequiredDescriptionDefault
hintNo
noteNo
yearNo
foundNo
reasonNo
sourceNo
formulaNo
data_as_ofNo
localitiesNo
loaded_yearsNo
base_rate_usdNo
locality_countNo
year_was_defaultedNo

Schema Changelog

Changes observed during successful MCP inspections.

  1. Added

TDQS

A4.6/5.0
Behavior4/5

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

Annotations already declare readOnly/idempotent/openWorld/non-destructive, so safety is covered. The description adds real behavioral context beyond that: the GAF is CMS's own published figure (not an estimate), it carries a 1.0 floor, a state returns all its localities, and years 2024-2026 are loaded.

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?

Front-loads the core question and answer, then layers examples, sourcing, and routing. It is somewhat long with repeated locality examples, but nearly every sentence earns its place by clarifying behavior or routing.

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?

An output schema exists, so return values needn't be described. Combined with full schema coverage and annotations, the description supplies everything an agent needs: what it returns, how to name localities, year range, and how it relates to sibling tools.

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

Parameters4/5

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

Schema coverage is 100%, so the baseline is 3, but the description adds meaning beyond the schema: the locality-vs-city distinction, that a bare state returns all localities, and that omitting year yields the newest loaded year. This is genuinely useful disambiguation the schema alone doesn't convey.

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?

States a specific verb and resource: returns the CMS FQHC PPS GAF for a locality/year plus the GAF-adjusted per-visit rate. It explicitly distinguishes itself from siblings medicare_fqhc_pps_rate (national base rate) and medicare_gpci_lookup (underlying GPCIs), so an agent can route without opening a schema.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines5/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

Gives concrete trigger examples ("FQHC PPS GAF for Orlando, Florida 2025") and names the alternative tools it complements. It also states a key usage constraint: a city is not a locality, so the caller must name a locality or pick from the list.

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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