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Glama

Medicare Provider Exposure

medicare_provider_exposure
Read-onlyIdempotent

Return a bounded sample of provider-level Medicare fee-for-service rows for one HCPCS code, optionally filtered by state, with the authoritative matching-row count. This is not a provider ranking and excludes suppressed/non-FFS activity.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
yearNo
limitNoSample rows (1-100, default 25).
stateNo
offsetNo
hcpcs_codeYes

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
yearYes
sourceYes
returnedYes
providersYes
hcpcs_codeYes
matching_rowsYes
interpretationYes

Schema Changelog

Changes observed during successful MCP inspections. Dates show when Glama detected each change.

  1. Added

TDQS

A4/5.0
Behavior4/5

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

Beyond the annotations (readOnlyHint, idempotentHint), the description adds that the tool excludes suppressed/non-FFS activity and that it provides a bounded sample rather than a full ranking. This provides useful behavioral context without contradicting the annotations.

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 consists of two well-structured sentences. The first sentence conveys the core purpose and key details, and the second adds clarifying exclusions. There is no unnecessary information.

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?

The description is fairly complete given the presence of an output schema and clear annotations. It explains the sample nature, exclusion criteria, and key filters. However, it does not mention the year or offset parameters, though the output schema likely covers return format.

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?

The description adds meaning to parameters by explaining that the tool returns data for one HCPCS code, optionally filtered by state, and that it provides a match count. However, with only 20% schema description coverage, the description does not fully compensate for the lack of details on parameters like year and offset.

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 explicitly states the tool returns a bounded sample of provider-level Medicare FFS rows for a single HCPCS code, with optional state filtering and an authoritative match count. This specifies a clear verb, resource, and scope, and it distinguishes itself from siblings by stating it is not a provider ranking and excludes suppressed/non-FFS activity.

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 usage context through phrases like 'bounded sample' and 'not a provider ranking,' but it does not explicitly state when to use this tool versus specific sibling alternatives. There are no explicit when-to-use or when-not-to-use guidelines beyond one brief exclusion.

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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TDQS

A3.5/5.0
Disambiguation2/5

The server mixes Medicare-specific tools with many unrelated general-purpose tools (e.g., bet_research, polymarket_arbitrage, remember), and there are multiple similar ask_pipeworx variants. This makes it difficult for an agent to distinguish which tool is appropriate for a given task without confusion.

Naming Consistency2/5

Tool names follow no consistent pattern. Some use a medicare_ prefix with underscores, others use generic verbs like forget, recall, or compound names like ask_pipeworx, deep_research. There is no uniform verb_noun or noun_verb structure.

Tool Count2/5

57 tools is excessive for a server ostensibly focused on 'Medicare Coverage'. Many tools (e.g., bet_research, polymarket_edge_tracker, scan_dependency) are unrelated to Medicare and should be in separate servers, inflating the count and diluting focus.

Completeness4/5

The Medicare-specific tools cover a broad range: NCDs, LCDs, NCAs, enrollment, DME, Part D, hospital, outpatient, post-acute, and provider data. Minor gaps include Medicare Advantage (Part C) and Medicare Supplement, but the coverage is largely comprehensive.