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Glama

extract_govcontracts

Read-only

US federal contract awards from USASpending.gov. Search by company name (e.g. 'Palantir'), keyword, or NAICS code. Returns amounts, dates, agencies.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
urlYesCompany name, keyword, or NAICS code

Schema Changelog

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

  1. Added

TDQS

A4/5.0
Behavior3/5

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

Annotations already declare readOnlyHint=true and openWorldHint=true, covering the tool's safety and nature. The description adds that it returns amounts, dates, and agencies, which is useful but does not go into depth about data freshness, pagination, or limitations. This is modest value beyond 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 is three short sentences that front-load the main purpose, then succinctly list search options and return fields. No unnecessary words or redundancy; every sentence contributes to understanding.

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?

For a simple tool with one parameter and no output schema, the description covers the core purpose, accepted query types, and return fields. It does not describe the return structure, but the mention of amounts, dates, and agencies gives a sufficient high-level view for a basic extraction tool.

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 100% for the single parameter, and the description essentially repeats the schema's description while adding an example ('Palantir'). The parameter name 'url' is ambiguous and not clarified by the description, so the added value is minimal.

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 clearly identifies the tool as retrieving US federal contract awards from USASpending.gov, which distinguishes it from sibling extraction tools. It specifies concrete search dimensions (company name, keyword, NAICS code), making the purpose unambiguous and actionable.

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?

The description provides clear context: it is for US federal contract data and can be searched by company name, keyword, or NAICS code. However, it does not explicitly mention when not to use it or offer alternative tools, so it lacks explicit exclusions.

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

A3.9/5.0
Disambiguation5/5

Each tool targets a distinct data source (finance, GitHub, Hacker News, etc.), with clear separation and no overlap. An agent can easily distinguish which tool to use for a given source.

Naming Consistency4/5

Tools use a consistent verb_noun pattern with 'extract_' for data extraction and 'search_' for search functions. The outlier 'package_trends' is still descriptive and fits the theme, so the pattern is mostly predictable.

Tool Count5/5

11 tools is well-scoped for a data aggregation server. Each tool serves a clear purpose and the count is neither too sparse nor overwhelming.

Completeness4/5

The server covers a broad range of sources (finance, code, news, social, academia, jobs, packages). Minor gaps like missing Twitter or general news are acceptable given the breadth already provided.