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haydentbs

USAspending MCP Server

by haydentbs

Count USAspending Transactions

usaspending_count_transactions
Read-onlyIdempotent

Count US federal spending transactions grouped by award category (contracts, grants, loans, etc.) using filters like time period, agency, or keyword.

Instructions

Count matching transaction records grouped by award category: contracts, grants, direct payments, loans, IDVs, and other.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
filtersNoUSAspending AdvancedFilterObject. Common keys include time_period, keywords, agencies, recipient_search_text, award_type_codes, award_ids, naics_codes, psc_codes, and place_of_performance_locations. Specify an explicit time_period for time-sensitive analysis.
response_formatNoOutput format: markdown for readable summaries, json for raw structured data.markdown
Behavior4/5

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

Annotations already indicate read-only, idempotent, non-destructive behavior. The description adds that the tool groups results by award category, providing behavioral context beyond the annotations. No contradictions.

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 a single sentence that directly states the tool's purpose and key behavior. No unnecessary words, and it is efficiently front-loaded.

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?

Given the tool's simplicity (two parameters, no output schema, good annotations), the description adequately covers the core functionality and return structure. Minor improvement could be specifying the exact output format or example categories.

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%, so baseline 3 applies. The description does not add extra meaning to the parameters; it only explains the output grouping. The parameters are well-described in the schema itself.

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 states the tool counts transaction records and groups them by award category (contracts, grants, etc.). This specific verb+resource+grouping distinguishes it from siblings like search_awards or search_transactions which retrieve lists, not grouped counts.

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 use for grouped counts but does not explicitly state when to use this tool over alternatives like usaspending_spending_by_category or usaspending_search_awards. No exclusions or context for when not to use it are provided.

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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