USASpending.gov

autocomplete_awarding_agency

Read-only

Find awarding agency names by partial match.

USASpending search filters require the EXACT awarding agency name
(slugs return zero). Use this to resolve a partial name to the canonical
one before passing to search_awards() awarding_agency parameter.

Tool call template

Replace each placeholder with a value matching the input schema. Only required parameters are included; add optional parameters as needed.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {
      "search_text": "<search_text>"
    },
    "name": "autocomplete_awarding_agency"
  }
}

Input Schema

Name	Required	Description	Default
`limit`	No
`search_text`	Yes

Output Schema

Name	Required	Description	Default
No arguments

Schema Changelog

Changes observed during successful MCP inspections.

First observedOct 21, 2026

TDQS

A4.2/5.0

Behavior4/5

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

Annotations already declare readOnlyHint, openWorldHint and non-destructive, so safety is covered. The description adds meaningful behavioral context about the underlying data: results are canonical names and the downstream filters reject non-exact input.

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?

Three short lines, front-loaded with purpose, then rationale, then the concrete call pattern. No filler or redundant restatement.

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 two-parameter lookup with an output schema, the description covers purpose, motive and integration point. Only the limit parameter's meaning and paging behavior are left implicit.

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 0%, so the description must compensate. It conveys that search_text is a partial-match string, but says nothing about the limit parameter or its default of 10, leaving half the parameters unexplained.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose4/5

Does the description clearly state what the tool does and how it differs from similar tools?

States a specific verb and resource ("Find awarding agency names by partial match"), which is clear. However it never distinguishes itself from the sibling autocomplete_funding_agency, which an agent could easily confuse with it.

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?

Explicitly says when to use it — resolve a partial name before passing to search_awards() awarding_agency — and explains why (exact names required, slugs return zero). That linkage to the downstream tool is unusually actionable guidance.

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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