NCES Education Data

get_district_finance

Get district-level financial data: total revenue, expenditures, per-pupil spending, federal/state/local revenue breakdown.

Returns fiscal data from the CCD School District Finance Survey (F-33),
including revenue sources, expenditure categories, and per-pupil spending.

Args:
    state: Two-letter US state abbreviation (e.g. 'CA', 'NY').
    county_fips: Optional 5-digit county FIPS code to filter by county.
    year: Fiscal year to query (default 2021). Finance data lags 1-2 years.
    limit: Maximum number of districts to return (default 50, max 500).

Input Schema

TableJSON Schema

Name	Required	Description	Default
`year`	No
`limit`	No
`state`	Yes
`county_fips`	No

Output Schema

TableJSON Schema

Name	Required	Description	Default
`result`	Yes

TDQS

A4.3/5.0

Behavior3/5

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

With no annotations, the description carries the burden and does add valuable context: it names the data source (CCD F-33 survey) and notes that finance data lags 1-2 years. However, it does not explicitly state it is read-only, mention pagination beyond a limit parameter, or disclose any other operational behaviors like rate limits or authorization requirements.

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 compact, front-loaded with the main purpose, and organized with an Args block. Each sentence adds value; the minor repetition of 'per-pupil spending' is harmless and reinforces key data points.

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 covers parameters and behavioral lag well, and the presence of an output schema handles return values. It does not discuss edge cases or pagination beyond limit, but given the simplicity of the tool and the schema richness, this is adequate.

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

Parameters5/5

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

Schema description coverage is 0%, so the description fully compensates by documenting all four parameters with formats, defaults, and constraints (e.g., state abbreviation, county FIPS code, year lag, limit max). This is exactly what the input schema lacks.

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 opens with a specific verb and resource: 'Get district-level financial data' and enumerates the exact data types (total revenue, expenditures, per-pupil spending, federal/state/local revenue breakdown). This clearly distinguishes it from sibling tools like get_district_overview or get_graduation_rates, which cover different domains.

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 clearly implies this tool is for financial data queries, but it does not explicitly mention when not to use it or point to alternatives like the siblings. It provides sufficient context for an agent to infer usage, but lacks explicit exclusions or alternative recommendations.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

All NCES Education Data tools Inspect

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TDQS

A4.4/5.0

Disambiguation5/5

Each tool targets a distinct data type: finance, directory overview, graduation rates, demographics, and school directory. Although some tools overlap in attributes (e.g., enrollment in get_schools and get_school_demographics), the level of detail and purpose are clearly separated.

Naming Consistency5/5

All tool names follow a consistent 'get_' prefix and snake_case convention, with predictable patterns like get_district_finance and get_school_demographics. This makes the set easy to navigate.

Tool Count5/5

The server has 5 tools, which is well within the ideal range for a focused data retrieval domain. Each tool covers a meaningful aspect of NCES education data without being redundant or overwhelming.

Completeness4/5

The set covers key K-12 data categories: finance, demographics, graduation, and directory information. Minor gaps (e.g., district-level demographics, state-level aggregates, or test scores) exist, but the core data types are well represented and there are no dead ends.

Resources

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