College Scorecard

get_school_detail

Get detailed data for a specific college or university.

Returns comprehensive information including costs, admissions, demographics,
earnings outcomes, financial aid, debt levels, and completion rates.
Use school IDs from search_schools results.

Args:
    school_id: The College Scorecard school ID (integer). Find IDs via search_schools.

Input Schema

TableJSON Schema

Name	Required	Description	Default
`school_id`	Yes

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?

No annotations are provided, so the description carries the burden. It states 'Returns comprehensive information' which implies a read-only operation, and the verb 'get' reinforces safety. However, it does not explicitly mention side effects, auth, or error behavior, though for a simple get tool these may not be necessary.

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 and front-loaded, immediately stating purpose. The Args section is precise with no filler, and each sentence adds value (purpose, return categories, and parameter source).

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 tool is simple with one parameter and an output schema exists, so the description need not detail return structure. It already lists the types of data returned and mentions the prerequisite from search_schools, making it sufficiently complete for an agent to select and invoke it.

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 coverage is 0%, so the description must compensate. It adds meaning by explaining 'The College Scorecard school ID (integer)' and directs users to 'Find IDs via search_schools,' providing both origin and how to obtain the value, which goes beyond the schema's bare type.

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?

Description begins with 'Get detailed data for a specific college or university,' clearly stating the verb and resource. It distinguishes itself from siblings by focusing on a single school's comprehensive data, unlike search_schools (search) or compare_schools (comparison).

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 gives clear context: 'Use school IDs from search_schools results,' indicating a prerequisite and a workflow. It does not explicitly mention alternatives or when not to use the tool, but the context is enough to guide an agent.

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

A4.4/5.0

Disambiguation5/5

Each tool has a clearly distinct purpose: searching for schools, retrieving comprehensive details for one school, comparing multiple schools, and accessing field-of-study data. Even though get_school_detail and compare_schools both return earnings metrics, the descriptions and use cases (single vs. multiple schools) make them unambiguous.

Naming Consistency5/5

All tool names follow a consistent verb_noun pattern in snake_case: search_schools, get_school_detail, compare_schools, get_field_of_study. There are no mixed conventions or vague names.

Tool Count5/5

With 4 tools, the server is well-scoped for its purpose. Each tool covers a distinct aspect of school data exploration (search, detail, comparison, field-level data), and the number falls comfortably within the ideal 3-15 range.

Completeness4/5

The tool set covers the core workflows: finding schools, retrieving detailed profiles, comparing schools, and examining field-of-study outcomes. Minor gaps exist, such as no support for historical trends or advanced filtering (e.g., by tuition range or size), but the surface is adequate for typical college research tasks.

Resources

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