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Rank NIH institutions (RPG research)

rank_institutions
Read-onlyIdempotent

Use this tool when the user asks which institutions get the most NIH money — 'top NIH-funded universities', 'where does NCI money go', 'rank research hospitals by R01 funding'. Each ranked row also yields its entity_id, the canonical institution identifier. Ranks institutions by competitive RPG-research NIH funding (R01 baseline), excluding intramural/contracts/centers/career/training, de-duplicated on core_project_num; NULL total_funding is not reported, never $0. total_funding here is RPG-research-only and is NOT comparable to the all-mechanism NIH totals served elsewhere. Bounds: limit 1-50 (default 20), offset 0-100000, fiscal years 1985-2100, ic 2-64 chars (NIH abbreviation or code, e.g. NCI or CA), sort_by one of composite | funding_scale | portfolio_breadth | new_grant_activity | avg_award_size.

Input Schema

NameRequiredDescriptionDefault
icNo
limitNo
offsetNo
sort_byNocomposite
fiscal_year_endNo
fiscal_year_startNo

Output Schema

NameRequiredDescriptionDefault

No arguments

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

A4.8/5.0
Behavior5/5

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

Annotations already declare the read-only/idempotent safety profile, and the description adds substantial context on top: the RPG-research-only scope, exclusions (intramural/contracts/centers/career/training), de-duplication on core_project_num, and the rule that NULL total_funding is omitted rather than shown as $0. The comparability caveat prevents a serious downstream misreading.

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?

Front-loaded with the when-to-use trigger, followed by output, methodology, the comparability warning, and bounds. Dense but every sentence adds decision-relevant information with no filler.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness5/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

With an output schema present, the description needn't explain return shape, yet it still notes the ranked rows yield entity_id. Combined with full bounds and scope caveats, an agent has everything needed to invoke this correctly.

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 carries the full burden and does so: it documents limit (1-50, default 20), offset (0-100000), fiscal years (1985-2100), ic format (2-64 chars, abbreviation or code) with examples, and enumerates all five sort_by values. This is near-complete parameter documentation despite the empty schema.

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 states a specific verb and resource ('Ranks institutions by competitive RPG-research NIH funding') and immediately scopes it with the R01 baseline and exclusions. It is clearly distinguishable from siblings like get_institution_profile or institution_concentration.

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?

It gives explicit triggering conditions with concrete user phrasings ('top NIH-funded universities', 'rank research hospitals by R01 funding'). It also warns the totals are not comparable to all-mechanism figures 'served elsewhere', but it never names the specific sibling tool an agent should switch to, so it stops short of full when-not/alternative routing.

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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