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Glama

VetAid — VA Claim Intelligence

by ai.vetaid

VA appeal denial statistics

va_denial_stats
Read-onlyIdempotent

Corpus-wide VA appeal statistics from 1.9 million public Board of Veterans' Appeals decisions, 1992 to present, updated nightly: how every decided issue came out (granted / denied / remanded / dismissed / other), the year-by-year trend, and the most-litigated conditions with their own shares. Rates are shares of ALL decided issues, so they sum to 100%, and they use complete crawl years only (an all-years block is included and labelled). Aggregate data only — contains no individual veteran's information.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Schema Changelog

Changes observed during successful MCP inspections. Dates show when Glama detected each change.

  1. First observed

TDQS

A4.5/5.0
Behavior4/5

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

With readOnlyHint, idempotentHint, and destructiveHint already declared, the description adds valuable context: 1.9 million decisions, nightly updates, rates summing to 100%, and the use of complete crawl years only. These details go beyond annotations and help the agent calibrate expectations for the data's scope and caveats.

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 well-structured and front-loaded with the core value proposition, followed by data coverage and definitional caveats. Every sentence adds useful information without redundancy or 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?

Even without an output schema, the description thoroughly explains what the tool returns: outcome breakdowns, year trends, condition-level shares, rate definitions, and data completeness rules. For a zero-parameter aggregate statistics tool, this is fully sufficient for correct invocation and interpretation.

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

Parameters4/5

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

The tool has zero parameters, so the baseline is 4. The description meaningfully clarifies what the returned statistics represent, including the denominator for rates and the labeling of an all-years block, which compensates for the lack of an output 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 clearly states the tool provides corpus-wide VA appeal statistics from a specific dataset, with concrete content categories (issue outcomes, year-by-year trends, conditions). It also explicitly distinguishes itself from individual-case tools by noting it contains no individual veteran's information.

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 indicates this tool is for aggregate corpus-wide statistics and explicitly excludes individual-level data, which signals not to use it for personal case analysis. It does not explicitly name sibling alternatives, but the aggregate-only framing makes the appropriate use context clear.

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

All VetAid — VA Claim Intelligence toolsInspect
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TDQS

A4.4/5.0
Disambiguation3/5

Most tools have clear individual roles, and the personal workflow tools are unambiguous. However, va_condition_intelligence overlaps with va_denial_stats, va_evidence_that_wins, and va_top_authorities, since it also reports outcome shares, evidence associations, and cited authorities, so selecting the right tool often depends on carefully reading the long descriptions.

Naming Consistency4/5

All names use lower_snake_case and are readable, with a consistent verb-first pattern for personal tools (get_my_*, list_my_*, run_my_*) and a va_ prefix for public data tools. The mix of verb-first and noun-phrase names is a minor inconsistency, but the two families are predictable and internally consistent.

Tool Count5/5

Nine tools is a well-scoped count for this domain. Each tool maps to a meaningful operation: four cover the personal case-analysis workflow and five cover aggregate VA data intelligence, with no obvious bloat at the tool-count level.

Completeness4/5

The surface covers the core lifecycle: list cases, check credits, run an analysis, retrieve the analysis summary, and query the main public intelligence areas (outcomes, evidence, authorities, and manual changes). Minor gaps exist, such as no explicit analysis-status endpoint for the 5-8 minute run and no separate condition-level denial-reason tool, but agents can work around these.

Resources