VetAid — VA Claim Intelligence

Run my case analysis (uses a credit)

run_my_case_analysis

RUN the full VetAid analysis pipeline on one of the veteran's OWN cases, ON THE VETERAN'S BEHALF. This SPENDS one of the veteran's analysis credits (free plan: first 2 free, then $9.99 each) and takes ~5-8 minutes — afterward poll get_my_case_analysis(case_id) for the results.

Requires a WRITE-scoped agent key: the veteran must have created the key with
the 'Allow running analyses' (read_write) scope. A read-only key returns a
'read-only key' error; out of credits returns 'no credits'; a case the key
owner does not own returns 'not found' (no cross-user access). Consider
calling get_my_vetaid_account() first to confirm a credit is available.

Args:
    case_id: The id of one of the veteran's own cases (from list_my_va_cases).

Input Schema

TableJSON Schema

Name	Required	Description	Default
`case_id`	Yes

Schema Changelog

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

First observedSep 6, 2026

TDQS

A4.7/5.0

Behavior5/5

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

The description goes well beyond the annotations by disclosing cost, latency, asynchronous behavior, auth-scope requirements, specific error strings ('read-only key', 'no credits', 'not found'), and the no-cross-user-access rule. This is exactly the behavioral context an agent needs for a long-running, credit-consuming operation.

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 longer than average, but every sentence conveys a necessary operational detail: cost, duration, polling, auth scope, error conditions, and argument provenance. It is front-loaded with the core action and most critical consequence (spending a credit), and the Args section is clearly separated.

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?

For a non-read-only, non-idempotent, long-running tool with no output schema, the description covers all essential context: prerequisites, side effects, timing, error modes, and how to obtain the result. An agent can decide whether to call it and do so with an appropriate case_id.

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 input schema only provides the raw property name and type, with 0% description coverage, so the description must compensate. It does so by explaining that case_id must be one of the veteran's own cases and pointing to list_my_va_cases as the source.

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 uses a specific verb ('RUN') and clearly identifies the resource: the full VetAid analysis pipeline on one of the veteran's own cases, on their behalf. It distinguishes this from the sibling polling tool get_my_case_analysis by stating that results are retrieved afterward, not returned by this call.

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 strong contextual guidance: it requires a write-scoped key, spends a credit, takes 5-8 minutes, and recommends checking get_my_vetaid_account() first. It does not explicitly contrast with every sibling, but it makes the flow clear enough that an agent will know when to call this versus retrieving results or listing cases.

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 tools Inspect

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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

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