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dbett4

regulated-reporting-mcp

by dbett4

workiva_wdata_validate_query

Validate a Wdata query by ID or raw SQL to confirm it is well-formed and error-free before use in regulated reporting.

Instructions

Validate a Wdata query by ID or raw SQL.

Args: query_id: The query ID (optional — validates an existing query) sql: Raw SQL to validate (if query_id not provided)

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
sqlNo
query_idNo

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes
Behavior2/5

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

No annotations are provided, so the description carries the full burden. It does not disclose what 'validate' entails—whether it executes the query, returns a success boolean, or reports errors. It does not mention side effects or expected outcome, which is a significant gap for a tool with no structured safety hints.

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 extremely concise: a one-line purpose followed by a simple arg list. Every word earns its place, and the structure is front-loaded with the core action. No fluff or redundancy.

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

Completeness3/5

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

The tool is relatively simple, but with no annotations and no schema descriptions, the description alone is sparse. It omits information about return values, error handling, and the validation process. An output schema exists but its content is not visible in the description, so the description should have been more complete.

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 schema provides only parameter names and defaults with 0% coverage, but the description adds meaningful semantics: query_id validates an existing query, sql is raw SQL used when query_id is absent. This compensates for the schema gap, though it could be more explicit about both being optional and empty-string defaults.

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 'Validate a Wdata query by ID or raw SQL' with a specific verb and resource. It distinguishes this tool from related query tools like create, run, and describe, making its purpose unmistakable.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines3/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description explains the two usage modes (by query_id or raw SQL) and notes that sql is used if query_id is not provided, but it does not explicitly state when to prefer this over alternatives or when not to use it. No exclusions or alternative tool references are given.

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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