Skip to main content
Glama
dbett4

regulated-reporting-mcp

by dbett4

workiva_wdata_create_query

Create a Wdata query by providing a name and SQL statement to define reusable data sets for Workiva reporting.

Instructions

Create a Wdata query.

Args: name: Query name sql: SQL statement

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
sqlNo
nameNo

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes
Behavior2/5

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

With no annotations, the description carries the full burden of disclosing side effects and operational traits. It states only that a query is created, but does not clarify persistence, required permissions, potential validation, or whether the query is executed immediately. This leaves significant behavioral ambiguity.

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, front-loaded with the purpose, and uses a clear args list. Every line earns its place without filler, making it efficiently structured and easy to scan.

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

Completeness2/5

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

Although an output schema exists, the description is incomplete for a create operation. It omits prerequisites (e.g., a connection or workspace), potential side effects, and the relationship to related operations like validate_query or run_query. The tool is simple but the description provides no surrounding context to guide correct invocation.

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

Parameters3/5

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

The schema has 0% description coverage, so the description's 'Args' section adds meaning by labeling 'name' as 'Query name' and 'sql' as 'SQL statement.' This provides essential semantic value beyond the schema, but it remains minimal and does not explain optionality, format requirements, or acceptable SQL syntax.

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's action with a specific verb and resource: 'Create a Wdata query.' This distinguishes it from sibling tools like list_queries, get_query, delete_query, and run_query.

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

Usage Guidelines2/5

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

No guidance is provided about when to use this tool versus alternatives. It does not mention prerequisites, whether the query is immediately run or only saved, or any exclusions compared to validate_query or describe_query. The usage context is entirely absent.

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

Install Server

Other Tools

Latest Blog Posts

MCP directory API

We provide all the information about MCP servers via our MCP API.

curl -X GET 'https://glama.ai/api/mcp/v1/servers/dbett4/regulated-reporting-mcp'

If you have feedback or need assistance with the MCP directory API, please join our Discord server