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vosesoftware

ModelRisk MCP

Official
by vosesoftware

diagnose_workbook

Run a one-call workbook health check to verify Excel connectivity, ModelRisk SDK activation, workbook sheets, input/output/distribution counts, and audit log location. Replaces multiple individual tool calls.

Instructions

ModelRisk: One-call workbook health check. Returns everything an MCP client typically wants at the start of a session: whether Excel is reachable, whether the ModelRisk SDK is activated, the active workbook's name + sheets, counts of inputs / outputs / distributions, whether a sibling .vmrs exists and when it was last modified, and the audit-log location. Use this as the first call instead of orchestrating 4-5 individual reading tools.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
workbook_nameNoWorkbook name. Omit for the active workbook.

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Behavior4/5

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

With no annotations, the description carries the full burden. It discloses a comprehensive list of returned data (Excel reachability, SDK activation, workbook info, counts, vmrs details, audit-log). It does not mention side effects, error conditions, or authentication requirements, but as a read-only health check, the disclosure is adequate.

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 exceptionally concise: two sentences with no wasted words. The first sentence states the primary purpose, and the second enumerates the returned items, ensuring front-loaded critical information.

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?

Given the tool's complexity (many sibling tools) and the presence of an output schema, the description is complete. It explains when to use it (first call vs. multiple tools) and what it returns, covering all essential context for an AI agent.

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 single parameter 'workbook_name' is fully described in the schema (100% coverage). The description adds no further meaning beyond repeating the schema's instruction to omit for the active workbook, so it meets the baseline but does not exceed it.

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 purpose as a 'one-call workbook health check' and lists the specific information returned. It distinguishes itself from sibling tools by explicitly offering a single call that replaces orchestrating 4-5 individual reading tools.

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

Usage Guidelines5/5

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

The description explicitly recommends using this tool as the first call and explains that it is an alternative to combining multiple reading tools, providing clear usage guidance and context.

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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