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LATINALU

etabs-mcp

by LATINALU

etabs_story_drifts

Retrieve inter-story drift values for selected load cases or combinations from the current ETABS model, enabling structural performance verification.

Instructions

Derivas por nivel para los casos/combinaciones seleccionados.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.1.0

TDQS

C2.8/5.0
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 behavioral disclosure. It only states what the tool provides but does not mention whether it requires an unlocked model, if it is read-only, or what the output structure is (though output schema exists). The lack of any side-effect or state information is a significant gap.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness4/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is a single, efficient sentence with no filler words. It is front-loaded with the core purpose. However, it is so terse that it sacrifices necessary context, but as a standalone statement it is concise.

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?

Given the tool has no parameters and an output schema exists, the description's brevity might be tolerated, but it fails to explain the 'selected' prerequisite and provides no usage context among many sibling result tools. It is incomplete for an agent to know when to invoke this tool confidently.

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 schema imposes no burden. The description adds contextual meaning by referencing 'selected cases/combinations,' implying reliance on prior selection state, which is useful. However, it does not explain how selection is made, but since no parameters exist, this is acceptable.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose4/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description states the tool provides story drifts per level for selected cases/combinations, which is a specific resource and distinguishes it from sibling result tools like base reactions or modal periods. However, it lacks a verb explicitly indicating the action (e.g., 'get' or 'retrieve'), and the meaning of 'selected' is ambiguous.

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

Usage Guidelines1/5

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

No guidance is provided on when to use this tool versus alternatives. There is no mention of prerequisites (e.g., prior analysis or selecting cases), no exclusions, and no reference to sibling tools. The agent is left to infer context.

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