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kks32

designsafe-mcp

by kks32

describe_material

Identify constitutive model parameters, data sources, and calibration order from manual citations before planning a calibration.

Instructions

Parameters, sensitivities, and the calibration sequence for a constitutive model, transcribed from its manual with page citations.

Use this before planning a calibration: it answers which parameters exist, what data informs each one, and in what order to calibrate.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
modelYes

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Behavior3/5

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

No annotations are provided, so the description must carry the transparency burden. It discloses that the tool returns information from a manual and that it answers questions about parameters, sensitivities, and calibration order. This implies a read-only, informational behavior. However, it does not mention potential edge cases (e.g., unsupported model names) or the output format beyond the schema.

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 two sentences, front-loaded with the core content. The first sentence summarizes the tool's output, and the second provides usage context. No unnecessary words or repetition.

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

Completeness4/5

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

Given the tool's simplicity (one parameter, output schema present), the description adequately covers what the tool does, when to use it, and the kind of information it provides. It does not explain the return structure, but the output schema likely covers that. A minor gap is the lack of any qualification about model compatibility or prerequisites, but it is not critical for this straightforward lookup tool.

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 a single 'model' parameter with no description (0% coverage). The tool description refers to a 'constitutive model,' which implies the parameter identifies the model to describe. This is adequate but adds no explicit details about the format, allowed values, or examples. Since the schema provides no semantics, the description gives just enough context but could be richer.

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 function: it provides 'Parameters, sensitivities, and the calibration sequence for a constitutive model.' It specifies the source ('transcribed from its manual with page citations') and the intended position in the workflow ('Use this before planning a calibration'), distinguishing it from sibling tools like plan_calibration and calibration_options.

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 explicit guidance: 'Use this before planning a calibration.' This places it in a clear context relative to planning and calibration workflows. However, it does not name alternatives or state when not to use the tool, which would make it a 5.

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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