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sinagilassi

PyThermoCalcDB-NASA-MCP

by sinagilassi

calc_S_T

Calculate component entropy at a given temperature using the NASA-9 database or custom reference content.

Instructions

Calculate component entropy S_T using the embedded NASA-9 database by default, or caller-supplied reference_content when source='reference'.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
requestYesRequest for a single-component NASA property calculation.

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

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 for behavioral disclosure. It only describes the computation and data sources, without stating whether the operation is read-only, safe, or has side effects. For a thermodynamic calculation tool, this omission leaves uncertainty about idempotency and permissions.

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 a single sentence that is front-loaded with the core action and efficiently conveys the primary purpose and key variation (default vs reference source). No extraneous words; every clause earns its place.

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 presence of an output schema (not shown but noted), the description does not need to detail return values. It covers the essential purpose and the two operational modes. However, it could be slightly more complete by mentioning preconditions (e.g., valid component data) or error scenarios, though this is not critical for basic usage.

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?

Schema description coverage is 100%, with detailed parameter documentation. The description adds significant meaning by explaining the two data source modes and the condition when 'reference_content' is required, which goes beyond what the schema alone provides. This helps agents decide how to populate the source and reference_content parameters.

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 it calculates component entropy S_T, specifies the default embedded NASA-9 database, and mentions the alternative caller-supplied reference_content when source='reference'. This is a specific verb+resource combination that distinguishes it from sibling tools like calc_H_T or calc_G_T, which calculate different thermodynamic properties.

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 implies usage for entropy calculations and explains the two source modes (database vs reference), but it does not explicitly state when to choose this tool over its siblings (e.g., which property to compute) or provide when-not-to-use guidance. Comparatively, it lacks explicit exclusions or alternative tool references.

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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