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sinagilassi

PyThermoCalcDB-NASA-MCP

by sinagilassi

calc_H_T

Calculate the enthalpy (H_T) of a chemical component at a given temperature using NASA-9 polynomial data. Supports custom reference content for flexible thermodynamic calculations.

Instructions

Calculate component enthalpy H_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 of disclosing behavioral traits. It does not mention whether the calculation is read-only, whether any side effects occur (e.g., caching, logging), or what happens if the component is not in the database. For a calculation tool that accesses a database, this 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 sentence of 18 words, specifying the default behavior and the alternative. It is concise and avoids redundancy. However, it could benefit from a brief additional sentence on the required inputs or sibling differentiation without becoming verbose.

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

Completeness3/5

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

Given the complexity of the tool (many parameters, nested objects, no annotations, but has output schema), the description is minimal. It covers the core function (calculating enthalpy from database/reference) but omits details about return values, error handling, or parameter selection. The output schema exists, so return format is covered, but the agent lacks guidance on parameter usage and behavioral constraints.

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 description coverage is 100%, so the schema already documents the nested object structure and field meanings. The description adds minimal value: it mentions the default NASA-9 database and the alternative reference source, which clarifies the 'source' and 'reference_content' parameters. However, it does not explain the 'mode', 'nasa_type', or 'component_key' parameters, nor does it provide context for when to use each. Baseline 3 is appropriate since the schema is comprehensive.

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

Purpose3/5

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

The description states it calculates component enthalpy H_T and mentions the default NASA-9 database and the alternative reference source. However, it does not clearly differentiate this from sibling tools like calc_S_T or calc_G_T, which likely share a similar interface. The description could be more specific about what distinguishes this enthalpy calculation from entropy or Gibbs free energy calculations.

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?

The description only briefly notes when to use 'source='reference'' vs the default database. There is no guidance on when to use this tool vs alternatives (e.g., when you need enthalpy vs entropy), no prerequisites (e.g., need component and temperature), and no mention of when not to use it. The agent is left to infer usage context from the tool name and sibling list.

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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