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sinagilassi

PyThermoCalcDB-NASA-MCP

by sinagilassi

calc_Cp_T

Calculate component heat capacity (Cp) at a given temperature using NASA-9 polynomials, either from default database or user-supplied reference data.

Instructions

Calculate component heat capacity Cp_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?

With no annotations, the description carries full burden for behavioral disclosure. It reveals that the tool uses an embedded NASA-9 database or custom reference_content, but fails to disclose error behavior (e.g., missing data, out-of-range temperature), permissions, or side effects. Critical gaps exist for a computational tool.

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 22 words, front-loaded with the purpose. It is concise with no redundant phrases, though slight tightening is possible (e.g., 'using the embedded NASA-9 database' could be 'using the NASA-9 database').

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?

Despite the tool's complexity (nested objects, many parameters), the description is minimal. It does not explain return values (though output schema exists), temperature validity ranges, or prerequisites. Annotations are absent, leaving significant gaps for correct invocation.

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?

Schema description coverage is 100%, so baseline is 3. The description adds value by explaining the dual-mode behavior (database vs reference) for the 'source' and 'reference_content' parameters. However, it does not elaborate on other parameters like mode, basis, or nasa_type, which are only documented in the schema.

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 clearly states it calculates component heat capacity Cp_T, specifying the verb 'Calculate' and resource. It mentions the default NASA-9 database and alternative reference_source, but does not explicitly distinguish from sibling tools like calc_H_T or calc_S_T beyond the property name.

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 provides internal context about using the database by default or caller-supplied reference_content, but offers no guidance on when to use this tool versus sibling tools (e.g., calc_H_T, calc_G_T). No exclusions or when-not-to-use conditions are given.

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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