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Scigantic

scigantic-mcp

Official
by Scigantic

get_schema_card

Retrieve a compact schema card for a scientific data archive, revealing file format, columns, sample rows, and linked documentation without downloading the dataset.

Instructions

Get the compact schema card for an archive: file format, columns, sample rows/headers, sidecar docs (READMEs/data dictionaries) and a copy-paste starter cell.

This is the fastest way to understand a dataset's structure without downloading it.

Args: id: Archive id from search_archives.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
idYes

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes
Behavior3/5

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

No annotations provided, so description carries the burden. The description does disclose what the tool returns (a compact card with specific components). However, it doesn't mention the id source (tells you to use search_archives id) or any caching/side effects. Since this is a read-only inspection tool, the risk profile is low, and the return content is well specified.

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?

Compact and front-loaded. The first line states the core purpose and content list. The usage context is one sentence. Args section is minimal. No wasted words.

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

Completeness5/5

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

Has an output schema and only 1 parameter. The description fully covers the parameter sourcing (from search_archives), the content of the result, and the use case. For a simple inspection tool, this is complete.

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 0%, so the description must compensate for the single 'id' parameter. It does, by explaining that the id comes from search_archives, which gives meaningful provenance. Even though the schema has 100% of the single parameter documented in structure, the description adds sourcing semantics beyond the bare schema.

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?

Specific verb+resource: 'Get the compact schema card for an archive' with detailed content enumeration (format, columns, sample rows/headers, sidecar docs, copy-paste starter cell). Clearly distinguishes from search_archives (searching) and get_archive/list_archive_files (retrieval/listing).

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?

Explicit use case: 'This is the fastest way to understand a dataset's structure without downloading it.' This provides clear context for when to prefer this tool. It doesn't explicitly name alternative tools for exclusion, but the context (fastest way to understand structure) signals when it applies and the siblings are understandable.

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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