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inspect_hyper

Analyze Tableau Hyper files to extract schema details, classify columns as dimensions or measures, and provide structured summaries for data analysis workflows.

Instructions

Inspect a Hyper extract file and return its schema with column classification.

Reads the Hyper file, maps column types, classifies columns as dimensions or measures, and returns a summary.

Requires tableauhyperapi (pip install tableauhyperapi).

Args: hyper_path: Path to the .hyper file. table_name: Specific table to inspect (empty = first table).

Returns: Human-readable schema summary with dimensions, measures, and types.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
hyper_pathYes
table_nameNo

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes
Behavior3/5

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

With no annotations provided, the description carries the full burden of behavioral disclosure. It does describe what the tool does (reads Hyper file, maps types, classifies columns) and mentions a prerequisite dependency. However, it doesn't disclose important behavioral aspects like error handling, performance characteristics, file size limitations, or what happens with malformed files. The description adds some value but leaves significant gaps in behavioral understanding.

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 well-structured and appropriately sized. It starts with a clear purpose statement, provides implementation details in the middle, and ends with parameter and return value explanations. Every sentence earns its place by adding valuable information. The formatting with clear sections (Args, Returns) enhances readability without unnecessary verbosity.

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 moderate complexity (file inspection with classification), no annotations, and the presence of an output schema, the description does a good job. It explains what the tool does, its parameters, and mentions the return format. The output schema existence means the description doesn't need to detail return structure. The main gap is lack of error/edge case handling information, but overall it's reasonably complete for the context.

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?

With 0% schema description coverage, the description must compensate for the lack of parameter documentation in the schema. It successfully explains both parameters: 'hyper_path' as 'Path to the .hyper file' and 'table_name' as 'Specific table to inspect (empty = first table)'. This provides clear semantic meaning beyond the bare schema. The only minor gap is not explaining path format expectations (absolute vs relative).

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 purpose with specific verbs ('inspect', 'read', 'map', 'classify', 'return') and resources ('Hyper extract file', 'schema with column classification'). It distinguishes itself from sibling tools like 'inspect_csv' by focusing specifically on Hyper files rather than CSV files, providing clear differentiation.

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 provides clear context about when to use this tool: for inspecting Hyper files to get schema information with column classification. It mentions a prerequisite ('Requires tableauhyperapi') which is helpful guidance. However, it doesn't explicitly state when NOT to use it or name specific alternatives among the many sibling tools, though 'inspect_csv' is an obvious alternative for CSV files.

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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