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by dlt-hub

get_table_schema

Retrieve the column names, data types, and structure of a specified table within a dlt pipeline.

Instructions

Get the schema of the specified table.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
pipeline_nameYes
table_nameYes

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
x-normalizerNo
x-loaderNo
x-extractorNo
nameNo
descriptionNo
schema_contractNo
table_sealedNo
parentNo
filtersNo
columnsNo
resourceNo
table_formatNo
file_formatNo
write_dispositionNo
referencesNo
Behavior2/5

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

With no annotations provided, the description carries the full burden of disclosing behavioral traits. It only states 'Get the schema' without indicating that this is a read operation, any side effects, authentication requirements, or return format. The agent must infer behavior from the tool name alone.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness3/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is a single sentence, which is concise, but it is under-specified relative to the tool's complexity. While it earns its place by stating the purpose, it fails to include necessary details about parameters or behavior, making it borderline insufficient.

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?

Given the existence of an output schema and two simple parameters, the description should at least hint at what the schema includes (e.g., column names, types) or how to use the parameters. It does not, leaving the tool incomplete for effective use.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters1/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

The input schema has 0% description coverage for its two parameters ('pipeline_name' and 'table_name'), and the tool description adds no explanation of what these parameters represent or how they should be used. This offers no value beyond the parameter names.

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 the action 'Get the schema' on 'the specified table', providing a specific verb and resource. However, it does not explicitly differentiate from sibling tools like 'display_schema' or 'get_table_schema_diff', which may perform similar functions.

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 no guidance on when to use this tool versus alternatives, such as comparing schemas with 'get_table_schema_diff' or listing tables with 'list_tables'. It also lacks context about prerequisites or typical scenarios.

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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