get_data_summary

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

No annotations provided, so description carries the burden. It discloses the returned items (column names, dtypes, row count, sample values) and implies a read-only, non-destructive operation. Missing mention of permissions or speed details, but sufficient for a summary tool.

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

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

Two concise sentences: first states primary purpose, second details return values and performance comparison. No unnecessary words, front-loaded with key information.

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

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

Given the low complexity, presence of output schema (not shown but known), and single parameter, the description fully covers the tool's behavior and context. It explains return values, mentions speed advantage, and provides an alternative, making it complete.

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

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

Schema description coverage is 100% for the single parameter, with a clear description in the JSON schema. The description adds no further meaning beyond what the schema already provides, so baseline score of 3 is appropriate.

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

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

The description clearly states the verb ('summary') and resource ('resource's data'), specifying it returns column names, dtypes, row count, and sample values without downloading the full file. This distinguishes it from sibling tools like get_resource_data, which downloads full data.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Does the description explain when to use this tool, when not to, or what alternatives exist?

Explicitly states when to use ('quick schema summary') and when to use an alternative ('Much faster than get_resource_data() for large XLSX/CSV files where you only need to know the schema'), providing clear usage context.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.