profile_dataset

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

With no annotations provided, the description carries the burden of behavioral disclosure. It usefully reveals that the full dataset is not sent to the model, implying local processing, but it does not state whether the operation is read-only, what side effects occur, or what the profiling process entails beyond that privacy guarantee.

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?

A single, well-structured sentence that front-loads the core purpose and adds the important privacy qualifier. Every word contributes value, with no filler or redundancy.

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?

With no annotations, no output schema, and no schema-level parameter descriptions, the one-line description leaves significant gaps: it does not describe the returned profile structure, clarify sample_rows semantics, or help the agent choose between this and audit_dataset. The simple input schema keeps it from being a 1, but an agent would still be guessing about important call behavior.

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?

The description adds meaning to the path parameter by specifying it must be a local file in CSV, Parquet, or JSONL format. However, it does not explain sample_rows or how it interacts with profiling, and schema description coverage is 0%, so the description only partially compensates.

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 identifies the action ('Profile') and the resource ('a local CSV, Parquet, or JSONL'), and adds a meaningful qualifier ('without sending the full dataset to the model'). It does not explicitly differentiate from the sibling audit_dataset, which also operates on datasets, so it falls just short of a full 5.

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?

The description gives clear context: use this tool to profile local tabular/structured files while avoiding sending the full dataset to the model. However, it does not state exclusions or explicitly point to alternatives such as audit_dataset when a full audit is needed.

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