profile_dataset

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

In the absence of annotations, the description fully carries the burden. It discloses that it reads the file, detects format, returns a structured overview, and describes the sampling behavior controlled by max_rows. It does not mention potential side effects (likely none) or performance limitations.

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?

The description is well-structured with a lead sentence, then bullet-like list. It is appropriately sized for the tool's complexity, though could be slightly more concise by merging some bullet points.

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?

Despite no output schema, the description enumerates all major return categories: file metadata, shape, memory, missing values, duplicate count, per-column summary, and data-quality flags. For a two-parameter tool, this is fully 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 0%, but the description explains path's role as 'Reads the file at path' and max_rows adds meaning: 'caps how many rows are read (default: up to one million); pass 0 to remove the cap entirely.' This adds value beyond the schema's type and title.

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 'Profile a tabular data file' and lists specific outputs (file metadata, shape, memory, missing values, column summary, flags). It distinguishes from sibling tools like preview_data and column_stats by emphasizing it's the fastest way to understand a dataset in one call.

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 recommends 'Use this first whenever a user points you at a data file and wants to know what is in it.' This provides clear when-to-use guidance, though it doesn't explicitly mention alternatives or when not to use.

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