register_dataset

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

No annotations are provided, so the description carries the full burden. It discloses that the tool returns a stable dataset reference, but it does not explain side effects (e.g., whether the dataset is persisted, whether registration overwrites existing references, whether the file is copied or referenced), permission requirements, or validation behavior. This is a significant gap for an operation that likely creates or mutates state.

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, directly worded sentence that front-loads the core action and return value. No filler or redundant phrasing.

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?

The description is adequate for a simple registration action but leaves gaps: no mention of prerequisites, error handling, or what the stable dataset reference looks like. With no output schema and no annotations, an agent may not know how to confirm success or use the returned reference correctly.

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 schema only defines 'path' as a string with no description (0% coverage). The description partially compensates by specifying it is a local file path for CSV or Parquet marketing datasets, but it does not provide details such as whether the path must be absolute, whether the file must already exist, or format constraints beyond the file types.

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 states a specific verb ('Register') and resource ('a local CSV or Parquet marketing dataset'), and explicitly mentions the return value ('a stable dataset reference'). This clearly distinguishes it from sibling tools like inspect_dataset or validate_dataset, which perform different actions.

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 implies when to use the tool: when you need to register a local CSV or Parquet dataset for later reference. However, it does not explicitly mention alternatives, exclusions, or a broader workflow context such as 'use this before fitting models' or 'use inspect_dataset to examine the dataset'.

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