load_csv

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

With no annotations, the description carries full burden. It discloses that the tool registers a dataset and returns the inferred schema, and mentions CSV format (first row is header). However, it omits important behavioral traits: what happens if the name already exists (overwrite/error), whether the operation is reversible, or any size/performance limits. This is adequate but has gaps.

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 extremely concise: two sentences plus a parameter list. Every sentence is substantive, with no filler. The purpose is stated first, followed by parameter details, which is an ideal structure.

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 tool's simplicity (2 required params, no nested objects, output schema present), the description covers the core functionality and parameter roles. However, it lacks details on duplicate name handling, error scenarios, or data format constraints (e.g., encoding). This is a minor gap for a load operation.

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%, so the description must compensate. It fully explains both parameters: 'name' is a unique name, 'csv_text' is raw CSV content with comma-separation and first-row header. This adds significant meaning beyond the schema's type/title alone.

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 tool's action: 'Register a dataset from CSV text.' This is a specific verb+resource, and it distinguishes itself from sibling tools like list_datasets, filter_rows, and correlation, which are for querying or analyzing existing data, not loading.

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 provides no guidance on when to use this tool vs alternatives. It does not mention prerequisites (e.g., ensure CSV is valid) or when not to use it (e.g., if the dataset already exists). Sibling tools are not referenced for context.

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