fetch_model_data

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

The readOnlyHint annotation already establishes that this is a safe read operation, and the description adds useful context that output is bounded and column-filterable. However, it omits an important behavioral trait: the mask_sensitive parameter defaults to true, meaning sensitive data is masked by default. That omission is a notable gap for a data-preview 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?

A single sentence, front-loaded, with every word contributing meaning: verb, scope, optional filtering, and resource. There is 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 output schema and 0% schema description coverage, the description should do more to explain the four parameters and return shape. It conveys the preview concept adequately but leaves masking behavior and pagination/return format implicit, which is incomplete for a tool whose schema is otherwise undocumented.

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 carry parameter meaning. It implies model_name ('model data'), limit ('bounded'), and columns ('column-filtered'), but says nothing about mask_sensitive, which is one of four parameters and has a security-relevant default. It covers most parameters at a high level but leaves a critical one unexplained.

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 and resource: 'Fetch ... preview of model data.' It also names key scoping traits ('bounded', 'optionally column-filtered'), making it distinguishable from metadata-oriented siblings like get_model or list_models. It does not explicitly name an alternative sibling, so it falls short of a 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 phrase 'preview of model data' implies sampling use, but the description gives no explicit when-to-use guidance and no exclusions against siblings such as profile_model or table_diff. The agent must infer that this is for quick row previews rather than profiling or diffing.

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