profile_data_source

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

With no annotations provided, the description carries the full burden of behavioral disclosure. It describes what the profile includes (dimension/measure classification, semantic types, etc.) and that it returns a 'Human-readable DataProfile with signals for template/chart decisions', which adds useful context. However, it lacks details on permissions, rate limits, or potential side effects, leaving some behavioral aspects unclear.

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 appropriately sized and front-loaded, starting with the core purpose, followed by scope details, profile contents, and parameter/return explanations. Every sentence adds value without redundancy, making it efficient and well-structured.

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 moderate complexity (1 parameter, no annotations, but with an output schema), the description is complete enough. It explains the purpose, usage context, parameter semantics, and return value, and since an output schema exists, it doesn't need to detail return values further. This covers all necessary aspects for effective use.

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 meaningful semantics for the single parameter 'source_type', explaining it's an override for source detection, with 'auto' as the default and other options like 'csv' or 'hyper' requiring separate tools. Since schema description coverage is 0% (the schema only provides a title and type), the description compensates well, though it could elaborate more on the implications of each option for a perfect score.

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 purpose with specific verbs ('profile') and resources ('currently connected data source'), and distinguishes it from siblings by specifying it works for 'ANY connection type' and includes dimension/measure classification, semantic types, etc. This is distinct from tools like 'profile_csv' or 'profile_twb_for_migration' which are more specific.

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 clear context on when to use this tool: 'Profile the currently connected data source' and 'Works for ANY connection type', implying it's a general profiling tool. However, it does not explicitly state when not to use it or name alternatives (e.g., 'profile_csv' for CSV-specific profiling), which prevents a score of 5.

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