profile_data

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 the type of statistics computed but does not state whether the operation is read-only, any side effects, permission requirements, or potential performance impact. Such information is critical for a profiling tool that likely scans full tables. The description is minimal and does not go beyond the basic output.

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 a single, compact sentence that front-loads the core purpose. It avoids unnecessary words and is appropriately sized. However, it is so brief that it sacrifices substantive content, though that is not a conciseness penalty — it is structurally efficient.

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?

Even though an output schema exists (so return format is covered), the description is incomplete for a tool with no annotations and two parameters. It omits parameter meanings, usage conditions, and any behavioral safety context. An agent would struggle to know how to pass the optional 'columns' parameter or whether the operation is safe to run. The description is adequate only as a terse overview.

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%, and the description does not explain either parameter. 'table_name' is required but never mentioned, and 'columns' (optional, default '') is not clarified regarding format (e.g., comma-separated list?) or behavior when empty. The description adds no value beyond the schema's property names, leaving the agent guessing about expected values.

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 a specific verb ('Профилирование' – profiling) and a concrete resource (column statistics) with explicit outputs: null%, uniqueness, min/max, top-5. This distinguishes it from sibling tools like data_quality_report or find_duplicates by specifying the exact metrics computed. Even though it's in Russian, the meaning is unambiguous.

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 versus alternatives such as data_quality_report or distribution_analysis. There is no mention of appropriate use cases, exclusions, or comparisons to sibling tools. An agent would have to infer from the name and stats listed.

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