analyze

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

No annotations are provided, so the description carries full burden. It does not disclose whether the tool is read-only, its performance impact (e.g., full table scan), required permissions, or any side effects. The output list is given but behavioral traits are absent.

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 short (two sentences plus an Args block) and efficiently conveys the tool's purpose. However, the Args section is minimally formatted and could be more streamlined. Overall, every sentence adds value.

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 complexity and the presence of an output schema, the description covers core functionality and arguments. However, it lacks context about when to use this tool versus siblings, potential performance implications, and any prerequisites, leaving important gaps for an AI agent.

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?

With 0% schema description coverage, the description must compensate but only adds trivial context: 'Name of the database from config' and 'Name of the table to analyze'. This does not provide format, constraints, examples, or validation beyond the schema's bare titles.

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 profiles a table with a detailed list of statistics (row count, column types, null percentages, etc.), which is a specific verb+resource combination. It distinguishes from sibling tools like 'schema' (column definition only) or 'summary' (possibly different aggregation).

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 usage when profiling a table is needed but provides no explicit when-to-use or when-not-to-use guidance, nor does it mention alternatives among siblings. The user must infer context from sibling tool names.

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