set_row_name_pattern

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

No annotations are provided, so the description must disclose behavioral traits on its own. It mentions the operation ('set') and the return JSON, but does not explain side effects, persistence, permission requirements, or behavior on invalid patterns. The lack of depth leaves the agent unaware of potential impacts or failure modes.

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 concise and well-structured with a clear purpose statement, Args/Returns sections, and examples. It front-loads the main function and every sentence adds value—no fluff or redundancy. The length is appropriate for the tool's simplicity.

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?

For a simple setter tool with two parameters and an output schema, the description provides sufficient context: purpose, parameter semantics, and examples. It does not cover error handling or edge cases, but the output schema likely covers return details, and the examples demonstrate typical usage. This is complete enough for an agent to invoke correctly.

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 input schema has no descriptions (coverage 0%), so the description compensates by explaining both parameters. table_name is described as 'Name of the table to update,' and pattern is fully explained as a Handlebars template with triple braces, reinforced by concrete examples. This adds significant meaning beyond the raw schema.

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 sets the pattern for displaying row names in the UI, with a specific verb ('set') and resource ('row name pattern'). It distinguishes itself from sibling tools like set_visible_columns and set_table_display by focusing on the row-name display template.

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 what the tool does and includes examples showing how to call it. It implicitly signals when to use it (when you need to customize row name display) without explicitly naming alternatives or exclusions, but the context is sufficient for an agent to choose appropriately.

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