Slugify / case-convert / template-fill

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

With no annotations provided, the description carries the full burden. It discloses that the tool is free, describes each op's behavior (e.g., slugify -> URL slug), and specifies required argument combinations. However, it omits return format, error behavior (though strict is in schema), and any side effects.

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 compact, starts with the core purpose ('FREE. Text transforms.'), and every sentence provides necessary detail. It avoids redundancy with the schema.

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?

While the description covers the main operations and argument combinations, it lacks a statement about return values, which is important given there is no output schema. It also does not address potential error cases, though strict behavior is documented in the schema.

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 schema has 100% coverage, so the baseline is 3. The description adds value by explaining which parameters are used together for different ops, and elaborates on the 'op' parameter semantics beyond the schema's list enumeration.

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 explicitly identifies the tool as 'Text transforms' and enumerates all operations (slugify, case conversions, template filling), making its purpose unambiguous and distinct from sibling tools like encode or hash.

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?

It provides clear context by specifying which op requires which arguments (op + text for slugify/case, template + data for template), and implies when to use each op. However, it does not explicitly mention when NOT to use this tool or point to alternatives.

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