saptiva_help

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

No annotations are provided, so the description carries the full burden of behavioral disclosure. It clearly indicates this is a read-only, informational tool ('shows examples'), which implies no destructive actions or authentication requirements. However, it doesn't disclose potential behavioral traits like response format (likely text/markdown), whether it's static content or dynamically generated, any rate limits, or if it requires specific permissions. The description adds basic context but lacks depth for a tool with no annotation coverage.

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: the first sentence states the core purpose, followed by a structured list of topics with brief explanations. Every sentence earns its place by directly supporting the tool's function as a beginner's guide. The use of emoji and clear headings enhances readability without adding fluff. It efficiently conveys necessary information in a compact format.

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 low complexity (1 parameter, informational purpose) and no output schema, the description is moderately complete. It covers the purpose, usage context, and parameter semantics adequately. However, without annotations or output schema, it lacks details on behavioral aspects (e.g., response format, error handling) and doesn't fully address what the user can expect beyond 'examples'. For a simple help tool, this is acceptable but leaves some gaps in contextual understanding.

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 100% description coverage, with the 'topic' parameter fully documented via enum values and a description ('Tema de ayuda a mostrar'). The description adds value by listing and briefly explaining each enum option (e.g., 'quick_start: Inicio rápido con ejemplo básico'), providing semantic meaning beyond the schema's enum labels. This compensates well, though it doesn't detail parameter syntax or constraints beyond what's implied. With 1 parameter and high schema coverage, baseline is 3, but the added explanations justify a higher 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: 'Muestra ejemplos de peticiones y respuestas de la API de Saptiva' (Shows examples of requests and responses for the Saptiva API). This is a specific verb ('shows examples') with a clear resource ('Saptiva API requests and responses'). It distinguishes from sibling tools like saptiva_chat or saptiva_ocr by focusing on documentation/examples rather than performing API operations. However, it doesn't explicitly contrast with saptiva_list_models (which might list tools vs. showing examples).

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 for when to use this tool: as a 'GUÍA PARA PRINCIPIANTES' (Beginner's Guide) to learn about API usage through examples. It lists specific topics available, which implicitly guides usage based on the user's learning needs (e.g., use 'quick_start' for basics, 'ocr_example' for image text extraction). However, it doesn't explicitly state when NOT to use it (e.g., for actual API operations) or name alternatives like official documentation or sibling tools for direct API calls.

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