glpi_search_faq

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

No annotations are provided, so the description carries the burden. It does disclose the underlying filter (is_faq=true) and implies a read-only search, but it doesn't specify return format, pagination behavior, or any other operational traits beyond the schema. This is adequate but not rich.

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 two sentences, front-loaded with the core purpose and followed by a clear use case. Every word earns its place, and there is no redundancy or filler.

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 search tool with no output schema and all-optional parameters, the description provides the essential context: what is searched, the filter, and when to use it. It doesn't clarify the return structure, but the close sibling glpi_search_knowbase might cover general KB search; still, this is sufficiently complete for the tool's simplicity.

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 100%, so the schema already documents all four parameters. The description adds no additional parameter-level meaning, but the baseline of 3 applies because the schema does the heavy lifting.

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 'Busca artigos marcados como FAQ na base de conhecimento' and identifies the specific filter is_faq=true, distinguishing it from the broader glpi_search_knowbase sibling tool. The verb 'Busca' and resource 'artigos marcados como FAQ' are specific and 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 clear usage context: 'Use para dúvidas rápidas de uso do GLPI antes de abrir ticket.' It doesn't explicitly name alternatives like glpi_search_knowbase for general knowledge base articles, but the FAQ-specific scope and use case make the intended usage clear.

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