Search GLPI items by name

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

Annotations already declare readOnlyHint, idempotentHint, openWorldHint and destructiveHint=false, so the safety profile is covered. The description still adds real behavioral context beyond that: matching is partial rather than exact, itemtype is open-ended, and the response contains IDs rather than full records. It does not mention result capping or pagination behavior, which is the remaining gap.

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?

Two sentences with no filler, and the most decision-relevant information (what it searches, then what it returns and how to use it) is front-loaded. Nothing repeats the title or wastes tokens.

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?

With no output schema, the description correctly states the return content (IDs) and the follow-up tools, which is the key missing piece an agent would otherwise lack. For a four-parameter, non-nested search tool with rich annotations, this is nearly complete; only pagination and result-limit behavior are unaddressed.

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 coverage is 50%: itemtype and start carry descriptions, while query and limit have none. The description compensates for query by specifying name-based partial matching, but adds nothing for limit or pagination, and its itemtype examples largely restate the schema description. This is a baseline-plus contribution, not full compensation.

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?

"Find assets, users, groups, locations, categories, suppliers, KB articles or any other itemtype by name (partial match)" gives a specific verb and a wide resource enumeration, so an agent knows this is the generic itemtype search. It is distinguishable from glpi_search_tickets and glpi_search_knowledgebase only implicitly through "any other itemtype", rather than by naming those siblings directly.

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 second sentence names the downstream tools (glpi_get_item or the ticket tools) and states that the output is IDs for them, which gives clear workflow context. It stops short of explicit exclusions such as "use glpi_search_tickets for ticket text search", so the choice between this and the specialized search siblings is left partly to inference.

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