search_entity

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

The description discloses case-insensitivity and fuzzy matching but no other behavioral traits (e.g., pagination, performance, result ordering). Since annotations are absent, the description carries the full burden, and it provides only basic transparency.

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 a single sentence that front-loads the action and resource, with no wasted words. It is optimally concise for a search tool.

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 absence of an output schema and the existence of sibling tools, the description adequately covers the essential function. However, it lacks details about result types or cross-entity searching, which would improve completeness for more complex use cases.

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 100%, so the schema already documents both parameters. The description adds the fuzzy matching detail not in the schema, enhancing parameter semantics beyond the baseline of 3.

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: searching for classes, individuals, and properties by name keyword with case-insensitive fuzzy matching. It uses specific verbs and resources, distinguishing it from sibling tools that perform specific CRUD operations or complex queries.

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 implies use for keyword-based search across multiple entity types but does not explicitly state when to use this tool over alternatives like list_classes or sparql_query. No guidance on when not to use it is provided.

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