search_entities

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

With no annotations, the description must carry behavioral disclosure. It reveals that matching is multi-signal and that results are candidate entities, implying fuzzy or ranked rather than exact lookup. It doesn't describe result ordering, pagination, or edge cases, so coverage is partial.

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?

Single sentence front-loads the verb and object, then adds scoping detail. No filler; every clause earns its place.

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 two-parameter search tool, the core invocation is clear. However, the absence of an output schema means the description should have said what the returned candidates look like or how matching behaves, and it doesn't address when to prefer get_entity. This leaves the agent to infer integration details.

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?

Input schema covers both parameters fully, so the description adds little new parameter meaning. The phrase 'name, alias, or keyword' mirrors the query schema's description, and limit behavior is documented only in the schema.

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?

Description names a concrete operation—searching candidate entities—and scopes it by input type (name, alias, keyword) and method (multi-signal matching). This distinguishes it from exact-lookup siblings like get_entity and from relationship/evidence tools.

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 establishes clear trigger conditions: an agent should call this when it has a name, alias, or keyword and needs candidate entity matches. It doesn't explicitly state when not to use it or name an alternative, so it stops short of full routing guidance.

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