semantic_search

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

No annotations are provided, so the description must disclose behavioral traits. It only states it performs semantic search, but doesn't mention idempotency, read-only nature, performance considerations, or how hybrid search behaves. The schema describes parameters like hybrid_search and semantic_weight, but the tool description doesn't explain their impact on behavior.

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 concise sentence that directly states the tool's function. It could be slightly more structured (e.g., listing key features), but it's not verbose.

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 8 parameters and no output schema, the description is too sparse. It doesn't explain what results are returned, how to use parameters like min_similarity or hybrid_search in practice, or any context for interpreting similarity scores. The tool description relies heavily on the schema descriptions for detail.

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 baseline is 3. The description does not add any additional semantics beyond the schema; it's a general statement that doesn't elaborate on parameters.

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 entities semantically using vector embeddings and similarity in the knowledge graph. It uses specific verb+resource and distinguishes from sibling tools like search_nodes (likely keyword-based) and read_graph (returns all entities).

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 no guidance on when to use this tool versus alternatives, such as keyword search or graph traversal. No context on prerequisites or situations where semantic search is not appropriate.

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