semantic_search

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

Without annotations, the description carries the full burden. It discloses that the tool uses meaning-based similarity, not keywords, and provides an example demonstrating non-literal matching. It does not detail return format or performance, but it is sufficiently transparent about its core 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 extremely concise: two sentences plus an example. Every element serves a purpose—stating the tool's function, a prerequisite, a key differentiator, and a concrete example. No redundancies 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?

Given the tool's complexity (search with semantic matching, 3 parameters, no output schema), the description is adequate but not fully complete. It omits details about output format (e.g., ranked documents, scores), which forces the agent to rely on assumptions or schema. The example helps, but more behavioral context is needed for full autonomy.

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?

The input schema has 100% parameter description coverage, so the baseline is 3. The description's example adds value by showing how the 'query' parameter works in a semantic context (e.g., 'movable objects' finds 'sprites'), which enriches understanding beyond the schema definition.

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 searches the knowledge base using semantic/conceptual similarity, distinguishing it from keyword search. The example ('movable objects' finds 'sprites') concretely illustrates the purpose, leaving no ambiguity about what the tool does.

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 includes a prerequisite ('requires USE_SEMANTIC_SEARCH=1') and contrasts with keyword search, guiding when to use this tool. However, it does not explicitly state when not to use it or mention alternatives like 'hybrid_search' or 'fuzzy_search', which would be helpful for an agent making a choice.

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