get_semantic_search

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

With no annotations, the description carries the full burden. It discloses the use of text-embedding-3-small vectors, hybrid keyword+semantic+reranking, and return format (relevance-ranked results with similarity scores and text snippets). It does not mention rate limits or authentication, but the core behavior is transparent.

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 three concise sentences with no waste. The first sentence states the purpose, the second explains the technology, and the third gives a concrete example. Every sentence is essential.

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 (semantic search with 6 parameters) and no output schema, the description covers return format and provides parameter context. It is complete enough for an agent to understand and use the tool correctly.

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% coverage with descriptions, and the tool description adds extra context beyond the schema. For example, it provides example queries for 'q' and states the default limit (10) which the schema only defines as min/max. This adds meaningful value.

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 'Search 64,000+ NZX announcements using AI semantic search', providing a specific verb and resource. It differentiates from sibling tools like search_announcements by highlighting conceptual matching that keyword search misses, as shown in the example.

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 explicitly says 'Finds conceptual matches that keyword search misses' with an example, indicating when to use this tool over keyword search. However, it does not explicitly list alternatives or state when not to use it, leaving some room for interpretation.

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