hyperspace_search_text

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

With no annotations, the description carries the full behavioral burden, and it does disclose the return shape (JSON array of up to `top_k` items with id, score, payload) — valuable since there is no output schema. It never states that this is a non-mutating read, says nothing about behavior when the collection is missing or empty, and does not mention that lexical/hybrid modes exist.

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?

Two sentences, front-loaded with the operation and scope, then the return contract. No filler, no restatement of the tool name.

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?

The return-value description compensates for the absent output schema, which is good. But the tool is actually a hybrid lexical/semantic searcher (it exposes `bm25_options` and `hybrid_alpha`), and the description frames it as purely semantic, leaving an agent unaware of capabilities it can invoke.

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 description coverage is only 20%, so the description must compensate — it does clarify that `text` is a natural-language query and that `top_k` bounds the result count. But `collection` gets no semantics beyond the word itself and `bm25_options` is entirely unmentioned, so the low coverage gap is only partly bridged.

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?

Specific verb ("Search") plus resource ("collection") and explicit semantic matching against a natural-language `text` query, so the core operation is unambiguous. It does not, however, distinguish itself from the sibling `hyperspace_search_wasserstein`, which is also a search, so the agent has to infer which search operator applies.

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 parenthetical "(natural language query)" implies the semantic-search use case, but there is no explicit when-to-use, when-not, or named alternative among the many siblings (notably `hyperspace_search_wasserstein`). An agent choosing between the two searches gets no routing guidance.

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