vector_search

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

No annotations are provided, so the description carries the full burden of behavioral disclosure. It mentions account isolation, which is a useful semantic constraint, but does not disclose behavior like ranking semantics, result format, pagination, cost/latency, or what happens with empty or poor-match queries. For a search operation with zero annotation coverage, this is a noticeable gap.

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-loaded with the core purpose, zero filler. It is appropriately short for a straightforward search tool, though it could add a sentence of behavioral detail without becoming 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?

This is a relatively simple three-parameter tool with an output schema present, which lowers the completeness bar. However, no annotations and 0% schema coverage mean the description should explain the semantic search semantics, result behavior, and how it differs from knowledge_search. It covers the basics but leaves ranking/result details open.

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 0%, so the description must compensate. It mentions 'query' and 'account_id' implicitly through the account-isolation note, but provides no detail about what 'limit' does beyond schema defaults, no guidance on query format, and no semantics around result scoring or threshold behavior. The description adds minimal value over the bare 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?

The description uses a specific verb ('Run semantic similarity search') with a clear resource ('OKF vector index') and explicitly notes account isolation. It distinguishes reasonably from siblings like email_search and knowledge_search, which are also retrieval tools, though it doesn't name them explicitly.

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 implies usage context (semantic search against OKF index) and mentions account isolation as a scoping constraint. However, it does not explicitly state when to prefer this over knowledge_search, email_search, or other sibling retrieval tools, nor when not to use it.

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