semantic_search

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

There are no annotations, so the description must carry the behavioral disclosure burden. It usefully reveals the fallback from embeddings to keyword search, which is genuine behavioral context, but it does not describe the result shape, ranking behavior, or what happens when the search returns no matches.

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 carry the core function and an important fallback behavior with no filler. The primary purpose is front-loaded and the secondary behavior follows naturally.

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 description is adequate for a simple search tool but leaves gaps: no annotations exist, no output schema is provided, and the description does not describe return values, the role of limit, or the relationship to sibling search tools. The fallback mention adds useful context but does not fully round out the calling picture.

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 for the lack of parameter documentation. It provides minimal context for 'query' by describing semantic search, but 'limit' is completely unexplained, including its effect or default behavior.

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 identifies the tool as semantic search over the wiki, which is a specific verb and resource. It does not explicitly differentiate itself from sibling search tools like search_wiki or search_in_project, so it falls just short of full sibling differentiation.

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 the tool should be used when embedding-based semantic matching is needed, and mentions fallback behavior when embeddings are unavailable. However, it does not explicitly state when to prefer this over search_wiki or when keyword search would be a better choice.

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