search_semantic

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

With no annotations provided, the description must carry behavioral disclosure. It does state that the tool relies on embeddings (bge-m3 via Ollama), which signals semantic vector matching. However, it does not mention dependencies such as index state, result ranking behavior, or limitations, so the behavior is only partially 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?

Single, tightly written sentence with no wasted words; the core semantic mechanism is front-loaded before the model detail. This is appropriately concise.

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?

For a low-complexity search tool with an output schema, most operational details are inferable, but the description omits guidance for choosing this over search_code and any prerequisite behavior such as needing an updated index. It is adequate but not complete.

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 needed to explain the parameters. It only indirectly clarifies that 'query' is a meaning-based search phrase; 'limit' and query formatting/interpretation are left entirely to inference from the schema names and defaults.

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 names a specific verb ('Search'), resource ('code'), and method ('by meaning using embeddings'), which clearly differentiates this from sibling search_code, presumably a lexical search. It goes beyond a vague restatement and identifies the semantic nature of the tool.

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 phrase 'by meaning' implies this is for conceptual/semantic searches rather than exact-string searches, but it never explicitly states when to choose this over search_code or when not to use it. No alternatives or exclusions are named.

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