semantic_search

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

With no annotations provided, the description carries the full burden of disclosure. It fails to mention any behavioral traits such as how results are ordered, whether indexing is required, performance characteristics, or what constitutes 'semantic understanding.' This is insufficient for a tool with no other behavioral hints.

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 a single, front-loaded sentence with no wasted words. However, it may be overly terse given the tool's complexity and the number of sibling search tools.

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?

Despite 5 parameters and no output schema or annotations, the description provides minimal context. It does not explain the expected return format, how results are scored or ranked, or how 'semantic understanding' works. This is incomplete for an AI agent to select and invoke 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?

Input schema covers 100% of the 5 parameters with descriptions, so the baseline is 3. The description adds no additional meaning beyond the schema; it simply restates the functional purpose.

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 'Search files using semantic understanding' clearly specifies the verb (search) and resource (files), and distinguishes this tool from siblings like search_content or search_files by highlighting the use of semantic understanding rather than keyword or regex matching.

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 for natural language queries versus keyword search, but it does not explicitly state when to use this tool over alternatives like search_files or fuzzy_search, nor does it provide any exclusion criteria or context.

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