semantic_search

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

With no annotations, the description discloses hybrid search weights (50% vector, 30% keyword, 20% authority) and mentions vector reranking. It does not discuss authorization, rate limits, or side effects, but provides good operational detail.

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 well-structured with a clear purpose sentence, followed by a bulleted hybrid search breakdown, and a parameter list. Every sentence adds value with no redundancy or fluff.

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?

Given 6 parameters, no output schema, and no annotations, the description explains search behavior, parameter details, and return values (ranks results across libraries). It could mention read-only nature but is sufficiently 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?

The schema has 0% description coverage, but the description's 'Args' block explains each parameter's meaning and defaults (e.g., version defaults to 'latest', auto_detect_version defaults to False). This adds significant value beyond the raw 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 clearly states the tool performs 'Enhanced semantic search across one or more libraries with AI-powered relevance ranking.' It uses specific verbs (search) and resources (libraries), and distinguishes from simpler search tools like filtered_search.

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 semantic search but does not explicitly contrast with sibling tools like filtered_search or suggest when not to use this tool. No alternatives or exclusions are mentioned.

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