Semantic Vector Search

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

The description adds rich behavioral context beyond annotations: it uses Google Gemini for embedding, returns ranked text chunks with similarity scores, source page references, and direct PDF links. It explains it's semantic search against a vector database. No contradiction with annotations (readOnlyHint=true).

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 appropriately sized, front-loading the priority and purpose. It is structured with clear sections: priority statement, technology, usage guidance, args description, returns, and examples. Every sentence adds value, and no information is redundant.

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 the tool has 4 parameters (1 required) and no output schema, the description fully explains what the tool returns: ranked text chunks with similarity %, subject, topic, page range, and PDF link. It also provides usage context and examples, making it complete for an AI agent to 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?

Schema coverage is 100% with descriptions for all parameters. The description adds extra value with usage tips like 'Be precise' for query and provides default and max values for limit. It also gives concrete examples that illustrate parameter combinations. This goes beyond the schema's baseline but doesn't fully compensate for the schema's already adequate coverage.

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 title 'Semantic Vector Search' and description clearly state the tool performs semantic search over a pre-indexed document library. It distinguishes itself from siblings like fetch_pdf by explicitly instructing to call this first. The verb 'search' and resource 'document library' are specific.

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 explicitly says 'Always call this first before attempting fetch_pdf', providing clear guidance on when to use this tool vs. its sibling. Examples show different usage scenarios, and the description implies this is the primary search tool, not for listing resources or getting single items.

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