qdrant_search

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

Annotations already declare readOnlyHint=true, destructiveHint=false, idempotentHint=true. Description adds significant behavioral context: uses Ollama for embedding, Qdrant for search, lists specific error messages (collection not found, embedding failed, connection error), and details advanced processing steps like RRF and LLM reranking.

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?

Well-structured with clear sections (general description, advanced features, Args, Returns, Errors) and front-loaded purpose. While somewhat verbose, each sentence adds necessary context for a complex tool.

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?

Comprehensively covers all aspects: purpose, all parameters (including advanced ones), return format (formatted string with similarity scores), and specific error cases. No gaps given the tool's complexity.

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 descriptions cover all parameters, but description adds value by explaining advanced behavior (e.g., 'auto-embedded', 'generates hypothetical document'), default values, and constraints like 'max 100 results', which goes beyond the basic schema descriptions.

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?

Description clearly states 'Search for similar documents in Qdrant' with specific verb 'search' and resource 'Qdrant vector database'. Distinguishes from sibling qdrant_list_collections by focusing on searching within a collection.

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?

Provides detailed usage context including advanced features like query expansion, HyDE, and reranking. Though no explicit when-not-to-use, the single sibling makes intent clear: this is for searching, not listing collections.

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