Zotero Chunk RAG

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

With no annotations provided, the description carries the full burden of behavioral disclosure. It describes the return format ('List of results with passage text, context, and metadata') and mentions 'relevant passages with surrounding context,' which adds value beyond basic functionality. However, it lacks details on permissions, rate limits, or error handling that would be helpful for a search tool.

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 and front-loaded with the core purpose, followed by clear sections for Args and Returns. Every sentence earns its place by providing essential information without redundancy, making it efficient and easy to parse.

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's moderate complexity (5 parameters, no annotations, but with an output schema), the description is largely complete. It explains parameters thoroughly and notes the return format, though it could benefit from more behavioral context (e.g., performance hints or limitations). The output schema reduces the need to detail return values, but some gaps remain in usage guidance.

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 must fully compensate. It provides detailed semantics for all 5 parameters: 'query' as a natural language search query, 'top_k' with range (1-50), 'context_chunks' with range (0-3), and 'year_min/year_max' as publication year filters. This adds significant meaning beyond the bare 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 'Semantic search over research paper chunks' which specifies the verb (search), resource (research paper chunks), and method (semantic). It distinguishes from siblings like 'get_index_stats' (statistics), 'get_passage_context' (context retrieval), and 'search_topic' (topic-based search) by focusing on semantic search over chunks.

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 provides no guidance on when to use this tool versus alternatives like 'search_topic' or other siblings. It mentions what the tool does but lacks explicit when/when-not instructions or prerequisites, leaving the agent to infer usage from context alone.

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