search

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

No annotations are provided, so the description carries full burden. It discloses a silent fallback returning empty results on error, a fixed limit of 10 results, deep-link URL format, and that natural language queries work via embedding match. While it doesn't mention read-only nature explicitly, the behavior is clear enough 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 relatively long but each sentence adds value: purpose, usage guidance, output format, parameter details, error handling, and an example. It is well-structured and front-loaded with the most critical information.

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 complexity—specialized for a specific client, with a single parameter and an explicit output format—the description covers all necessary aspects: purpose, usage context, parameter semantics, output structure, error behavior, and prerequisites. It is fully complete for an 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?

The input schema has one parameter 'query' with no description (0% coverage). The description adds that it is a topic string and that natural language works (embedding match), providing meaningful context beyond the 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 it performs semantic search over the active Zotero library and returns a JSON string with specific fields. It explicitly distinguishes from sibling tools by specifying that this endpoint is for the ChatGPT connector, while alternatives like zotero_semantic_search and zotero_search_items should be used in other contexts.

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 states when to use this tool (via the ChatGPT connector) and when not to (in general MCP contexts, recommending other tools). It also provides a prerequisite: running zotero_update_search_database first if empty.

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