Iconsult MCP

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 does well by explaining what the tool returns ('full text, chapter, page numbers, section title, suggested_questions'), the deterministic nature of suggested questions, and the logging capability. However, it doesn't mention potential limitations like rate limits, error conditions, or whether this is a read-only operation (though implied by 'search').

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 with three sentences that each serve a distinct purpose: explaining the core functionality, providing usage guidance, and describing logging. It's front-loaded with the most important information. The 'DEEP CONTEXT' prefix is slightly verbose but doesn't significantly detract from overall efficiency.

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?

For a tool with 4 parameters, no annotations, and no output schema, the description provides adequate coverage of the tool's purpose and usage context. However, it doesn't fully compensate for the lack of output schema by describing the exact structure of returned passages or the format of suggested_questions. The description is complete enough for basic understanding but leaves some implementation details unspecified.

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?

With 100% schema description coverage, the baseline is 3 even without additional parameter information in the description. The description does add some context about 'concept_ids from get_subgraph' and 'consultation_id to log retrieval steps', but doesn't provide significant semantic value beyond what's already documented in the 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?

The description clearly states the tool's purpose with specific verbs ('RAG search', 'embeds', 'returns') and resources ('book sections', 'passages'). It distinguishes from siblings by mentioning 'concept_ids from get_subgraph' and 'consultation_id from match_concepts', showing awareness of related tools. The description goes beyond the name 'ask_book' to explain the retrieval-augmented generation mechanism.

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 clear context for when to use this tool ('ALWAYS scope with concept_ids from get_subgraph for precision') and mentions prerequisites ('Pass consultation_id to log retrieval steps'). However, it doesn't explicitly state when NOT to use it or name specific alternatives among the many sibling tools, which prevents a perfect score.

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