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ask_experts

Routes questions to the most relevant expert knowledge bases, retrieves and reranks passages with citations, and optionally synthesizes a grounded answer.

Instructions

Ask the mixture of domain experts a question.

The server routes the question to the most relevant expert knowledge base(s), runs hybrid retrieval + reranking, and returns the best-supported passages. EACH passage includes a citation (title, author, location). You MUST cite these sources in your answer using their bracket numbers, and answer only from them.

Args: question: The natural-language question. top_k: Max passages to return (default 8). experts: Optional list of expert names to force; omit to auto-route. synthesize: If true, the server also returns a grounded, cited answer string.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
top_kNo
expertsNo
questionYes
synthesizeNo
Behavior4/5

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

Describes the process: routing, hybrid retrieval, reranking, and citation format. Mentions the 'synthesize' option for a grounded answer. No annotations provided, but the description covers the behavior adequately without contradicting any metadata.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness4/5

Is the description appropriately sized, front-loaded, and free of redundancy?

Well-structured with an introductory paragraph and a clear parameter list. No unnecessary fluff, but could be slightly more concise. The instruction to cite sources is important and placed appropriately.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness5/5

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 complete context: how the question is processed, what the output contains (passages with citations, optional synthesized answer), and how to use the result.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters4/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

All four parameters are explained with meaningful descriptions beyond the schema (which has 0% description coverage). 'question' is clearly natural-language, 'top_k' has default, 'experts' explains optional forcing, 'synthesize' explains its effect.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose5/5

Does the description clearly state what the tool does and how it differs from similar tools?

Clearly states the tool retrieves answers from domain experts using hybrid retrieval and reranking. Differentiates from siblings ('get_source' retrieves a specific source, 'list_experts' lists experts) by focusing on question answering with citations.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines4/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

Provides explicit usage instruction to cite sources, but does not explicitly contrast with sibling tools or state when not to use. Implicitly guides that questions should be natural-language and experts can be forced or auto-routed.

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

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