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hou_tea_recommend

Get ranked tea recommendations from a natural-language query. Provides explanations for each product, tailored to your mood, occasion, or use-case.

Instructions

[core] Get curated tea recommendations from a natural-language query. Returns ranked products with explanation. Best entry point when the user asks 'recommend me a tea for X' or describes a mood / occasion / use-case.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
queryYes
budget_maxNo
occasionNo
limitNo
Behavior2/5

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

No annotations provided, so the description must fully disclose behavioral traits. It mentions 'curated' and natural-language processing but does not state whether the tool is read-only, if it modifies any state, or if any permissions/authentication are needed. The behavior beyond the basic purpose is insufficiently described.

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

Conciseness5/5

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

Two concise sentences that front-load the core purpose and provide usage context. No unnecessary words; every sentence serves a purpose.

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

Completeness3/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given the lack of annotations and output schema, the description covers the basic function and typical use case but omits details about parameters (especially budget_max and occasion) and the exact return format beyond 'ranked products with explanation'. It is minimally complete but could be enhanced.

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

Parameters2/5

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

Schema description coverage is 0%, so the description must explain parameters. Only the query parameter is implicitly described as a natural-language query. The remaining parameters (budget_max, occasion, limit) are not explained, leaving the agent to infer meaning solely from parameter names and types.

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?

Description clearly states it provides tea recommendations from a natural-language query and returns ranked products with explanation. It distinguishes itself from sibling tools like hou_tea_browse (general browsing) and hou_tea_discover_extended (extended discovery) by focusing on personalized recommendations and being the best entry point for recommendation requests.

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?

Explicitly indicates it is the best entry point when the user asks for a recommendation or describes a mood/occasion/use-case. While it does not mention when to avoid this tool, it provides clear context for its use relative to other tools.

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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