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search_hybrid

Search academic papers by combining full-text and semantic vector searches to find the most relevant text chunks.

Instructions

混合搜索文献库

使用全文搜索(FTS)和向量相似度搜索的组合,找到与查询最相关的文本块。

Args: query: 搜索查询字符串 k: 返回结果数量,默认 10 alpha: 向量搜索权重(0-1),默认 0.6。FTS 权重为 1-alpha per_doc_limit: 每篇文档最多返回的 chunk 数量,默认 3(避免单篇论文刷屏) fts_topn: FTS 候选数量,默认 50 vec_topn: 向量候选数量,默认 50

Returns: 搜索结果,包含: - results: 按相关性排序的 chunk 列表 - fts_candidates: FTS 候选数量 - vec_candidates: 向量候选数量

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
queryYes
kNo
alphaNo
per_doc_limitNo
fts_topnNo
vec_topnNo

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Behavior4/5

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

No annotations provided, so description carries full burden. It details the hybrid approach, per-document chunk limit to avoid spamming, and alpha weighting. However, it does not disclose performance considerations or error conditions.

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?

The description is structured with numbered Args and Returns sections. It is clear but slightly verbose; some parameter explanations could be shorter. However, it is well-organized and front-loaded with the purpose.

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

Completeness4/5

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

Given the tool has 6 parameters, no annotations, and an output schema implied from the Returns, the description covers the core functionality, parameters, and return fields. It lacks prerequisites or edge cases but is fairly complete for a search tool.

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

Parameters5/5

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

Schema coverage is 0%, but the description fully explains all 6 parameters with their purpose, defaults, and constraints (e.g., alpha range 0-1, per_doc_limit to avoid single paper overwhelming results). This adds significant value beyond the schema.

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?

The description clearly states it performs hybrid search combining full-text search and vector similarity, with specific verb '搜索' and resource '文献库'. It distinguishes itself from siblings like search_fts_only and search_vector_only by explicitly mentioning the combination.

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?

The description explains what the tool does and its parameters, but does not explicitly state when to use this tool vs the separate FTS or vector search tools. However, the presence of siblings provides context, and the description implies it's for queries needing both modalities.

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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