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search_hybrid

Combines semantic and full-text search results using Reciprocal Rank Fusion to retrieve relevant notes. Supports optional graph expansion to include neighboring notes.

Instructions

Hybrid search: combines semantic (embedding) and BM25 (full-text) results via Reciprocal Rank Fusion. Best general-purpose query. Pass expand: {hops: 1} to auto-attach 1–2 hop typed-edge neighbors as expansions[] per hit (preserves ranking; runs after recency/authority rescore).

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
queryYes
rrf_kNo
top_kNo
expandNo
rerankNo
vaultsNo
exclude_pathsNo
half_life_daysNo
recency_weightNo
authority_weightNo
frontmatter_boostsNo
frontmatter_filterNo
include_supersededNo
Behavior4/5

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

With no annotations provided, the description discloses key behavioral traits beyond the schema: it explains the RRF fusion method, and details that expand runs after recency/authority rescore and preserves ranking. This gives useful insight into the tool's internal processing, though it doesn't cover return format or error behavior.

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?

The description is concise, front-loaded with the core purpose, and every sentence contributes value. The first sentence defines the tool in one line, and the second adds an optional behavior with a clear code example and caveat, with no filler.

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

Completeness2/5

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

The tool is complex (13 params, nested objects) with no output schema and no annotation support. The description covers the core mechanism and one optional feature, but leaves most parameters undocumented, making it difficult for an agent to fully utilize the tool without additional information.

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

Parameters1/5

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

The schema has zero description coverage for 13 parameters. The description only explains the expand parameter in detail and implicitly references the query. All other parameters (rrf_k, top_k, rerank, half_life_days, recency_weight, authority_weight, etc.) remain completely unexplained, failing to compensate for the schema's lack of semantic information.

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 the tool performs a hybrid search combining semantic and BM25 results via Reciprocal Rank Fusion, naming the specific resource and behavior. It distinguishes itself from sibling tools like search_text and search_semantic by calling it the 'best general-purpose query.'

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 provides clear context for when to use this tool ('Best general-purpose query') and gives a specific usage tip for the expand parameter. It does not explicitly name alternatives or exclusion criteria, but the guidance is practical and distinct.

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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