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Search indexed documents using hybrid semantic and keyword matching to improve recall on both meaning and exact terms.

Instructions

Search indexed documents using hybrid semantic + keyword search.

Combines vector similarity and BM25 full-text search via Reciprocal Rank Fusion (RRF) for better recall on both meaning and exact terms.

Args: query: Natural language search query. limit: Maximum number of results (default 10, max 50). document_filter: Optional exact document name to filter by. collection: Optional collection name to search within. page_type: Optional content type filter (text, code, spreadsheet, etc.). source_format: Optional source format filter (.pdf, .py, .xlsx, etc.). agent_handle: Optional agent handle to filter by (e.g. "rmh"). memory_type: Optional memory type filter (fact, observation, etc.).

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
limitNo
queryYes
page_typeNo
collectionNo
memory_typeNo
agent_handleNo
source_formatNo
document_filterNo

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes
Behavior3/5

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

The description discloses the hybrid search algorithm (RRF, vector, BM25) and its rationale, which is a behavioral trait. However, with no annotations provided, it does not explicitly state that the operation is read-only or mention any side effects, though 'search' implies non-destructive behavior. It also does not mention limitations like only searching already-indexed documents, which is a constraint but not fully explicit.

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 well-structured: a concise summary, a mechanism explanation, and a clean Args list. Every sentence earns its place, the format is consistent with the schema, and it is neither too long nor too short. It front-loads the purpose effectively.

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?

The description is highly complete for a search tool: it explains purpose, algorithm, and all parameters, and the existing output schema covers return values. The main gap is the lack of explicit usage guidance versus siblings, which prevents a perfect score, but given the complexity and schema coverage, this is a minor omission.

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?

The input schema has 0% description coverage, so the description carries the full burden for parameter semantics. It compensates exceptionally by documenting all 8 parameters with clear meanings, defaults, max limits, and examples (e.g., agent_handle 'rmh', memory_type 'fact'). This is far beyond the bare 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 the tool's purpose: 'Search indexed documents using hybrid semantic + keyword search.' It specifies the search mechanism (vector similarity + BM25 via RRF) and distinguishes itself from sibling tools like 'list' or 'show' through its search-focused verb and detailed method.

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

Usage Guidelines3/5

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

The description explains how the search works and the available filters, but it does not explicitly state when to use this tool versus alternatives like 'list' or 'show'. Use is implied by the tool's name and purpose, but no exclusions or direct alternative comparisons are provided.

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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