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appflowy_search

Search documents in a workspace using keywords or natural language queries. Returns matching results with previews and relevance scores.

Instructions

Search documents in a workspace by keyword or natural-language query (full-text plus semantic search when the server has indexing enabled). Returns matching documents with object_id (the page view_id), preview, and score.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
workspace_idYes
queryYes
limitNo
preview_sizeNo
Behavior3/5

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

With no annotations provided, the description carries the full burden for behavioral disclosure. It notes that both full-text and semantic search are used when indexing is enabled, and it details return fields (object_id, preview, score). However, it does not explicitly state that the operation is read-only or non-destructive, which would be expected for a search tool.

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 two sentences, each serving a clear purpose: the first explains the action and method, the second states return fields. No wasted words, and the most critical information is front-loaded.

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 no output schema and no annotations, the description covers the essential aspects: what it searches, how it searches, and what results contain. It is complete enough for a search tool, though it could mention error handling or behavior when indexing is disabled.

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

Parameters3/5

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

Schema coverage is 0%, so the description must compensate. It explains the 'query' parameter (keyword or natural-language query) and implies 'workspace_id' as the scope. However, it does not elaborate on 'limit' or 'preview_size' beyond defaults, missing an opportunity to add value for these parameters.

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 searches documents in a workspace by keyword or natural-language query, specifying the resource (workspace) and action (search). It distinguishes itself from sibling tools, as no other search tool exists among the siblings.

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 clearly indicates when to use the tool (to search documents) and provides context about semantic search availability (when server indexing is enabled). However, it does not explicitly exclude other use cases or mention alternatives, though the sibling list implies no alternative search tool exists.

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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