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Query Data Source By Values

notion_query_data_source_by_values
Read-only

Query Notion data sources using simple filters like Status equals Done or Tags contains AI, without writing raw Notion filter JSON. Automatically validates property names and value types.

Instructions

Query a Notion data source using simple schema-aware filters and sorts instead of raw Notion filter JSON. Use this after notion_inspect_data_source when the user asks for common queries like Status equals Done, Tags contains AI, Due on or before a date, Estimate greater than 3, or Done equals false. The server validates property names, option names, value types, and supported operators before calling Notion.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
matchNoHow to combine multiple filters. all maps to Notion and; any maps to Notion or.
sortsNoSimple property sorts.
formatNoSpecify the response format. 'json' returns the original data structure, 'markdown' returns a more readable format. Use 'markdown' when the user only needs to read the page and isn't planning to write or modify it. Use 'json' when the user needs to read the page with the intention of writing to or modifying it.
filtersNoSimple schema-aware filters. Multiple filters are combined with match=all by default.
page_sizeNoNumber of results per page (max 100)
start_cursorNoPagination cursor for next page of results
response_modeNoControls response size for list-heavy tools. Use auto by default so the server returns compact summaries when the Notion response would be noisy. Use compact when IDs and summaries are enough. Use full only when raw Notion API objects are required for an advanced operation.
data_source_idYesThe ID of the data source to query. It should be a 32-character string (excluding hyphens) formatted as 8-4-4-4-12 with hyphens (-).
Behavior5/5

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

Annotations already indicate read-only and non-destructive. Description adds validation behavior (property names, option names, types) beyond what annotations provide. No contradiction.

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?

Three sentences, front-loaded with purpose, then usage, then validation detail. No wasted words; each sentence adds independent value.

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?

Covers main use cases and workflow (after inspect). Lacks mention of pagination or response structure, but schema covers those. Adequate for a query tool with no output schema.

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

Parameters4/5

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

Schema has 100% coverage, but description adds context like default operator logic and value type guidance (strings for text, numbers for numbers, booleans for checkboxes), enhancing semantics beyond 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 explicitly states it queries a Notion data source with simplified filters/sorts, distinguishes from raw JSON, and gives concrete examples like 'Status equals Done'. It differentiates from sibling tools like notion_query_data_source.

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?

Directs to use after notion_inspect_data_source for common queries, implying alternative for raw JSON. Lacks explicit when-not-to-use or mention of notion_query_data_source but provides clear context.

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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