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add_database_entry

Create one database entry in Notion using simple key-value property inputs, supporting text, numbers, select options, dates, checkboxes, relations, and people.

Instructions

Create one database entry using simple key-value property inputs. Call get_database first to see available property names and valid select/status options.

Writable property values use simple inputs:

  • title, rich_text: string

  • number: number

  • select, status: option name string

  • multi_select: array of option name strings

  • date: ISO date string (start only)

  • checkbox: boolean

  • url, email, phone: string

  • relation: string or array of page IDs

  • people: string or array of user IDs

Not writable from this tool:

  • formula, rollup, unique_id, created_time, last_edited_time, created_by, last_edited_by: computed by Notion

  • files, verification, place, location, button: not supported for value writes here

Example: { "Name": "Buy groceries", "Status": "Todo", "Priority": "High", "Due": "2025-03-20", "Tags": ["Personal"] }.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
database_idYesDatabase ID
propertiesYesKey-value property map to convert using the database schema
Behavior4/5

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

No annotations are provided, so the description carries the full burden. It clearly states the tool creates an entry and enumerates supported property types. However, it does not disclose authorization requirements, rate limits, or return value structure, though the behavioral intent is well covered.

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 well-structured and front-loaded with the core purpose. It is concise enough but could be slightly more terse by omitting the full list of not-writable types, though that list adds context. Still efficient overall.

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 complexity (nested properties, no output schema) and the presence of sibling tools, the description adequately covers what the tool does and what property types are supported. It lacks details on the response format, but for a creation tool, the description is sufficient for an agent to use it correctly.

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 description coverage is 100%, but the description adds significant value by explaining how the properties map should be constructed, including type constraints and example formats. This goes beyond the schema's brief descriptions.

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?

Description explicitly states 'Create one database entry' using key-value inputs, clearly distinguishing it from sibling tools like add_database_entries (bulk) and update_database_entry. The verb+resource is specific and unambiguous.

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

Usage Guidelines5/5

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

Provides direct guidance to first call get_database to discover property names and valid options. Also lists writable vs non-writable property types, helping the agent decide when this tool is appropriate and what data to prepare.

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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