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organizations_get_collection

Retrieve organizations with cursor pagination and date range filtering for efficient large-scale data synchronization and ETL pipelines.

Instructions

Get all organizations using the collection endpoint.

This endpoint provides an alternative way to fetch organizations with different capabilities:

  • Cursor-based pagination (more efficient for large datasets)

  • Date range filtering (since/until)

  • Optimized for data synchronization

  • Better performance for large-scale operations

Key differences from organizations/list:

  • Uses cursor pagination instead of offset/limit

  • Supports date-based filtering for incremental sync

  • More efficient for fetching large volumes

  • Better for ETL and data integration scenarios

Parameters:

  • cursor: Pagination cursor from previous response

  • limit: Items per page (default: 100, max: 500)

  • since: Start date (YYYY-MM-DD) - get organizations modified since this date

  • until: End date (YYYY-MM-DD) - get organizations modified until this date

  • owner_id: Filter by owner user ID

  • first_char: Filter by first character of name

Use cases:

  • Initial data synchronization

  • Incremental updates (using since parameter)

  • Large-scale data exports

  • Integration with external systems

  • ETL pipelines

  • Backup and archival

The cursor-based approach is more reliable than offset pagination for datasets that change frequently, as it maintains consistency even when records are added or deleted during pagination.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
cursorNoCursor for pagination (from previous response)
limitNoNumber of items to return (default: 100, max: 500)
sinceNoStart date for filtering (YYYY-MM-DD format)
untilNoEnd date for filtering (YYYY-MM-DD format)
owner_idNoFilter by owner user ID
first_charNoFilter by first character of name (single letter)
Behavior4/5

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

Since no annotations are provided, the description carries the burden of behavioral disclosure. It explains cursor-based pagination, date filtering, and performance benefits for large datasets. However, it does not explicitly state that the tool is read-only or non-destructive.

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 with sections and bullet points, but some statements are redundant (e.g., 'Better performance' and 'Better for ETL' convey similar ideas). Overall efficient, with no extraneous content.

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 covers usage, parameters, and key differences from alternatives. However, it lacks details about the response format, such as how to interpret the cursor for further pagination. Given no output schema, this additional context would improve completeness.

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 coverage is 100%, but the description adds significant value by detailing each parameter's purpose, default values, constraints (e.g., max 500), and formatting (YYYY-MM-DD). It also explains how parameters like 'since' enable incremental sync.

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 retrieves organizations via a collection endpoint with cursor-based pagination and date filtering. It explicitly differentiates from organizations/list, highlighting unique capabilities like cursor pagination and date-range filtering.

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?

The description provides explicit use cases (initial sync, incremental updates, large-scale exports) and contrasts with the sibling tool organizations/list. It explains when cursor pagination is beneficial over offset pagination.

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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