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list_integrations

Read-onlyIdempotent

List organization-level AI provider integrations with optional workspace or type filters. Retrieve integration slugs and details before updating models or workspaces.

Instructions

List org-level AI provider connections with optional workspace or type filters. Use this to find integration slugs before model or workspace updates. Returns total plus id, name, slug, provider, status, description, workspace counts, and config summary.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
current_pageNoPage number for pagination
page_sizeNoNumber of results per page (default 100, max 100)
workspace_idNoFilter integrations accessible by a specific workspace
typeNoFilter by integration type: 'workspace', 'organisation', or 'all' (default)

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
okYesWhether the tool call succeeded and returned structured data
dataNoStructured success payload when ok is true
errorNoStructured error payload when ok is false
Behavior4/5

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

Annotations already declare readOnlyHint, destructiveHint, idempotentHint, openWorldHint. Description adds output field details and filter context, but could mention pagination defaults or sorting.

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?

Two sentences, front-loaded with action, then use case, then output summary. No waste; each sentence earns its place.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness5/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given optional pagination params and existing output schema, the description covers purpose, usage, return fields, and filter options. Complete for a list operation.

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 100% with descriptions for all 4 parameters. Description mentions filters generically but does not add new meaning beyond what schema provides.

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 the verb 'List' and the resource 'org-level AI provider connections', with optional filters. It clearly distinguishes from siblings like list_integration_models by focusing on top-level integrations.

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?

Provides a clear usage scenario: 'Use this to find integration slugs before model or workspace updates.' Does not explicitly exclude alternatives but context implies when to use it.

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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