create_integration

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

The description adds significant behavioral context beyond annotations: key is write-only, secret_mappings can resolve keys or configuration fields at runtime, and pricing_adjustments affect cost accounting. It also discloses that the integration becomes the source for workspace providers and returns the new integration id and slug. No contradictions with annotations.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is concise yet comprehensive, with each sentence serving a distinct purpose: purpose, key field explanations, behavior controls, security notes, and follow-up steps. It is front-loaded with the core action and avoids redundancy, making it effective for a tool with 19 parameters.

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

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

For a complex creation tool, the description covers essential aspects: purpose, key parameters, conditional behavior, follow-up actions, and return value. The output schema further defines the return. It lacks explicit prerequisites (e.g., existence of ai_provider_id) but overall provides sufficient context for an agent to invoke the tool correctly.

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

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

While the schema already covers all 19 parameters (100% coverage), the description adds valuable semantic grouping: ai_provider_id identifies the backend, provider-specific fields configure cloud providers, and create_default_provider controls automatic provider creation. It also explains the relationship between key and secret_mappings, going beyond individual parameter descriptions.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the tool's primary function: 'Create an AI-provider integration that becomes the source for workspace providers.' It distinguishes this from sibling tools like create_provider and create_mcp_integration by specifying the integration's role. The mention of provider-specific fields for Azure, Bedrock, Vertex, and custom hosts further clarifies its scope.

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

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

The description provides clear guidance on when to use the tool, including context for workspace-scoped integrations via create_default_provider. It also directs users to use update_integration_models and update_integration_workspaces after creation. However, it does not explicitly state when not to use this tool or mention alternatives like create_provider for different scenarios.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.