Create a new AirPipe configuration (config_yaml is base64-encoded YAML) and optionally deploy it to staging or production.
| Name | Required | Description | Default |
|---|---|---|---|
| role_uuid | No | ||
| permission | No | ||
| config_yaml | Yes | ||
| deploy_staging | No | ||
| deploy_production | No | ||
| organization_uuid | No |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries full burden. It reveals that config_yaml is base64-encoded and that deployment can be to staging/production. However, it omits behaviors such as success/failure responses, idempotency, or overwriting behavior, which are relevant for an AI agent.
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 a single sentence that effectively front-loads the primary action and encoding detail. While it could benefit from more structure (e.g., listing parameters), it remains concise and to the point.
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?
Given the complexity (6 parameters, optional deployment, no output schema or annotations), the description does not fully equip an agent. Many parameters are undocumented, and the deployment intent is vague. The description lacks enough context for proper tool invocation.
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?
Schema description coverage is 0%, so the description must compensate. It adds meaning for config_yaml (base64-encoded YAML) and hints at deploy_staging/deploy_production, but leaves role_uuid, permission, and organization_uuid unexplained. This is insufficient given the low schema coverage.
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 action (create) and resource (AirPipe configuration), specifies that config_yaml is base64-encoded YAML, and mentions optional deployment. It effectively distinguishes from siblings like create_module, delete_config, and update_config.
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 mentions optional deployment but does not provide explicit guidance on when to use this tool versus alternatives like update_config or deploy_config_revision. The context of sibling tools suggests a need for clearer differentiation, but the description does not address it.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Add one secure layer between your agents and this server.
Every tool has a clearly distinct purpose, targeting either configs or modules with specific actions (create, get, list, delete, update, deploy, etc.). The only potential overlap is between edit_config and plan_config, but they serve different stages of config management (editing vs. authoring).
The naming follows a verb_noun pattern consistently (e.g., create_config, delete_config, list_configs). Minor inconsistency: 'list_configs' uses plural while most others use singular (config). Overall, the pattern is predictable and clear.
With 19 tools, the count is slightly above average but justified by the need to manage two resource types (configs and modules) with full lifecycle operations including deployment, revision handling, and validation. It is well-scoped for a configuration management server.
The tool surface is comprehensive, covering CRUD for both configs and modules, plus deployment, undeployment, toggling, revision management, editing via NL, planning, and validation. No obvious gaps for the intended domain.