create_automation

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

No annotations provided, so description carries full burden. Discloses key behaviors: returns parsed_trigger for human review, does not auto-activate, requires explicit POST to /v1/triggers, includes confirmation_required and notes. Very transparent about lifecycle.

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?

Well-structured: first paragraph defines tool, second gives examples, third explains return and activation step, fourth gives usage guidance. No fluff, each sentence adds value. Front-loaded with key information.

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?

Covers tool purpose, usage, parameters (partially), return format, and follow-up actions. Mentions webhooks but not authentication or permissions. With only two simple params and output schema referenced, it's mostly complete but lacks security context.

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 has 0% description coverage for two required params. Description compensates for 'instruction' with multiple examples, clarifying its natural language format. However, 'mint_id' is not explained; context suggests machine ID but not explicit. Overall adds significant value for instruction param.

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?

Clearly states the tool creates automated monitoring and actions for industrial machines using natural language. Specific verb 'create' and resource 'automation' distinguishing it from siblings like 'activate_automation' or 'delete_automation'. Examples reinforce purpose.

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?

Explicitly says 'USE WHEN: a user wants to set up monitoring, alerts, or automations for machine state transitions.' Provides clear post-use steps (show parsed_trigger to user, ask confirmation). Lacks explicit when-not-to-use but implied by context.

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