start_workflow

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

With no annotations provided, the description carries the full burden of behavioral disclosure. It mentions the action ('Start a workflow execution') but lacks critical details: it doesn't specify whether this is a read-only or destructive operation, what permissions are required, how errors are handled, or what the execution entails (e.g., asynchronous vs. synchronous). This leaves significant gaps for an agent to understand the tool's behavior.

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 highly concise and well-structured: the first sentence states the core purpose, and the second provides a practical example without unnecessary details. Every sentence earns its place by adding clear value, making it easy to parse and understand quickly.

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 of starting a workflow execution (a potentially destructive operation with 3 parameters and no output schema), the description is minimally adequate. It covers the basic purpose and parameter usage but lacks details on behavioral aspects like side effects, error handling, or return values, which are crucial for safe and effective use by an AI agent.

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?

The description adds some value by explaining the 'input' parameter with an example ('if the workflow expects "company_url", pass: { input: { company_url: "https://..." } }'), which clarifies its purpose beyond the schema's generic description. However, with 100% schema description coverage, the schema already documents all parameters adequately, so the description's contribution is marginal, meeting the baseline score.

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 ('Start a workflow execution') and the resource ('workflow'), making the purpose immediately understandable. However, it doesn't explicitly differentiate from sibling tools like 'retry_execution' or 'stop_execution' which also involve workflow executions, leaving some ambiguity about when this specific tool should be used versus those alternatives.

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 some implied context about when to use the tool ('Optionally provide input data that maps to the workflow's input page fields'), suggesting it's for initial execution. However, it doesn't explicitly contrast with alternatives like 'retry_execution' or mention prerequisites such as needing an existing workflow ID, leaving gaps in comprehensive guidance.

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