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

Annotations already communicate readOnlyHint=false, destructiveHint=false, and idempotentHint=false, so the description's value is additive. It discloses that the created draft is the only mutable surface, outlines the workflow lifecycle, and directs the agent to follow llmContext guidance in results. This goes beyond the structured hints without contradicting them.

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?

Each of the four sentences earns its place: definition, creation modes, lifecycle, and result-context instruction. The stage-flow shorthand (parse → extract/classify/split → validations → human review) is compact and informative, though the second sentence is dense enough that a slight split would improve readability.

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 high-complexity tool with an output schema, the description covers creation modes and lifecycle, and deliberately defers deep step-graph authoring rules to a linked documentation call. The steps-param routing rules live in the schema, and return values are covered by the output schema, so nothing critical for invocation is missing.

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 100%, so baseline is 3 — the schema already documents all four parameters. The description adds cross-parameter semantics that isolated property descriptions cannot convey: name alone creates an empty draft, while steps builds the graph eagerly. This is meaningful supplemental meaning.

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 names a concrete verb-object pair ('Create a workflow') and clarifies what the resource is — a multi-step document pipeline with a specific stage flow (parse → extract/classify/split → validations → human review). It also distinguishes itself from lifecycle siblings like update_workflow, deploy_workflow_version, and run_workflow, so the agent can pick the right tool.

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?

It explicitly contrasts the two creation modes — name alone yields an empty draft, while steps builds the graph eagerly — and instructs the agent to call get_documentation with a specific URL before hand-authoring a step graph. It also names the alternatives for subsequent operations (update_workflow, deploy_workflow_version, run_workflow), giving clear when-and-when-not context.

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