Seed sandbox analytics test data

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

The description discloses deterministic generation, idempotence, and the refusal to operate on production hosts, production API processes, non-dev databases, or mismatched locations. Even though idempotentHint is already annotated, the production refusal and deterministic behavior add concrete runtime context. It does not explain return values or the dry-run/apply flow, but the output schema and mode parameter cover those.

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?

Two compact sentences place the purpose and scope first, and the guardrail behavior second. Every sentence earns its place with no filler or redundant enumeration of 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?

The tool is moderately complex, but the input schema covers 80% of parameters, an output schema exists, and annotations already declare idempotence and non-destructiveness. The description adds the critical dev-vs-production guardrail and data-domain overview. It is slightly incomplete only in not spelling out the dry-run-before-apply workflow on its own, though mode and planDigest schema descriptions effectively convey it.

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 80%, so the description can rely on the schema for parameter meaning. The prose only indirectly references location/confirmation via the dev organization, adding no syntax or format detail beyond what the schema already provides. This meets the high-coverage baseline but does not surpass it.

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 uses a specific verb and resource: 'Create deterministic customers, orders, ratings, and storefront funnel events' for a named dev organization. This clearly distinguishes the tool from sibling read/manage tools like list_customers or get_location_orders.

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 gives a clear context clue by scoping to the Alvin's Test Hospitality Group dev organization and excludes production/non-dev environments. However, it never names alternative tools or states an explicit when-to-use condition such as 'use this when you need sandbox analytics seed data', leaving sibling comparison to inference.

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