'Buy' a product (100% fake, no payment). Returns an order id. Then call track_order to watch the absurd delivery. Nothing real happens — it's a joke.
| Name | Required | Description | Default |
|---|---|---|---|
| address | No | any address — the package 'travels' there | |
| product_id | Yes |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description fully discloses the tool's non-real nature ('no payment', 'just a joke') and its key output (returns an order id). It also hints at the absurd delivery behavior of the follow-up tool, adding valuable context beyond the schema.
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 two concise sentences, front-loaded with the critical fake nature, then the return value, then the next step. Every sentence earns its place with no filler.
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 simple joke tool with no annotations and no output schema, the description covers the essential behavior, return value, and follow-up step. It is complete enough for an agent to invoke the tool correctly and understand the expected result.
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 does not elaborate on the parameters beyond what the schema already provides. product_id is self-evident from the tool name 'buy', and address already has a descriptive schema comment. The description adds no additional semantic depth to the parameters, and with 50% schema coverage, it fails to compensate for the undocumented product_id.
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 that the tool simulates a purchase (with quotes around 'Buy'), returns an order ID, and is distinct from sibling tools like get_product, search_products, and track_order. It uses a specific verb and resource, and explicitly positions itself as the fake purchase step.
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 explicitly instructs to call track_order afterward, providing a clear sequential usage pattern. It also states the tool is '100% fake, no payment' and 'Nothing real happens,' which implicitly excludes real-world purchasing and sets expectations for when to use 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.
Each tool handles a distinct step in a simulated shopping flow: search, view, purchase, and tracking. No overlap in purpose.
All tool names follow a consistent verb_noun pattern using snake_case (search_products, get_product, buy, track_order).
Four tools is well-scoped for a parody shop, covering the essential operations without excess or deficiency.
The set provides a complete loop for the simulated experience: discovery, details, purchase, and tracking. No obvious gaps for its intended purpose.