List the three comedic voices (Hype Man, Best Friend Roast, Conspiracy Theorist) and the cover image model each prefers. Free, no side effects. Call this first to pick a voice.
| Name | Required | Description | Default |
|---|---|---|---|
No arguments | |||
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries full burden; it explicitly states 'free, no side effects,' which covers safety and cost, though it lacks details on authentication or rate limits.
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?
Three concise sentences with no wasted words; front-loads the main purpose, then covers safety and usage guidance.
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 no output schema, the description adequately explains what is returned (list of voices with cover image models) and when to use it, though output format is not detailed.
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?
No parameters exist, so baseline is 4; the description adds value by naming the voices and cover image model association beyond the schema.
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 tool lists the three specific comedic voices and their preferred cover image models, distinguishing it from sibling tools like list_formats and list_image_models.
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 'Call this first to pick a voice,' providing clear usage context, though it does not mention when not to use or alternatives.
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 has a clearly distinct purpose: gift lifecycle (create, get, cancel, list), account info, pricing, resource listings, and brief validation. No overlap or ambiguity.
All tools follow a consistent verb_noun pattern in snake_case (e.g., create_gift, list_voices, validate_brief), making it predictable for agents.
12 tools is well-scoped for a gift ordering service, covering creation, retrieval, cancellation, pricing, account management, and resource listings without bloat.
The tool surface covers the full gift lifecycle and supporting operations (pricing, validation, account info, payment setup), with no obvious gaps for the intended domain.