list_offersIBO's production packages: stable ids, prices, 50% deposits, deliverables, review rounds, and the scope/refund policy. Call this first.
| Name | Required | Description | Default |
|---|---|---|---|
No arguments | |||
| Name | Required | Description | Default |
|---|---|---|---|
| url | No | ||
| offers | No | ||
| studio | No | ||
| currency | No | ||
| policies | No | ||
| how_to_order | No |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare readOnlyHint=true, and the description adds behavioral details such as stable IDs and the fact that this returns package info (prices, deposits, deliverables). It also provides sequencing guidance, which is beyond the annotations.
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 a single, information-dense sentence. It is front-loaded with the core subject and uses a compact list to convey necessary details, followed by a clear actionable directive.
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, read-only, parameterless tool with an output schema, the description fully covers what an agent needs: what the tool lists, what information is included, and when to call it (first). No gaps.
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 tool has zero parameters, so the description doesn't need to explain any. With no params, baseline is 4, and the description's mention of returned fields (ids, prices, etc.) adds useful context.
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 IBO production packages, with specific details like stable ids, prices, and deliverables. This differentiates it from sibling tools that create or retrieve orders, making the purpose unambiguous.
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 instruction 'Call this first' provides explicit sequencing guidance, indicating this is the entry point before other tools. It doesn't mention alternatives, but the sibling tool names make the distinction obvious, giving clear context.
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 targets a distinct purpose: listing offers, creating payment checkout, verifying payment, uploading files, submitting briefs for paid orders, and custom inquiries. No overlap in functionality.
All tools follow a consistent verb_noun pattern (e.g., create_checkout, get_order, list_offers). No mixing of conventions or unclear names.
Six tools cover the entire workflow without excess or deficiency. Each tool serves a necessary step in the process from offer viewing to brief submission.
The tool surface covers the core workflow well. Minor gaps exist (no order cancellation or custom inquiry status retrieval), but these are mitigated by external processes (email) and clear instructions.