Purchase a phone number returned by search_phone_numbers (monthly subscription).
| Name | Required | Description | Default |
|---|---|---|---|
| phone_number | Yes |
| Name | Required | Description | Default |
|---|---|---|---|
| data | No | ||
| message | No |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already indicate non-read-only and non-destructive behavior. The description adds the 'monthly subscription' detail, which hints at ongoing cost but does not fully describe side effects (e.g., billing implications, number allocation).
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 sentence that front-loads the verb and resource, with no unnecessary words. Every part earns its place.
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 tool with one parameter and existing annotations, the description covers the core purpose, prerequisite, and subscription nature. It could mention the return value (e.g., created phone number details) but the output schema may compensate.
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 provides context that the phone_number parameter must come from search_phone_numbers, adding meaning beyond the raw schema (0% description coverage). However, it does not specify format, validation, or constraints like country code.
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 action ('Purchase') and the specific resource ('a phone number returned by search_phone_numbers'), including the context of a monthly subscription. It distinguishes from sibling tools like search_phone_numbers and release_phone_number.
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 implies that the tool should be used after search_phone_numbers and mentions the subscription model. However, it does not explicitly state when not to use it or provide alternatives beyond the implicit prerequisite.
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.
Most tools target distinct resources and actions clearly (e.g., create_assistant vs create_campaign). However, there is some overlap like get_outbound_assistants vs get_assistants and list_all_phone_numbers vs get_phone_numbers, causing minor ambiguity.
Tools follow a consistent verb_noun pattern with underscores (e.g., create_document, delete_label, get_voices). Only minor deviations exist, such as generate_ai_reply and list_all_phone_numbers, but overall the pattern is maintained.
With 75 tools, the server is excessively large. Although the domain is broad (assistants, calls, messaging, etc.), the number of tools makes it difficult for agents to navigate and select the correct one, reducing coherence.
The tool set covers CRUD operations for most resources, plus webhooks, AI replies, and reference data fetching. Minor gaps exist (e.g., no delete_conversation, no attach phone number to assistant), but the surface is largely comprehensive for the platform's purpose.
