Create a label to tag assistants (e.g. "inbound", "outbound"). Assign via the label_ids field on create_assistant / update_assistant.
| Name | Required | Description | Default |
|---|---|---|---|
| name | Yes | Label name (max 255 chars, unique per account) | |
| color | No | Badge color |
| Name | Required | Description | Default |
|---|---|---|---|
| data | No | ||
| message | No |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already indicate a write operation, and the description adds valuable behavioral context such as uniqueness constraint ('max 255 chars, unique per account') and the intended lifecycle (create then assign). No contradictions with 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?
Single sentence that efficiently conveys purpose and usage. No redundant or unnecessary information.
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 creation tool, the description covers the purpose, usage, and lifecycle. The existence of an output schema and full parameter descriptions in the schema complement the description well.
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 coverage is 100%, so baseline is 3. The description provides example values ('inbound', 'outbound') but does not add substantive parameter meaning beyond what the schema already offers.
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 'Create a label to tag assistants' with concrete examples ('inbound', 'outbound'), and distinguishes this tool from other create_* tools (e.g., create_assistant) by specifying it creates labels, not other entities.
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 tells how to use the label after creation ('Assign via the label_ids field on create_assistant / update_assistant'), providing clear context. It does not explicitly state when not to use this tool, but the guidance is sufficient for a creation tool.
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.
