List approved templates for a WhatsApp sender (status defaults to "approved").
| Name | Required | Description | Default |
|---|---|---|---|
| status | No | ||
| sender_id | Yes |
| Name | Required | Description | Default |
|---|---|---|---|
| data | Yes |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare readOnlyHint, idempotentHint, and openWorldHint, making the tool's behavioral profile clear. The description adds the default status ('approved') but does not disclose other traits like pagination or data freshness. It does not contradict 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 concise sentence that front-loads the core action. While it could include more parameter details, it contains no extraneous words. Every part contributes to the purpose.
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 the presence of an output schema, the description does not need to detail return values. However, it lacks information on how to use the 'status' parameter (e.g., other acceptable values) and does not mention pagination or errors. The annotations cover safety, but completeness is moderate for a listing tool.
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 0%, requiring the description to document parameters. It mentions the default for 'status' but does not explain 'sender_id' or list possible status values. With no enums in the schema, the description fails to compensate adequately, leaving parameter meaning incomplete.
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 'List approved templates for a WhatsApp sender' with a specific verb and resource. It distinguishes itself from sibling tools like 'send_whatsapp_template' and 'get_whatsapp_senders' by focusing on listing templates. The default status clarification adds precision.
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 when to use the tool (to list approved templates) but does not provide explicit guidance on when not to use it or mention alternatives. The readOnlyHint annotation reinforces its safe usage, but the description could be more directive about appropriate contexts.
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.
