list-whitelabel-packagesList whitelabel packages via GET /v1/whitelabel/packages.
| Name | Required | Description | Default |
|---|---|---|---|
No arguments | |||
| Name | Required | Description | Default |
|---|---|---|---|
| result | Yes | JSON or plain text body returned by the Botsify HTTP API |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare readOnlyHint, idempotentHint, and destructiveHint, covering the safety profile. The description adds the HTTP GET method, which reinforces read-only behavior, but provides no additional context like pagination or permission requirements. With annotations present, this is adequate but not exceptional.
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?
A single, front-loaded sentence that directly conveys purpose and method. No filler or redundancy.
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 zero-parameter list operation with strong annotations and an output schema, the description is fully sufficient. The endpoint is specified, and no additional requirements (e.g., permissions, filters) are needed.
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, and the schema coverage is 100% (empty schema). The description does not need to explain parameters, and the baseline of 4 applies since there are no parameter semantics to clarify.
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 'List' and the resource 'whitelabel packages', with the HTTP endpoint providing additional specificity. It distinguishes itself from sibling tools like 'create-whitelabel-package' and 'list-whitelabel-clients'.
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 tool's purpose is self-evident as a read-only listing operation, and the context makes it clear when to use it. However, it does not explicitly mention alternatives or conditions when not to use it, so it stops short of a 5.
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.
Several tools have overlapping purposes, such as send-converse-message, send-inbox-message, send-user-message, and stream-user-message, which all deliver messages but with subtle differences. Similarly, list-bot-messenger-users and list-messenger-users both fetch messenger users, and start-builder-chat, clear-builder-conversation, and store-builder-response all manage builder chat state. Descriptions help, but the boundaries are still confusing.
Tool names consistently use hyphenated lowercase verb-noun format, but the verbs and nouns vary significantly in specificity. For example, 'get-query-response' vs 'query-mcp-agent' vs 'stream-user-message' all imply querying but with different styles. The pattern is readable but not highly predictable, with some names like 'change-user-activation' and 'patch-instruction-section' deviating from the simple verb_object structure.
With 44 tools, this server feels overloaded. The breadth covers bots, messaging, templates, whitelabel, and versions, but many tools could be consolidated (e.g., multiple message-sending variants). The count exceeds the 25-tool threshold for 'too many', making it difficult for agents to select the right tool without extensive context.
The tool set covers the main lifecycle: agent creation, versioning, deployment, deletion, messaging, conversation history, user management, template management, and whitelabel operations. Minor gaps exist, such as missing delete for WhatsApp templates or update operations for user attributes, but these are workable edge cases. Core workflows are well supported.