list_clients
List the email clients this deployment can render right now, with their rendering tier, engine, and capabilities
Input Schema
| Name | Required | Description | Default |
|---|---|---|---|
No arguments | |||
List the email clients this deployment can render right now, with their rendering tier, engine, and capabilities
| Name | Required | Description | Default |
|---|---|---|---|
No arguments | |||
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description must convey behavior. It states the tool lists clients that 'this deployment can render right now', implying current state read-only access, but does not explicitly mention idempotency, data freshness, or side effects.
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, well-structured sentence that conveys the essential information without any redundant or irrelevant details.
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?
The tool is simple with no parameters and no output schema, but the description adequately explains what is returned (list of clients with rendering tier, engine, and capabilities). It meets the needs for this tool's complexity.
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 no parameters, so schema coverage is 100%. The description adds no parameter information because none exists, but the baseline for zero-parameter tools is 4.
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 email clients with rendering details (tier, engine, capabilities), distinguishing it from sibling tools like get_job, get_screenshot, and submit_preview which focus on different operations.
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 is clear about the tool's function but does not explicitly state when to use it vs alternatives. However, the sibling list shows distinct tool purposes, so usage context is implied and sufficient.
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 has a clear and distinct purpose: submitting previews, checking job status, fetching specific screenshots, and listing clients. No overlapping functionality.
All tool names follow a consistent verb_noun pattern (get_job, get_screenshot, list_clients, submit_preview), making them predictable and easy to distinguish.
With four tools, the server is well-scoped for its purpose—submitting email previews, tracking jobs, retrieving screenshots, and listing clients. No tools feel extraneous or missing.
The toolset covers the full workflow: submission, status polling, screenshot retrieval, and client discovery. There are no obvious gaps for the stated purpose of rendering email previews.