Fetch a rendered screenshot. Returns the image URL for the given job, client, width, and environment (color scheme / images).
| Name | Required | Description | Default |
|---|---|---|---|
| client | Yes | Client ID | |
| job_id | Yes | The job ID | |
| color_scheme | No | The render's color scheme | light |
| viewport_width | Yes | Viewport width of the render, matching the job (1280 when the job used client defaults) | |
| images_disabled | No | Whether the render had images blocked |
Changes observed during successful MCP inspections. Dates show when Glama detected each change.
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description bears full responsibility for behavioral disclosure. It only states the action and return value, omitting details like side effects, permissions, rate limits, or error conditions. No contradiction with annotations (none provided).
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?
Extremely concise two-sentence structure with front-loaded action. Every word adds value, no filler. Ideal length for quick comprehension.
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 5 parameters and no output schema, the description is too brief. It mentions return type (URL) but lacks details on prerequisites, default behavior for optional parameters, or what happens with invalid inputs. Schema annotations absent, so completeness relies solely on description.
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 description coverage is 100%, so baseline is 3. The description groups 'color scheme / images' as 'environment', adding minor context, but does not provide meaning beyond the schema's individual parameter descriptions.
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?
Description clearly states it fetches a rendered screenshot and returns an image URL, naming key parameters (job, client, width, environment). While not explicitly contrasting with sibling tools, the action is distinct enough to infer usage.
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?
No guidance on when to use this tool versus siblings like get_job or submit_preview. The description implies its purpose but does not set usage boundaries or prerequisites.
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.
