ONE screen's layout: canvas resolution (use THESE px), elements x/y/w/h, links, popups. Read before editing a screen. has_reference_image:true → get_screen_image shows you the actual image.
| Name | Required | Description | Default |
|---|---|---|---|
| id | No | Preferred | |
| name | No | If no id | |
| project_id | No |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations declare readOnlyHint=true, so the safety profile is already known. The description adds behavioral detail about what is returned (layout elements, links, popups) and the conditional use of get_screen_image based on has_reference_image, going slightly beyond the annotation.
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?
Two sentences, front-loaded with the most important content ('ONE screen's layout'), and no filler. Every word earns its place while conveying the core purpose and an actionable pointer to get_screen_image.
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 read tool with strong annotations and no output schema, the description covers what is returned (resolution, elements, links, popups), the usage case, and the reference-image branch. It could mention error cases or id requirements, but for this complexity it is sufficiently complete.
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 description does not mention or elaborate on any parameters. Schema coverage is 67% (id and name have descriptions, project_id does not), and the description fails to add meaning beyond the schema, such as when to use id vs name or the role of project_id.
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 uses a specific verb ('get') and identifies the resource ('ONE screen's layout') with concrete contents (resolution, elements x/y/w/h, links, popups). It clearly distinguishes itself from siblings like list_screens and get_screen_image by emphasizing 'ONE screen' and the reference-image condition.
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 phrase 'Read before editing a screen' gives explicit when-to-use guidance. The instruction 'has_reference_image:true → get_screen_image shows you the actual image' points to an alternative when a reference image exists. However, there are no explicit when-not-to-use or exclusionary conditions.
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 clearly distinct purpose, with explicit distinctions between direct actions and proposals via Inbox. The verbs and object types (system, milestone, screen, element, balance) are unique enough that no two tools appear to do the same thing.
Most tool names follow a consistent verb_noun snake_case pattern (get_system, propose_screen, update_element). Minor deviations like 'dedupe', 'search', 'next_task', and 'reorder' are single words or non-verb but remain readable and stylistically compatible.
With 54 tools, this server vastly exceeds the typical MCP scope, hitting the 'extreme mismatch' threshold. Even for a complex domain, the sheer number will overwhelm agents and degrade selection performance.
The tool surface is remarkably complete, covering full lifecycle operations for all major entities, plus import, design generation, drift detection, status reporting, inbox handling, and rejection workflows. No obvious dead ends or missing operations for the stated purpose.