SECONDARY (user-driven UI): propose a NEW screen → Inbox. parent = popup over that screen; purpose grounds AI suggestions. Whole UI? design_ui_from_systems first.
| Name | Required | Description | Default |
|---|---|---|---|
| name | Yes | Screen name (Title Case, English) | |
| parent | No | Make it a POPUP over this screen | |
| purpose | No | What this screen is for | |
| project_id | No |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations only include destructiveHint=false. The description adds useful context by explaining that parent creates a popup over another screen and that purpose grounds AI suggestions, and it indicates a proposal workflow via '→ Inbox'. However, it does not disclose the proposal lifecycle, permissions, or return behavior, leaving some ambiguity about what happens after the proposal is created.
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 packs essential guidance into a single dense sentence, using arrows and semicolons efficiently. It is not padded, though the 'SECONDARY (user-driven UI)' prefix is slightly jargon-heavy and could be clearer.
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 tool's low complexity (4 params, no output schema, no enums), the description covers core behavior, key parameter roles, and the primary alternative tool. It omits the project_id parameter and does not describe return values, but these are minor gaps given the available sibling context.
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 covers 75% of parameters with descriptions. The description adds functional meaning for 'parent' ('popup over that screen') and 'purpose' ('grounds AI suggestions'), going beyond the schema. The 'project_id' parameter remains undocumented in both schema and description, preventing a perfect score.
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 'propose a NEW screen → Inbox', specifying the action, the resource (screen), and the receiving queue. It distinguishes this tool from sibling propose_* tools by targeting screens specifically and points to design_ui_from_systems for whole-UI work, making its scope unambiguous.
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?
It explicitly frames itself as 'SECONDARY (user-driven UI)' and instructs 'Whole UI? design_ui_from_systems first', naming a concrete alternative for a different use case. This provides clear when-to-use and when-to-use-other guidance, exceeding the minimum.
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.