screenshot_previewCapture a screenshot of the user app. Call it whenever you want to SEE what the app currently looks like (layout, styling, rendered state) or want to debug the app.
| Name | Required | Description | Default |
|---|---|---|---|
| projectId | Yes |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare readOnlyHint=true and destructiveHint=false, so the tool's safety profile is covered structurally. The description adds useful context (the tool captures a visual snapshot for inspection/debugging) but does not disclose potential caveats like whether the app must be running, the freshness of the screenshot, or any rate limits. Given the annotation coverage, the description adds some value but not deep behavioral detail.
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, tightly written sentence that front-loads the core action ('Capture a screenshot') followed by explicit usage guidance. Every word serves a purpose; there is no fluff, redundant phrasing, or unnecessary detail. It is a model of conciseness.
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 only one parameter and no output schema. The description explains when to use it and what it does, but it omits any explanation of the projectId parameter and does not mention potential prerequisites (e.g., app running). While annotations cover safety, the lack of parameter guidance and any return expectations leaves gaps that an agent might need to infer, making it adequate but not fully self-contained.
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 input schema has a single required parameter 'projectId' with no description, and the schema_description_coverage is 0%. The description does not mention projectId at all, leaving its purpose, format, or how to obtain it entirely unexplained. With zero coverage and no compensatory text, the parameter semantics are severely deficient.
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 'Capture a screenshot of the user app' and specifies the resource (the user app preview). It distinguishes the tool's purpose from siblings like 'get_preview_url' (which provides a URL, not a visual) or 'navigate_preview' (which changes the view). The mention of 'want to SEE what the app currently looks like' and 'debug the app' gives concrete, concrete use cases.
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 provides explicit guidance on when to call this tool: 'whenever you want to SEE what the app currently looks like' or to debug. This gives a clear context for selection, though it does not explicitly mention alternatives or when-not to use, which prevents it from being a 5. The usage intent is unambiguous enough for an agent to decide correctly.
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.
Tools are mostly distinct, but there is some overlap among file-modifying tools (edit_file, write_file, apply_patch) and between run_code_in_vm and run_code_in_browser. Detailed descriptions and clearly scoped use cases help agents select correctly.
Most tools follow a verb_noun snake_case pattern (create_project, list_files, execute_sql), but a few deviate (apply_patch, card_upload_asset, run_code_in_vm). Overall readable and predictable, with only minor inconsistencies.
With 46 tools, the server exceeds the typical well-scoped range and approaches the extreme threshold. While the broad scope of a full development platform justifies many tools, this count may overwhelm agents and increase misselection risk.
The tool surface covers the full development lifecycle: project creation, file operations, database management, resource provisioning, deployment, testing, and debugging. Minor gaps exist (e.g., no delete_project or checkpoint management), but core workflows are well-supported.