Skip to main content
Glama
sosadly
by sosadly

screenshot_views

Capture multiple camera angles of a 3D model in one call to identify gaps, rotations, missing detail, and asymmetry from all sides.

Instructions

Capture several camera angles in ONE call and return them all as images, so you can see the whole model and catch problems (gaps, wrong rotations, missing detail, asymmetry) from every side. Defaults to iso/front/left/back. This is the main way to review and iterate — do it after each modeling/texturing pass, not just once.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
viewsNoCamera views in order. Each item is a preset id string ('front','back','left','right','top','bottom','isometric_right_front','isometric_left_front') or a {position:[x,y,z], target:[x,y,z]} object. Omit for a sensible default set.
widthNo
heightNo
Behavior2/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

No annotations are provided, so the description must disclose behavioral traits. It mentions returning images but does not specify format, side effects (e.g., file creation), or limitations. For a tool that captures screenshots, missing details like output type or resolution behavior reduce transparency.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness4/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is four sentences with minimal wasted words. It front-loads the main action and adds usage guidance efficiently. Could be slightly more structured but is concise overall.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness2/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

No output schema exists, so the description should explain return values (e.g., image format, encoding). It only says 'return them as images'. Missing details like number of images, coordinate system, or error handling. For a tool with moderate complexity, this is incomplete.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters2/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema coverage is 33%—only the 'views' parameter has a description. The tool description adds context for 'views' (defaults) but provides no info for 'width' and 'height', leaving those parameters undocumented. With low coverage, more compensation is needed.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose5/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the action ('capture several camera angles... and return them as images') and the resource (model views). It distinguishes from the sibling 'screenshot' tool by emphasizing multiple views in one call, making purpose unambiguous.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines4/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description provides explicit usage guidance: 'This is the main way to review and iterate — do it after each modeling/texturing pass, not just once.' It also mentions default views. It does not explicitly exclude alternatives but the context strongly implies when to use.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

Install Server

Other Tools

Latest Blog Posts

MCP directory API

We provide all the information about MCP servers via our MCP API.

curl -X GET 'https://glama.ai/api/mcp/v1/servers/sosadly/blockbench-mcp'

If you have feedback or need assistance with the MCP directory API, please join our Discord server