Generate a 3D-printable STL from a text prompt: cookie cutter, stamp, or jewelry. Costs $0.15 (USDC, Base). Returns STL file as a base64 resource plus JSON metadata.
| Name | Required | Description | Default |
|---|---|---|---|
| type | No | cookie-cutter | |
| prompt | Yes | What to generate, e.g. 'dachshund', 'maple leaf' | |
| widthMm | No | ||
| heightMm | No | ||
| lengthMm | No | ||
| modelMode | No | cutter | |
| includeBase | No | ||
| includeDetail | No | ||
| wallThicknessMm | No |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries the full burden. It discloses cost ($0.15 USDC on Base) and return format (base64 resource + JSON metadata), which is valuable. However, it doesn't mention prerequisites (e.g., payment setup), error behavior, or potential side effects, leaving gaps for a paid generation tool.
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 three short, focused sentences: what it does, what it costs, and what it returns. Every sentence provides essential information with no redundancy or filler.
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 tool with 9 parameters, no output schema, and no annotations, the description is too sparse. It covers the core purpose and output but lacks details on parameter usage, unit constraints, error handling, and payment prerequisites, which are critical for an AI agent to invoke it correctly.
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 only 11% (only 'prompt' has a description), so the description must compensate for the other 8 parameters. It does not explain widthMm, heightMm, modelMode, includeBase, etc., and the mention of 'stamp' contradicts the enum which only includes 'cookie-cutter' and 'jewelry'. This is misleading and lacks necessary parameter context.
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 tool generates a 3D-printable STL from a text prompt, naming specific output categories (cookie cutter, stamp, jewelry). This specific verb+resource combination distinguishes it from the unrelated sibling tools (about, web_search, web_search_read).
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 clear context: use when you need a 3D-printable STL generated from a text prompt, and it mentions cost and output format. It doesn't explicitly state exclusions or alternatives, but the sibling tools are clearly unrelated, so the usage context is sufficient.
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.
The tools are mostly distinct, but web_search and web_search_read overlap significantly as one returns snippets and the other full text. 'about' is informational and unrelated to the core STL generation.
The naming pattern is mixed: 'about' is an outlier with a single word, while the others follow a verb_noun or noun_verb pattern. 'generate_stl', 'web_search', and 'web_search_read' are consistent among themselves.
Four tools is a reasonable number, but the server mixes two disparate functionalities (STL generation and web search) with no management tools. The count feels slightly thin for the implied scope.
The core domain of generating STL from text only has one tool, lacking any CRUD operations or management capabilities. The web search tools are unrelated and do not fill the gaps.