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STL Analysis

format_stl
Read-onlyIdempotent

Extract metadata from an STL file (ASCII or binary).

Returns triangle count, bounding box, surface area, volume,
manifold analysis (watertight, open edges, non-manifold edges),
triangle quality metrics, vertex deduplication count, mean edge
length, minimum bounding sphere, and a noise estimate derived
from planar region fitting.

Payment via x402 (USDC on Base) or card via MPP (Stripe). See format_auto
for payment flow details. Privacy policy: https://caliper.fit/privacy

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
paymentNoPayment proof as a JSON string. Set this when retrying after a payment_required response. For x402: must contain 'transaction' (on-chain tx hash), 'network', and 'priceToken' from the payment_required response. For MPP: must contain 'challenge' and 'payload' from the org.paymentauth/credential flow. Default: null (omit on first call; set only when retrying with payment).
file_b64NoBase64-encoded file content. Max 200KB decoded. Use file_url for larger files to avoid consuming model context window budget. Default: null (omit if providing file_url instead).
file_urlNoHTTP/HTTPS URL of the geometry file to analyze. Preferred for large files (over 200KB). The file format is detected from the URL path extension, so the filename parameter is not needed when using file_url. Max 100MB. Default: null (omit if providing file_b64 instead).
filenameNoOriginal filename with extension (e.g. 'model.stl'). Required for format detection when using file_b64. Not needed when using file_url (format is detected from the URL path). Default: null.

TDQS

A4/5.0
Behavior4/5

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

The annotations (readOnlyHint, openWorldHint, idempotentHint) already establish the tool's safety profile. The description adds meaningful behavioral context by enumerating the exact computed metrics (triangle count, manifold analysis, noise estimate, etc.) and disclosing payment requirements (x402/card). It does not contradict annotations and provides additional transparency about the analysis performed.

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

Conciseness5/5

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

The description is appropriately concise: a single sentence defining purpose and a list of outputs, followed by a sentence about payment and privacy. Every sentence adds value, no filler. The structure front-loads the core purpose and then details outputs and practical instructions.

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

Completeness4/5

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

Given there is no output schema, the description carries the burden of explaining what the tool returns, and it does so comprehensively with a detailed list of metrics. It also covers payment methods, privacy policy, and a pointer to format_auto for payment flow details. It is slightly incomplete regarding when to use this tool versus format_auto or format_detect, but for a read-only analysis tool, the essential context is covered.

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

Parameters3/5

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

Schema coverage is 100% – all four parameters have detailed descriptions in the input schema. The description does not add significant new parameter semantics beyond pointing to format_auto for payment flow, which relates to the payment parameter. Since the schema already explains each parameter, the description's contribution here is marginal, matching the baseline of 3.

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 tool's function: 'Extract metadata from an STL file (ASCII or binary).' It names the specific file format (STL) and the action (extract metadata), which distinguishes it from sibling format_* tools like format_obj or format_ply. The listed output metrics further clarify its purpose.

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

Usage Guidelines3/5

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

Usage context is implied by the tool name and description (use for STL files), but there is no explicit guidance on when to choose this over format_auto or format_detect. The only alternative mentioned is 'See format_auto for payment flow details,' which addresses payment flow, not tool selection. No exclusions or when-not-to-use instructions are provided.

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

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TDQS

A4.4/5.0
Disambiguation5/5

Every tool has a clearly distinct purpose with no ambiguity. The general-purpose format_auto and format_batch tools cover multiple formats, while the format-specific tools (format_gltf, format_las, etc.) target individual formats, and feature_request serves a completely different administrative function. The descriptions clearly differentiate between auto-detection, batch processing, format detection, and format-specific analysis.

Naming Consistency5/5

All tools follow a consistent snake_case naming pattern with clear verb_noun structure. The format_ prefix is used consistently for 9 out of 10 tools (format_auto, format_batch, format_detect, format_gltf, etc.), while feature_request follows the same naming convention for the remaining tool. There are no deviations in naming style or convention.

Tool Count5/5

With 10 tools, this is well-scoped for a geometry file analysis server. Each tool earns its place by covering different aspects of the domain: general analysis (format_auto), batch processing (format_batch), format detection (format_detect), format-specific analysis (7 tools for different formats), and feature requests (feature_request). The count is neither too sparse nor overwhelming for the domain.

Completeness4/5

The tool surface provides excellent coverage for geometry file metadata extraction across multiple formats, with both general and format-specific tools. The inclusion of batch processing and format detection adds useful workflow support. The only minor gap is the lack of tools for actual mesh manipulation, repair, or conversion operations, but the server's stated purpose appears focused on analysis rather than modification, and feature_request allows users to request missing capabilities.

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