Caliper

Batch Analysis

format_batch

Read-onlyIdempotent

Analyze multiple geometry files in a single batch request.

Submit up to 10 files, receive a single quote, pay once, and get
structured metadata for all files. Supports mixed formats. Read-only
analysis — does not modify, convert, or repair files.

Payment is required via x402 (USDC on Base) or card via MPP (Stripe). If no payment is provided,
the response includes the total price and per-file breakdown. Retry
with the payment argument containing "transaction", "network", and
"priceToken".

Partial success: if some files fail processing, you still receive
results for the files that succeeded.
Privacy policy: https://caliper.fit/privacy

Input Schema

TableJSON Schema

Name	Required	Description	Default
`files`	Yes	JSON array of file descriptors. Each object has optional keys: "file_url" (HTTP/S URL), "file_b64" (base64 string), "filename" (for format detection). Provide either file_url or file_b64 per file. Max 10 files per batch.
`payment`	No	Payment 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).

TDQS

A4.7/5.0

Behavior5/5

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

The description discloses significant behavioral context beyond annotations: payment requirements (x402/MPP), the two-step flow (initial call returns price, retry with payment), partial success handling, and a privacy policy link. This greatly aids the agent in understanding side effects and expected behavior.

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 well-structured and efficient. It opens with a clear purpose, then covers payment, partial success, and privacy in a logical order. Every sentence adds value with no redundancy.

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

Completeness5/5

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

With no output schema, the description explains what to expect: a single quote, structured metadata for all files, and if no payment, a price breakdown. It also addresses partial success and payment flow, making it complete for this tool.

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

Parameters4/5

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

Schema coverage is 100%, so both parameters are already documented. The description adds useful context on the payment retry flow ('If no payment is provided, the response includes the total price and per-file breakdown. Retry with the payment argument...') and reiterates the 10-file limit, which enhances understanding beyond the schema.

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 'Analyze multiple geometry files in a single batch request' with a specific verb ('Analyze') and resource ('geometry files'), and the batch scope distinguishes it from siblings like format_detect or format_stl.

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 clear context for when to use the tool: batch analysis of multiple files with mixed formats, and explicitly states what it does not do ('does not modify, convert, or repair files'). It does not name alternative tools, but the exclusions and batch context are sufficient.

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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