axis_compareCompare two avatar contracts. Returns similarity score and section-level diffs. [Paid: $0.10 USDC via x402 for unauthenticated calls on the hosted /mcp endpoint; settled only on a successful (non-error) result.]
| Name | Required | Description | Default |
|---|---|---|---|
| file_a | Yes | Path to first mesh file | |
| file_b | Yes | Path to second mesh file | |
| sections | No | Limit comparison to specific contract sections |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare readOnlyHint=true and idempotentHint=true, covering the safety profile. The description adds valuable operational context: it discloses the paid nature ($0.10 USDC via x402) and the condition that payment is settled only on successful results. It also mentions the return format (similarity score and diffs), going beyond what annotations provide. No contradictions with annotations.
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 exactly two sentences: the first clearly states the core function, and the second provides essential payment information. No wasted words, and the critical purpose is front-loaded.
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 a well-covered schema and annotations. The description adds the return value ('similarity score and section-level diffs') and the payment caveat, which is important for an agent. No output schema exists, so describing the return structure is helpful. However, it doesn't explain what 'section-level diffs' entails, leaving some ambiguity for unfamiliar agents, but overall it is complete enough for selection and invocation.
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 100% description coverage for all three parameters (file_a, file_b, sections), so the schema already explains their meaning. The description does not add any additional parameter-specific details, such as format hints or examples, beyond what the schema provides. Baseline of 3 is appropriate.
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 states a specific verb ('Compare') and resource ('avatar contracts'), and distinguishes itself from sibling tools by mentioning the unique output ('similarity score and section-level diffs'). The title 'Compare Two Meshes' reinforces the purpose, making it unmistakable.
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 clearly implies the tool is for comparing two meshes/avatar contracts, which provides some context for when to use it. However, it does not explicitly mention alternatives or when-not scenarios, leaving usage guidance to inference. This is implied usage rather than explicit guidance.
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.
Each tool occupies a clearly distinct role: generation (image/text) plus status polling, pipeline processing (file vs inline), validation, repair, export, compliance, manifest verification, inspection, comparison, capabilities, and animation retargeting are all separated. The only potential overlap between axis_process and post_process_mesh is explicitly resolved by input method and scope.
Two naming styles coexist: axis_* prefix for core pipeline/contract tools and descriptive non-prefixed names for generation, repair, and compliance tools. Within axis_*, the verb/noun order is inconsistent (e.g., axis_manifest_verify vs axis_list_capabilities), making the set readable but not uniform.
14 tools is squarely within the ideal 3-15 range and matches the broad but well-defined scope of a full avatar foundry: generation, processing, validation, repair, export, compliance, and metadata inspection. Every tool serves a necessary function with no redundancy or bloat.
The toolset covers the full lifecycle from generation (image/text) and status polling through post-processing, repair, validation, export, and Roblox-specific compliance. Minor gaps exist, such as no tool to list available animation clips (retarget_animation references 'built-in' clips) or manage a library of previously generated avatars, but core workflows are fully supported.