validate_sceneValidate a scene against the Keyframer format before create_scene or generate_code. Returns errors (must fix) and warnings (advisory). Free to call — iterate until clean.
| Name | Required | Description | Default |
|---|---|---|---|
| scene | Yes | The scene as a JSON object (preferred) or a JSON string. Call get_scene_format for the shape. |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare readOnlyHint=true, so the description doesn't need to restate that. It adds value by specifying the return type ('errors (must fix) and warnings (advisory)') and the cost-free nature, going beyond annotations without contradicting them.
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?
Three short sentences with zero fluff. The action is front-loaded, the purpose is immediately clear, and the iteration hint is a valuable additive detail. Every sentence earns its place.
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 simple one-parameter, read-only validator, the description covers purpose, usage timing, return types, and how to proceed. It even references a sibling tool for shape details. Nothing an agent needs to call it correctly is missing.
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 coverage is 100% and the parameter description is rich, offering type alternatives and pointing to get_scene_format for shape. The tool description itself doesn't add parameter details, but the schema already provides excellent guidance, so this exceeds the baseline for high coverage.
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 clear verb ('Validate'), a specific resource ('a scene against the Keyframer format'), and explicitly ties it to subsequent actions ('before create_scene or generate_code'). It distinguishes itself from siblings by framing validation as a gate for those operations.
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?
Explicitly says when to use the tool ('before create_scene or generate_code') and even provides iteration guidance ('Free to call — iterate until clean'). This leaves no ambiguity about its role relative to sibling tools.
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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Each tool maps to a distinct resource or action: scene CRUD, validation, motion sampling, recipe lookup, code generation, and QR preview. Potential pairs like validate_scene vs sample_scene are clearly separated as structural validation vs motion evaluation, and get_scene vs get_recipe differ by source and purpose.
Tool names consistently follow a verb_noun snake_case pattern: create_scene, get_scene, list_scenes, update_scene, validate_scene, search_recipes. The few compound nouns like get_preview_qr and get_scene_format still fit the same predictable convention.
11 tools is well within the ideal range and each tool serves a clear part of the scene authoring workflow: discovery, validation, sampling, editing, compiling, and previewing. None feel redundant or extraneous for the stated purpose.
The toolset covers the core scene lifecycle well: create, read, list, update, validate, sample, generate code, and preview. The main gap is the absence of a delete_scene tool, which is a minor omission since the authoring and iteration workflow is otherwise fully supported.