spriteship

Get animation frames

get_frames

Read-onlyIdempotent

Presigned per-frame thumbnails for a character animation or an asset motion pair — never inline base64. Use format:"sheet" to get ONE index-labeled contact sheet, which lets you judge a whole capture in a single look; that is the intended way to pick which frames to keep before calling select_frames.

Input Schema

TableJSON Schema

Name	Required	Description
`size`	No	Max thumbnail edge (default 256, cap 1024). "full" opts out of downscaling.
`format`	No	"sheet" returns one labeled contact sheet.
`pairId`	No	Motion pair id — required when target=assetPair.
`target`	Yes	Frames of a character animation, or of an asset motion pair.
`indices`	No	Comma-separated frame indices to subset, e.g. "0,4,8".
`entityId`	Yes	Character id (target=character) or asset id/slug (target=assetPair).
`animation`	No	Animation slug — required when target=character.

TDQS

A4.4/5.0

Behavior4/5

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

Annotations already declare readOnly/openWorld/idempotent, so the description doesn't need to rehash safety. It adds valuable behavioral detail: output is presigned (URLs) and never inline base64, and the sheet is index-labeled. This goes beyond the structured annotations and helps set expectations about the response format.

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?

Two sentences, front-loaded with the core output type, and each clause earns its place. The contrast between inline base64 and presigned URLs is a critical constraint stated in a single phrase, and the sheet usage guidance is concise but complete.

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?

Despite 7 parameters and no output schema, the description covers the key behavioral aspects: output format, presigned URLs, sheet semantics, and integration with select_frames. The schema handles parameter details, so the description doesn't need to enumerate every field. It lacks some detail on how indices and size interact, but this is adequately covered by the schema. Overall, sufficiently complete for the tool's complexity.

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 description coverage is 100%, so the schema already documents all parameters thoroughly. The description adds meaningful context around the format parameter (explaining the sheet's purpose) and the output nature (presigned), but doesn't materially enhance the understanding of other parameters beyond what the schema provides. Baseline 3 is appropriate.

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: returning presigned per-frame thumbnails for character animations or asset motion pairs. It distinguishes itself from sibling tools by explicitly referencing select_frames as the intended downstream action, making its role in the workflow unambiguous.

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

Usage Guidelines5/5

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

Provides explicit usage guidance: warns against inline base64, recommends format:"sheet" for judging whole captures, and names select_frames as the next step. This clarifies when to use this tool and how to choose between thumbnails and contact sheet, effectively covering both when and how.

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

A3.9/5.0

Disambiguation4/5

Most tools have clearly distinct purposes, and the descriptions are extremely detailed with cross-references (e.g., animate_asset vs frame_animation vs generate_character_animation). A few pairs like reprocess_asset vs revise_asset could be confused initially, but their descriptions and use cases are explicit enough to prevent misselection.

Naming Consistency5/5

All tool names follow a consistent verb_noun pattern in snake_case (e.g., create_project, get_asset, cancel_job). Verbs are imperative and nouns are appropriately singular/plural, making the API predictable and readable.

Tool Count2/5

At 41 tools, the server is far beyond the 15-25 range considered reasonable for most APIs. While the domain is broad (project, assets, characters, animations, jobs, exports, credits), the sheer number creates a heavy surface that may overwhelm agents and suggests the API could be consolidated into higher-level operations.

Completeness4/5

The tool set covers the full creative pipeline: project creation, asset/character generation, animation (both AI and frame-based), revisions, exports, and job management. Minor gaps include lack of delete operations for assets/characters/projects and no listing of all jobs, but these are not critical for the core workflow and are likely intentional for a generative art platform.

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