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spriteship

by com.spriteship

Animate an asset

animate_asset

PAID (image-to-video, cost scales with duration × pair count). Animate ANY asset type — the animation lands on the source asset and its still image is preserved. For grid assets (tileset/staged) pass pairs of tile indices; a self-loop { from: n, to: n } makes one tile loop seamlessly. ASK THE USER WHICH STAGES FIRST. Call get_asset, describe the tiles you can see, and get an explicit answer on which is the START and which is the END before you spend. "Animate the treasure box" does not tell you whether they mean closed→open, open→closed, or the lid alone, and guessing wrong bills them for a clip they cannot use. The server rejects a grid animate with no pairs (400) precisely so that this choice is always made deliberately — do not satisfy it by defaulting to 0→last. DEFAULTS TO A COST PREVIEW — see the dryRun argument. Returns { jobId } — poll get_job.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
pairsNoGrid assets only — which tile transitions to animate. Omit for single-image assets.
dryRunNoDEFAULTS TO TRUE. While true this returns only a cost quote ({ estimatedCredits, balance, spendCapDaily, spentLast24h, capRemaining }) and executes nothing. Show the user estimatedCredits and get an explicit yes for that amount, THEN re-call with dryRun:false to actually spend.
assetIdYesAsset id or slug.
closeLoopNoSingle-image assets — reuse the start frame as the end frame so the clip loops.
motionHintNoExtra motion guidance folded into the prompt.
videoModelNoOverride the video model.
iterationIdYesRevision (iteration) id to animate.
idempotencyKeyNoOptional Idempotency-Key for the real (dryRun:false) call. Omit and one is minted per call. Reuse the SAME value when retrying a call that failed with ENTITY_BUSY / 402 / 429 so the retry cannot double-dispatch.
durationSecondsNoClip length, clamped server-side to 2-10s.

TDQS

A4.8/5.0
Behavior5/5

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

The description discloses critical behavioral traits beyond annotations: it defaults to a cost preview (dryRun=true), returns only estimatedCredits and billing info, requires explicit user confirmation before spending, and mentions server rejection with 400 for missing pairs. It also explains the self-loop behavior for seamless tiles. Annotations only say openWorldHint=true and readOnlyHint=false, but the description adds substantial context about billing, dry-run flow, and error handling.

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

Conciseness4/5

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

The description is dense but front-loaded: it starts with PAID (image-to-video) to set expectations immediately. It packs a lot of actionable guidance into a few sentences, and every sentence serves a purpose (cost, animation behavior, grid-specific instructions, user confirmation requirement, error handling, dry-run default, return type). It's slightly long but justifiably so.

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?

Given the tool has 9 parameters, no output schema, and only basic annotations, the description is remarkably complete: it explains the cost model, dry-run flow, grid vs single-image behavior, user confirmation necessity, error handling for missing pairs, and what the response contains ({ jobId }). It even provides specific examples of ambiguous requests like 'Animate the treasure box' to illustrate the need for clarification. This covers all key operational aspects.

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 the baseline is 3. The description adds meaningful semantics by explaining the dryRun argument's purpose (cost preview, show user estimatedCredits, then re-call with false), and the pairs argument's meaning for grid assets. It also clarifies the idempotencyKey usage for retries. However, some parameter details like videoModel and motionHint are not elaborated in the description 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 what the tool does: 'Animate ANY asset type' with image-to-video, landing on the source asset, and preserving the still image. It distinguishes this from siblings like frame_animation, create_animation_from_pose, and revise_asset by emphasizing that it works on any asset type and is paid.

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?

The description provides explicit when-to-use guidance: it tells the agent to ask the user which stages first, call get_asset to see tiles, and get explicit start/end before spending. It also gives exclusion guidance: 'do not satisfy it by defaulting to 0→last' and explains the 400 error for grid animate with no pairs. This is strong usage guidance with clear alternatives and prerequisites.

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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