spriteship

Regenerate one asset motion pair

regen_asset_pair

PAID (~400 credits at defaults). Re-run video generation for a SINGLE motion pair of an animated asset, leaving its other pairs alone. The new take lands as an additional iteration on that pair — earlier takes are preserved. DEFAULTS TO A COST PREVIEW — see the dryRun argument. Returns { jobId } — poll get_job.

Input Schema

TableJSON Schema

Name	Required	Description
`dryRun`	No	DEFAULTS 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.
`pairId`	Yes	Motion pair id (from get_asset).
`assetId`	Yes	Asset id or slug.
`videoModel`	No	Override the video model.
`motionPrompt`	No	Replacement motion prompt for this take.
`idempotencyKey`	No	Optional 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.
`durationSeconds`	No	Informs the cost estimate only — the dispatched job uses the pair's own duration.

TDQS

A4.5/5.0

Behavior5/5

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

The description discloses important behavioral traits beyond annotations: the cost (~400 credits), the default to a cost preview via dryRun, that earlier takes are preserved (non-destructive), and that it returns a jobId to poll. This adds significant context beyond the readOnlyHint/idempotentHint/destructiveHint annotations and aligns with them (no contradiction).

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 three sentences, starts with the critical cost warning, and packs in scope, preservation, default behavior, and return type without redundancy. Every sentence earns its place.

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 no output schema and seven parameters, the description covers the essential context: what it does, its non-destructive nature, cost, dryRun flow, and return value. Param details are in the schema, so the description is complete enough for an agent to select and invoke it correctly.

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?

Input schema coverage is 100%, so each parameter is described. The description reinforces the dryRun default and idempotencyKey behavior but does not add substantial meaning beyond the schema's own parameter descriptions. Baseline 3 is appropriate because the schema already carries the burden.

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 re-runs video generation for a single motion pair of an animated asset, explicitly distinguishing it from regenerating all pairs. The verb 'Re-run' plus the resource 'motion pair' and the scope 'leaving its other pairs alone' make the purpose unambiguous and differentiate it from sibling tools like revise_asset or reprocess_asset.

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 conveys when to use this tool by focusing on a single pair and preserving other pairs, but it does not explicitly name alternative tools or provide exclusion criteria. It does give clear context, including the cost preview default and that earlier takes are preserved, which implies when this is appropriate.

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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