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build_asset_from_spec

Builds a sprite from a specification by creating scaffolding, applying palette, layers, animations, and running exports without drawing pixels.

Instructions

Build the asset described by an aseprite_mcp.asset_spec.v1 document.

Executes the (validated) plan by dispatching each step to an existing tool: scaffolds
the sprite for its `kind`, applies palette / extra layers / animation frames+tags /
slices, and runs the requested exports. **Structure only — no pixels are drawn;** the
returned manifest's `suggested_next_actions` hand the actual art back to you.

Args:
    overwrite: Passed to the export steps (replace existing export files). The sprite
        itself is created no-clobber, so building over an existing ``<name>.aseprite``
        raises — build to a new name or remove the old file.

Returns a ``workflow_manifest.v1`` (kind ``asset_spec``) with the created files, the
executed `plan`, and next actions. Raises ``ValidationFailed`` if the spec is invalid.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
specYes
overwriteNo
Behavior4/5

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

With no annotations, the description discloses key traits: no pixels drawn, no-clobber sprite creation, overwrite passed to exports, raises ValidationFailed if spec invalid, and returns a workflow manifest. It does not cover auth or rate limits, but those are less critical for a build tool.

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 somewhat lengthy but well-structured, starting with a summary then details about args and return. It uses a list for args and return, making it scannable. Could be slightly more concise, but overall good.

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?

The tool has two parameters, no output schema, and nested objects. The description covers behavior, return type, and error conditions. It references a document type for spec, which is reasonable. It might benefit from mentioning the need for prior validation, but it's implied.

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?

The description explains overwrite clearly, including its effect and the no-clobber behavior for the sprite. For the 'spec' parameter, it only mentions the document type and that it's a validated plan, lacking detailed structure. With 0% schema coverage, more detail on spec would be helpful.

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 it builds an asset from an aseprite_mcp.asset_spec.v1 document, and distinguishes from sibling tools like validate_asset_spec and plan_asset_spec by referring to executing a validated plan. It also notes that no pixels are drawn, differentiating from drawing tools.

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 explains that the tool executes a validated plan and mentions overwrite behavior and no-clobber on sprite creation. It implicitly tells when to use (after validation and planning) but does not explicitly state alternatives or exclude wrong usage scenarios.

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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