spriteship

Generate a project creative brief

generate_project_vision

PAID but very cheap (one Gemini call) and SYNCHRONOUS — the result comes back in this response, there is no jobId to poll. Turns a rough game idea into { aiVision, aiPromptGuidance, aiNegativeGuidance }: a written creative direction plus the positive/negative guidance to reuse in later prompts, which is what keeps a whole project visually consistent instead of every asset drifting. Stores NOTHING — feed the wording into create_project (description/style) and into your own prompts. DEFAULTS TO A COST PREVIEW — see the dryRun argument.

Input Schema

TableJSON Schema

Name	Required	Description
`name`	Yes	Working title of the game.
`style`	No	Art style, if the user already has one in mind.
`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.
`gameType`	Yes	The view the game is played in — the brief is written for it.
`references`	No	Up to 6 tagged reference images the model can look at.
`description`	No	The idea in the user's own words: setting, mood, mechanics.
`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.

TDQS

A4.7/5.0

Behavior5/5

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

The description discloses numerous behavioral traits beyond the annotations: it is 'PAID but very cheap (one Gemini call)', 'SYNCHRONOUS', 'Stores NOTHING', and defaults to a cost preview. These are safety and cost implications not captured by readOnlyHint (false), openWorldHint (true), idempotentHint (false), or destructiveHint (false). The description significantly reduces the risk of an agent invoking it without understanding the paid, non-idempotent nature. No contradictions with annotations.

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 four sentences, each providing essential information: cost and synchronous behavior, output structure, storage side-effect, and dryRun default. It is front-loaded with the most critical differentiator (PAID) and avoids redundancy. Every sentence earns its place, and the structure makes the tool's unique aspects immediately visible.

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's complexity (7 parameters, no output schema, paid execution), the description is remarkably complete. It covers the cost model, synchronous response, lack of jobId, output fields, side effects (stores nothing), default dryRun behavior, and how to chain the output into create_project. The schema covers parameters thoroughly, and the description covers behavioral context, making it sufficient for an agent to select and invoke the tool 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?

Schema description coverage is 100%, so the baseline is 3. The tool description adds minimal parameter-specific meaning beyond the schema; it only briefly references the dryRun argument ('DEFAULTS TO A COST PREVIEW'), but the schema already provides a thorough explanation. The description clarifies how the output (not parameters) should be reused, which is useful but not directly about parameter semantics.

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: 'Turns a rough game idea into { aiVision, aiPromptGuidance, aiNegativeGuidance }' — a specific verb and resource. It differentiates from siblings like create_project by emphasizing it produces reusable prompt guidance, and from async tools by noting it is synchronous with no jobId. The title 'Generate a project creative brief' aligns with the description.

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 usage guidance: it tells the agent to 'feed the wording into create_project (description/style) and into your own prompts', directing when to use this tool as a precursor to project creation. It also instructs on the dryRun workflow: 'DEFAULTS TO A COST PREVIEW — see the dryRun argument', and clarifies that results come back synchronously, distinguishing it from sibling tools that require job polling.

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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