Cannon Studio

Create Cannon Studio Generation Request

create_generation_request

Destructive

Create billable async Cannon Studio generation work only after explicit user approval. Requires OAuth or a developer API key; can spend credits up to max_credits and cannot be cancelled through MCP after submission. Use estimate_generation_cost first, then set confirmed=true and a user-approved max_credits cap. This tool does not create API keys, charge payment methods directly, or delete assets.

Input Schema

TableJSON Schema

Name	Required	Description
`input`	Yes	Operation-specific request payload. Use the exact shape documented by get_api_operation for the selected operation; this is the billable payload that will be submitted if confirmed and within max_credits.
`confirmed`	No	Must be true only after the user explicitly approves this billable generation request, including operation, payload, and max_credits. Missing or false returns a confirmation error and creates no job.
`operation`	Yes	Cannon Studio developer API operation id to run. Use get_api_operation first if unsure. Examples: image.generate, video.generate, three_d.model.generate, three_d.location.generate, music.generate, narration.generate, subtitles.generate.
`max_credits`	No	Highest credit spend the user explicitly approved for this request. The tool rejects the request when the current estimate is greater than this cap.
`webhook_url`	No	Optional HTTPS URL that Cannon Studio calls when the request reaches a terminal succeeded or failed state. Omit when polling with get_generation_request.
`idempotency_key`	No	Optional stable retry key for the same operation and payload. Reuse it when retrying after a network/client error; do not generate a new key for the same intended request.

Output Schema

TableJSON Schema

Name	Required	Description	Default
`ok`	No
`error`	No
`status`	No
`response`	No
`maxCredits`	No
`estimatedCredits`	No

TDQS

A4.7/5.0

Behavior5/5

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

Despite annotations indicating destructive/non-idempotent behavior, the description adds valuable context: it can spend credits up to max_credits, is irreversible after submission, and requires explicit user approval. It clarifies what it does not do, mitigating the destructiveHint's broad implication. No contradiction 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 three efficient sentences: purpose, requirements/risks, and workflow/exclusions. Every sentence adds value, and the most important information (explicit approval, billable, cancellation) is front-loaded.

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?

For a complex tool with 6 parameters, nested input objects, and an output schema, the description covers the critical operational context: approval workflow, credit limits, authentication, non-cancellation, and what it does not do. Combined with the rich schema and annotations, it is complete.

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 description reinforces the meaning of 'confirmed' and 'max_credits' but does not add new parameter-level detail beyond what the schema already provides.

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 opens with 'Create billable async Cannon Studio generation work only after explicit user approval,' which uses a specific verb (Create), resource (Cannon Studio generation request), and a clear condition. This distinguishes it from sibling tools like estimate_generation_cost or get_generation_request.

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?

Explicit workflow guidance is provided: 'Use estimate_generation_cost first, then set confirmed=true and a user-approved max_credits cap.' It also states prerequisites (OAuth or developer API key), exclusions (does not create API keys, charge payments, or delete assets), and a critical caveat that requests cannot be cancelled through MCP after submission.

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

A4.1/5.0

Disambiguation5/5

Each tool targets a distinct resource or action: status, comparison, creation, estimation, fetching, API docs, checkout, generation polling, model availability, pricing, capabilities, offerings, toolkits, workflow recommendation, and knowledge search. Even the get_* and list_* tools have clear, non-overlapping purposes.

Naming Consistency3/5

Most tools follow a verb_noun pattern (create_generation_request, list_offerings, get_checkout_link), but there are exceptions: api_status is a noun, and fetch and search are single verbs without an object. The mix of get/list/compare/recommend/search/fetch is readable but not perfectly uniform.

Tool Count5/5

15 tools is at the upper bound of the well-scoped range, but each tool serves a clear, distinct purpose in the Cannon Studio domain—from estimation and creation to knowledge retrieval and workflow recommendation. No tool feels redundant or superfluous.

Completeness3/5

The surface covers creation, estimation, polling, knowledge, and commercial operations, but the generation lifecycle is incomplete: there is no update, cancel, or list tool for generation requests, and the create tool explicitly cannot be cancelled through MCP. This is a notable gap for agents managing ongoing work.

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