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Submit video generation

generate_video
Destructive

Submit confirmed paid fal.ai video generation requests using exact model IDs and schema-validated inputs; no defaults, retries, or polling.

Instructions

Confirmed paid model request after current native input-schema validation. Exact model_id/input required; image/video commands do not invent fields or choose a default. Queue submissions return receipt only; synchronous timeout may leave an unknown paid outcome. No retry or polling.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
inputYesExact native model inputs. Fetched current model JSON schema validates these before a paid request; no guessed prompt/image/duration adapters.
accountNoExact configured isolated API-key profile label.
confirmNoExplicit approval for the requested paid work, mutation, upload or private file.
model_idYesExact current catalog endpoint ID. Never guess model names or parameter mappings.
store_ioNoLocal default false sends X-Fal-Store-IO:0. true allows provider JSON payload storage; CDN media retention/ACL is separate.
lifecycleNoNative CDN expiry/ACL preference. Omit to use account defaults. null expiration means no expiry; default CDN access may be public. Unknown nicknames may be dropped by provider.

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv2.0.0

TDQS

B3.3/5.0
Behavior4/5

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

Annotations already declare destructiveHint=true, idempotentHint=false, and openWorldHint=true, so the safety profile is covered. The description adds genuinely non-obvious behavior: this is a paid request, queue submissions return a receipt only, and a synchronous timeout may leave an unknown paid outcome with no retry. That is real value beyond the annotations.

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?

Dense but front-loaded: the paid/validated precondition and the required inputs come first, followed by the queue/timeout/no-retry consequences. No sentence is filler, though the jargon-heavy phrasing slightly hurts scannability.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness3/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

For a destructive, paid, 6-parameter tool with no output schema, the description covers the critical paid-outcome and no-retry behaviors. However it omits how to observe results after a queue receipt (e.g., get_job_status) and says nothing about the confirm/account gating, leaving a follow-up gap.

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 schema already documents all six parameters well, including the nested lifecycle/ACL objects. The description only reinforces model_id/input ('do not invent fields or choose a default') without adding format or value semantics, so baseline 3 applies.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose3/5

Does the description clearly state what the tool does and how it differs from similar tools?

The body opens with 'Confirmed paid model request' and only implies the video-generation purpose through the name/title and the passing phrase 'image/video commands.' It never cleanly states a verb+resource like 'generates a video,' and it does not distinguish itself from close siblings such as generate_image or run_model.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines3/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

It gives implicit operational guidance ('Exact model_id/input required,' 'No retry or polling') that constrains how the agent should behave, but there is no explicit when-to-use vs alternatives, and no routing to get_job_status/cancel_job for follow-up.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.