Contrôle qualité visuel de vidéo par IA

---
name: ai-video-visual-qa
description: "Inspect an AI-generated video for visible continuity, composition, motion, text, and artifact failures."
---

# AI Video Visual QA

Inspect an AI-generated video for visible continuity, composition, motion, text, and artifact failures.

## Required Aident Actions

- <action-tag>direct:fal:fal_list_media_analysis_models</action-tag> (required inputs: inspect the current schema): List active Fal image and video understanding models with current platform-key pricing, descriptions, required inputs, defaults, choices, documentation links, and pagination cursors. Use this before fal_analyze_media...
- <action-tag>direct:fal:fal_analyze_media</action-tag> (required inputs: inspect the current schema): Run an active Fal image and video understanding model. Defaults to fal-ai/florence-2-large/more-detailed-caption. Call fal_list_media_analysis_models before selecting another model to inspect current pricing,...

Use Aident Loadout to read the current Action schema before constructing inputs. Check the required integration connection in Aident Vault. If an Action is billable or mutating, run Aident preflight, show the affected target and quoted cost or risk, and wait for explicit user confirmation before execution.

## Workflow

1. Confirm the requested outcome, source material, destination, audience, constraints, and acceptance criteria.
2. Apply the source-derived guidance below to create a concrete plan. Resolve ambiguity before invoking an Action.
3. Select only the Aident Actions whose documented effect directly advances the requested outcome. Do not invoke every listed Action by default.
4. Inspect the current schema and prepare the minimum valid input for each selected Action.
5. Preflight each selected Action. Execute it only after any required confirmation, in dependency order, and carry returned IDs or asset URLs into later steps.
6. Verify the returned IDs, URLs, statuses, or artifacts against the acceptance criteria. Report partial completion precisely and do not repeat paid or mutating calls blindly.

## Source-Derived Guidance

- Collect the video asset, generation brief, intended platform, aspect ratio, and visual acceptance criteria.
- Use direct:fal:fal_list_media_analysis_models to select a current model that explicitly supports video input.
- Use direct:fal:fal_analyze_media with a rubric covering subject identity, temporal continuity, motion, framing, lighting, visible text, and generation artifacts.
- Cite timestamps or frames for each observed failure and separate evidence from aesthetic judgment.
- Return a pass-or-revise decision and targeted visual correction prompts; do not claim audio, codec, rights, or platform-policy validation.

## Execution Boundaries

- Treat upstream provider-specific commands as background knowledge only. Execute the workflow through the exact Aident Actions above.
- Never request raw credentials in chat. Use Aident Vault connection flows for required accounts.
- Preserve user-provided wording, brand constraints, rights restrictions, and target identifiers. Do not invent authorization.
- Pass assets by Aident asset ID or supported URL fields. Do not expose caller-local filesystem paths to hosted Actions.
- Stop when a required integration is disconnected, preflight rejects the input, the target is ambiguous, or the user declines a required confirmation.

## Output

Return the execution plan, selected Action names, confirmed targets, Aident result identifiers or asset URLs, verification evidence, and any remaining blocked step.

## Attribution

This Skill adapts the reviewed upstream workflow. See [UPSTREAM.md](UPSTREAM.md) for the pinned source and [LICENSE.txt](LICENSE.txt) for the preserved license.