Turns customer feedback into structured output
The source asks the model to group, classify, answer, or prioritize review feedback rather than treating every comment as an isolated case.
AI Video Generation is an ecommerce AI skill for 101 Skills, built for teams working with Codex, Claude Code. Use it to produce product, campaign, or ad assets. Do…
You need a repeatable way to produce product, campaign, or ad assets. Do not change every step at once: test Generate a 5-second product hero clip for a landing page alongside Produce short ad creatives for Meta/TikTok campaigns, then consider reducing blank-page work and… Start with a small test around “Generate a 5-second product hero clip for a landing page”, then check whether “Produce short ad creatives for Meta/TikTok campaigns” fits the way your team actually works.
The source asks the model to group, classify, answer, or prioritize review feedback rather than treating every comment as an isolated case.
The complete source is shown below. Copy it from the top right to use it.
You are an AI video generation operator working through the inference.sh belt CLI. Prerequisites: belt CLI installed and `belt login` completed. To generate video: 1) Clarify the goal (product clip, ad creative, social cut), aspect ratio, and duration; 2) Pick a model (e.g. google/veo-3-1-fast for speed, higher-quality models for hero shots); 3) Draft a cinematic prompt describing subject, motion, camera movement, lighting, and style; 4) Run `belt app run <model> --input '{"prompt": "..."}'`; 5) Review output, iterate on motion and camera language rather than re-rolling blindly. Keep prompts concrete: one subject, one camera move, one mood.Starter prompts for the main use cases—copy and use them directly.
Do not begin with a store-wide rollout. Pick one reversible task where AI Video Generation can help you create, localize, or check product content and visual assets. Use this when the input boundary, owner, and one primary measure from factual corrections, editing time, approval rate, and conversion quality are written down.
Use the Skill above to help me with this task: Start with one real task.
Task details: [TASK_DETAILS]
Constraints or policies to follow: [CONSTRAINTS]
Do not begin with a store-wide rollout. Pick one reversible task where AI Video Generation can help you create, localize, or check product content and visual assets.
Return a practical result and clearly flag anything that needs human review.[TASK_DETAILS][CONSTRAINTS]Collect only the verified product facts, source images, brand rules, target channel, and prohibited claims needed for this test. Remove unrelated personal data and state which actions must never run automatically. Use this when every input has a known source, sensitive fields are minimized, and the approver knows what the trial can read or change.
Use the Skill above to help me with this task: Prepare the input and guardrails.
Task details: [TASK_DETAILS]
Constraints or policies to follow: [CONSTRAINTS]
Collect only the verified product facts, source images, brand rules, target channel, and prohibited claims needed for this test. Remove unrelated personal data and state which actions must never run automatically.
Return a practical result and clearly flag anything that needs human review.[TASK_DETAILS][CONSTRAINTS]Read the source, installation method, and permission notes before adding AI Video Generation to a separate test project. Keep commands and Skill text exactly as published. Use this when you have a product-content draft that a responsible operator can inspect, and it stayed inside the approved boundary.
Use the Skill above to help me with this task: Inspect the source Skill, then run it.
Task details: [TASK_DETAILS]
Constraints or policies to follow: [CONSTRAINTS]
Read the source, installation method, and permission notes before adding AI Video Generation to a separate test project. Keep commands and Skill text exactly as published.
Return a practical result and clearly flag anything that needs human review.[TASK_DETAILS][CONSTRAINTS]Do not judge the result by fluency. Compare it with source data, the current SOP, and the pre-test baseline; record factual errors, omissions, and editing time. Use this when factual corrections, editing time, approval rate, and conversion quality has a pre-test baseline, and errors and exceptions are logged separately.
Use the Skill above to help me with this task: Review it against a baseline.
Task details: [TASK_DETAILS]
Constraints or policies to follow: [CONSTRAINTS]
Do not judge the result by fluency. Compare it with source data, the current SOP, and the pre-test baseline; record factual errors, omissions, and editing time.
Return a practical result and clearly flag anything that needs human review.[TASK_DETAILS][CONSTRAINTS]The instruction can group and prioritize feedback, but repeated wording is not proof of a product defect or customer-wide preference. Check the underlying sample before changing a product, policy, or campaign.
An open-source skills collection that packages repeatable AI workflows for creative, technical, and business tasks.
Review third-party permission scopes before providing store data. Never paste payment credentials, customer passwords, or unnecessary personal data into a model. Outputs must be checked by the operator responsible for the workflow.
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