media-post

Generate covers, vertical recomposes, SEO packs, and chapter cards from edited videos.

2.0k|274|Updated Jan 30, 2026
One-click install
npx skills add https://github.com/openakita/openakita --skill media-post
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: media-post
Source: https://github.com/openakita/openakita/tree/main/plugins/media-post
Command: npx skills add https://github.com/openakita/openakita --skill media-post

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill requires httpx, aiosqlite, pydantic, fastapi, playwright.

What problem does it solve?

Turning a finished video into platform-ready publishing material requires manual cover selection, aspect-ratio re-editing, copywriting for each social platform, and chapter card design. This Skill automates that entire post-edit packaging workflow through four modes backed by Qwen-VL-max vision scoring and ffmpeg.

Core Features & Use Cases

  • Smart Cover Pick: ffmpeg thumbnail prefiltering plus 6-axis VLM aesthetic scoring selects the top-N cover frames with bounding-box annotations.
  • Multi-Aspect Recompose: Converts 16:9 footage to 9:16 or 1:1 using scene-cut detection, VLM subject tracking, and EMA-smoothed dynamic cropping.
  • 5-Platform SEO Pack: Generates titles, descriptions, and hashtags for TikTok, Bilibili, WeChat, Xiaohongshu, and YouTube in parallel.
  • Chapter Cards: Renders chapter PNGs from HTML templates via Playwright, with an ffmpeg drawtext fallback.
  • Use Case: After editing a 10-minute vlog, run cover_pick for 8 scored thumbnails, multi_aspect for a vertical Shorts version, and seo_pack for per-platform copy — all with upfront cost estimates in CNY.

Quick Start

Ask the assistant to use media_post_create with mode cover_pick on your edited video file to get scored cover candidates.

Frequently Asked Questions about media-post

High-intent search queries and answers about installing and using this skill.

FAQPage Schema
How do I pick the best video cover frame automatically?▼

Use the cover_pick mode, which prefilters about 30 candidate frames with the ffmpeg thumbnail filter, then scores each on six aesthetic axes via Qwen-VL-max. The top-N frames above your min_score_threshold are copied to the task output folder.

How to convert 16:9 video to 9:16 for TikTok or Shorts?▼

The multi_aspect mode detects scene cuts with ffmpeg, tracks the main subject using Qwen-VL-max bounding boxes, smooths the crop trajectory with EMA, and renders a dynamic crop. It currently outputs 9:16 and 1:1 only.

Does media-post work without a DashScope API key?▼

Only the chapter_cards mode works without an API key since it renders locally. cover_pick, multi_aspect, and seo_pack all require a DashScope key configured in the plugin Settings tab.

What happens if Playwright is not installed for chapter cards?▼

The renderer transparently falls back to ffmpeg drawtext, so cards still generate without Playwright or CJK fonts. The output is visually blockier but valid, and the render_path field records which path was used.

How much does a multi_aspect recompose cost?▼

A 30-second clip at fps=2 costs about 0.32 CNY, while a 30-minute clip costs roughly 35 CNY. Estimates above the warn threshold of 10 CNY require explicit cost_approved=true before the task runs.

What are the limitations of the multi_aspect mode?▼

It only emits 9:16 and 1:1 ratios, recommends source videos of 30 minutes or less, and caps ffmpeg crop expression nesting at 95 levels with automatic downsampling for long segments. Ratios like 3:4 and 21:9 are deferred to a later version.