Getting it into your agent
One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.
npx agentmods add skills/ai-answer/contentrepurposesystem/outlinesnpx skills add AI-Answer/ContentRepurposeSystem --skill outlinesgit clone --depth 1 https://github.com/AI-Answer/ContentRepurposeSystemWhat it costs to keep this loaded
Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5 | $0.00081 | $0.01837 |
| Opus 5 | $0.00041 | $0.00919 |
| Sonnet 5 | $0.00016 | $0.00367 |
| Haiku 4.5 | $0.00008 | $0.00184 |
Grade A, and why
outlines scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 2d ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
How it starts
The opening of the file, as written. The whole thing — 209 lines — stays where its author put it; the contents beside it link to each section on GitHub.
YouTube Video Outline Generator
Generate recording-ready video outlines in your exact format. Includes hooks, structured body sections with talking points, visual aid placeholders, source citations, time budgets, competitive differentiation, and production notes.
When This Skill Activates
Activate when the user wants to:
- Structure a video for recording
- Turn research or an idea brief into a filmable outline
- Create a full video plan with talking points
- Organize raw notes into a video format
Example triggers:
- "Outline this video about RAG concepts"
- "Turn this research into a video outline"
- "Write the outline for tomorrow's video"
/outlinesor/outlines <topic>
Input
The user provides one or more of:
- Topic or idea brief — from
/ideationor described verbally - Research notes — vault files, brain dumps, or pasted research
- Hook — from
/hooks(optional — will generate one if not provided) - Target length — how long the video should be (default: 12-18 minutes)
Always check the vault for related research: search research/ and projects/ for files on the topic.
Workflow
Step 1 — Determine Video Format
Classify the video structure based on the content:
Concept/Educational — explaining ideas with escalating depth
- Structure: Hook → Concept 1 → Concept 2 → ... → Big Picture Closer
- Example: "7 RAG Concepts Every Claude Code User Should Know"
- Per concept: core idea (one-liner) → explanation → analogy → source
Level-Based — progressive mastery/identity arc
- Structure: Hook → Level 1 → Level 2 → ... → Master Level
- Example: "6 Levels of Claude Code"
- Per level: what it is → the shift → narrative arc (early/mid/late) → demos → key mantra → transition
Tool/Product Demo — showing how something works
- Structure: Hook → Problem/Context → Tool Intro → Demo → Honest Limitations → CTA
- Example: "This Free Tool Replaced My $200/month Software"
- Heavy on screen recording, light on talking head
What this file has done since we first saw it
Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.
- 2d ago First seen · 209 lines · 81 tokens per session scan A cf747c038c9a
outlines is a skill published in the GitHub repository AI-Answer/ContentRepurposeSystem (12 stars, last pushed 2mo ago), licensed MIT. It adds 81 tokens to every session and 1,837 once invoked, about $0.0004 per session on Opus 5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-30.
Other skills, from other repositories
muapi-ai-clipping
Turn a long video into N viral-ready short clips with a single managed API call. Wraps muapi.ai's /ai-clipping endpoint, which handles transcription, highlight ranking through a virality framework (hook / emotional peak / opinion bomb / revelation / conflict / quotable / story peak / practical value), overlap dedupe…
muapi-youtube-shorts
Auto-generate viral 9:16 YouTube Shorts (or TikTok / Reels clips) from a long-form video. Thin platform-aware wrapper around the AI Clipping skill — picks sensible defaults for short-form social platforms (9:16, 30–60s sweet spot) and delegates the actual highlight extraction + crop to muapi.ai's /ai-clipping endpoint.
muapi-nano-banana
Reasoning-driven image generation using structured creative briefs (Gemini 3 style) — generates high-fidelity images via muapi.ai with logic-based prompting.
data-artist
Create beautiful data visualizations with mathematical elegance, color theory, and narrative design - the "Data is Beautiful" aesthetic.
muapi-media-editing
Edit and enhance images and videos with AI via muapi.ai — prompt-based editing, upscaling, background removal, face swap, lipsync, video effects, and more.
gpt-image-2
面向 GPT Image 2 的图像生成 / 编辑技能。可在 3 种环境下使用：(A) Garden 本地模式，通过 OpenAI 兼容接口直接出图并落盘；(B) Host-Native 模式，把本 Skill 当作提示词工程指引，把渲染好的 prompt 交给宿主 Agent 自带的图像工具出图；(C) Advisor 模式，宿主无任何图像工具时退化为高质量 prompt 顾问。涵盖 18 大类、80+ 个结构化模板，覆盖海报 / UI / 产品 / 信息图 / 学术图 / 技术架构图 / 漫画 / 头像 / 流程板 / 电影分镜 / IP 周边 / 编辑工作流等场景。.