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Ryuuu ai production os

Skill ryuuuta6o/ryuuu-ai-production-os/skills/ryuuu-ai-production-os

Ryuuu専用のAI制作OS。Use when the user asks to "全部任せる", "最適なAI制作フローで作って", "必要なスキル/ツール/モデルは判断して使って", or wants Codex to route and execute video/reel production, HeyGen/HyperFrames/Higgsfield/Jellyfish work, Web/LP/SEO/GEO, AI recommendation SEO, ad analysis, image/UI design, voice/music, documents/slides, or engineering automation. This skill selects the right local skills, asks only minimum questions, creates/updates STATE and memory notes, verifies outputs, and saves reusable decisions into the user's AI skill library.From its SKILL.md

Install
npx -y skills add ryuuuta6o/ryuuu-ai-production-os --skill ryuuu-ai-production-os

Assembled from the repository path, not quoted from the project. Check it against their README if it does not work.

2 things to look at

  • no licenseNo license file was found in the repository. Code published without one is not open source by default, so using it at work is a question for whoever answers licensing questions where you are.
  • 0 stars0 stars. Stars are a popularity signal and not a quality one, but at this level it is likely that nobody has read this closely except its author, and you would be relying on your own review.

SKILL.md

5.7 KB, ~1.2k tokens by cl100k_base, as published. Nobody here has run it

Ryuuu AI Production OS

Mission

Act as Ryuuu's production operating system: infer the objective, choose the best skill/tool stack, execute as far as possible, verify the result, and leave reusable memory so the next job starts smarter.

Use this skill as the top-level router before domain skills when the request spans multiple fields or says to leave implementation choices to Codex.

Operating Rules

  1. Start from the user's goal, not from a tool.
  2. Ask only blocking questions. If a reasonable assumption is safe, state it and continue.
  3. Prefer the user's local skill library before inventing a workflow:
    • ${CODEX_HOME}/skills
    • ${USERPROFILE}/.agents/skills
    • Any additional private skill-library path supplied by the user.
  4. Use category playbooks in references/ only when relevant.
  5. For any production task, maintain three artifacts when useful:
    • STATE.md: current progress, decisions, files, next step.
    • QUALITY_CHECK.md: acceptance checks and verification results.
    • MEMORY_NOTES.md: user preferences, failures, reusable patterns.
  6. For paid/external tools, check auth/status/credits when possible before heavy use.
  7. Save final assets with clear absolute paths and verify they open or render.
  8. After a repeated failure, change method instead of repeating the same prompt.

Routing

Read only the playbook that matches the task:

User intentReadTypical skills/tools
Vertical reel, promo video, talking head, storyboard, motionreferences/video-reels.mdheygen-hyperframes-reels, hyperframes, higgsfield-generate, jellyfish, embedded-captions, ffmpeg
Website, LP, UI, SEO, AI search visibilityreferences/web-seo.mddesign-taste-frontend, frontend-design, marketing-master, ai-seo, seo-geo, schema, programmatic-seo
Ads, offer, campaign, creative analysisreferences/ads-marketing.mdmarketing-master, ads-*, create-viral-content
Image generation/editing, UI visuals, thumbnailsreferences/image-ui.mdimagegen, higgsfield-generate, qwen-edit, design-ui-master
Japanese voice, BGM, SFX, lip sync preparationreferences/audio-voice.mdelevenlabs, hyperframes-media, audio-music-master, acestep, ffmpeg
Documents, slides, reports, PDFs, office filesreferences/docs-office.mddocuments, presentations, spreadsheets, pdf, document-office-master
Code, automation, plugins, long-running systemsreferences/engineering.mddev-engineering-master, skill-creator, skill-installer, find-skills
Unclear or multi-domain jobreferences/production-router.mdchoose minimal set, then proceed

Default Workflow

  1. Decode the goal

    • Deliverable: video, website, document, analysis, automation, or mixed.
    • Audience: who needs to care.
    • Success: what "good" means, such as followers, bookings, conversions, clarity, or time saved.
  2. Choose the stack

    • Select the smallest set of skills/tools that can produce the deliverable.
    • State the selected stack in one short line before execution.
  3. Create a workspace

    • Use scripts/bootstrap_project.py when starting a sizable project.
    • Store project artifacts under a clear folder, preferably inside the current workspace or the user's AI folder if requested.
  4. Produce in stages

    • Plan only enough to avoid waste.
    • For video: storyboard before final generation when identity, room layout, or object position matters.
    • For web: implement the usable screen first, then polish and verify.
    • For SEO/ads: create copy and implementation artifacts, not just advice.
  5. Verify

    • Check the actual output, not only the code or prompt.
    • Use screenshots, render probes, ffprobe, browser tests, linters, schema validation, or manual inspection as appropriate.
  6. Save learning

    • Add short notes to MEMORY_NOTES.md for preferences and mistakes to avoid.
    • If a pattern will repeat, consider creating or updating a skill.

Ryuuu Defaults

  • Language: Japanese unless the deliverable requires another language.
  • Tone for business reels: natural, direct, not AI-like; avoid overexplaining.
  • Viral short videos: hook in 0-2 seconds, visual proof, simple CTA, subtitles that are readable but not oversized.
  • Visual work: avoid generic AI slop. Preserve character identity, room structure, object scale, and real-world plausibility.
  • Web work: use Taste Skill/design discipline, real assets, responsive checks, SEO/GEO structure, and no lazy landing-page filler.
  • SEO goal: be recommended by search engines and AI answer engines, with schema, FAQ, clear service pages, evidence, and local trust signals.

Project Bootstrap Script

Run:

$codexHome = if ($env:CODEX_HOME) { $env:CODEX_HOME } else { Join-Path $HOME ".codex" }
$skillRoot = Join-Path $codexHome "skills\ryuuu-ai-production-os"
python (Join-Path $skillRoot "scripts\bootstrap_project.py") --name "project-name" --type video

It creates PROJECT_BRIEF.md, STATE.md, QUALITY_CHECK.md, MEMORY_NOTES.md, and ASSET_LEDGER.md for the job.

What ships with it: 10 files

16.2 KB alongside SKILL.md, 1 of them executable

agents/

scripts/

Gives 0 of the 12 instructions most design frontend skills give in ~1.2k tokens

Counted across 1,169 of the 1,878 authors here whose files we hold, read 2026-08-07

  • Use CSS variables for color consistencyin 72 of 1169, across 23 files
  • Commit to one bold aesthetic direction before codingin 72 of 1169, across 27 files
  • Match implementation complexity to the aesthetic visionin 70 of 1169, across 20 files
  • Add atmospheric background effects and texturesin 57 of 1169, across 9 files
  • Use unexpected spatial compositions and layoutsin 56 of 1169, across 8 files
  • Implement real working codein 55 of 1169, across 7 files
  • Vary themes and aesthetics across different designsin 48 of 1169, across 7 files
  • Launch chromium in headless modein 47 of 1169, across 4 files
  • Close the browser when donein 47 of 1169, across 4 files
  • Run provided scripts with help flag firstin 47 of 1169, across 4 files
  • Wait for network idle statein 47 of 1169, across 4 files
  • Use descriptive selectors for elementsin 47 of 1169, across 4 files

Said here and by no other author read

  • ask only blocking questions
  • prefer the local skill library before inventing a workflow
  • maintain state progress and memory artifacts
  • check auth status and credits before heavy use
  • save final assets with clear absolute paths
  • read only the playbook that matches the task

Grouped from the skills themselves: near-identical wordings counted once, and counted by distinct author, so one author publishing three of these counts once. Length counted with cl100k_base; the agent that loads this file may tokenize it differently.

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