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Social pack

Skill SamurAIGPT/Generative-Media-Skills/library/social/social-pack

Multi-modal Generative Media Skills for AI Agents (Claude Code, Cursor, Gemini CLI). High-quality image, video, and audio generation powered by muapi.ai.

Install
npx -y skills add SamurAIGPT/Generative-Media-Skills --skill social-pack

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What its author says it does

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Re-render a hero image into Instagram, TikTok, YouTube-shorts and Twitter/X aspect ratios.

SKILL.md

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Social Media Pack

Re-render a hero image into Instagram, TikTok, YouTube-shorts and Twitter/X aspect ratios.

Inputs

NameTypeRequiredDefaultDescription
source_imageimage_urlyesURL of the hero image (or asset_id from this session).
caption_ideatextnoOptional caption / overlay direction (kept short).
formatslistno1:1, 9:16, 4:5, 16:9Aspect ratios to produce.

Steps

Use the plan to fan out one node per format.

  1. For each requested aspect ratio in {{formats}}:
    • Call muapi image edit (model=nano-banana-2-edit) with the source image.
    • Prompt: "Reframe the composition to {{aspect_ratio}} for social media. Keep the subject centred and uncropped. Match the original lighting and palette. {{caption_idea_hint}}".
    • Where {{caption_idea_hint}} = "Leave headroom at the top for a caption: '<caption_idea>'." (only if caption_idea is non-empty).
  2. All formats run in parallel (no inter-node dependencies).
  3. Return one asset id per format, labelled with the platform it suits:
    • 1:1 → Instagram feed
    • 9:16 → TikTok / IG Reels / YT Shorts
    • 4:5 → Instagram portrait
    • 16:9 → Twitter / X / YouTube
    • 21:9 → cinematic banner

Notes

  • Don't generate fresh images — only reframe / re-edit the source.
  • If the source already matches a format, skip that node and surface the original asset id for it.

Trigger Keywords

social pack, resize for social, cross-post, multi-platform


Notes for the Executing Agent

  • This recipe is LLM-orchestrated: read each phase, gather any missing inputs from the user, then call muapi CLI commands. Use muapi auth configure first if MUAPI_API_KEY is unset.
  • For model IDs without a CLI alias yet, fall back to the raw endpoint via curl -X POST https://api.muapi.ai/api/v1/<endpoint> -H "x-api-key: $MUAPI_API_KEY" -H 'content-type: application/json' -d '{...}' and poll with muapi predict wait <request_id>.
  • Substitute {{input_name}} placeholders with the user's actual inputs before issuing each call.

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