agentsclimarketplace

Media

Skill Minara-AI/media-agent/skills/media

Install
npx -y skills add Minara-AI/media-agent --skill media

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One thing to look at

  • 6 stars6 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.

What its author says it does

Copied from the file, not written here

Master orchestrator for the media-agent workflow. Guides the user through the full content creation pipeline: ideation, writing, image generation, and multi-platform publishing. Can resume from any stage by reading the content manifest. This is a thin sequencer — sub-skills contain the canonical implementation logic.

SKILL.md

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/media — Full Content Creation Workflow

The complete guided workflow: idea → write → image → publish.

This orchestrator is a thin sequencer. For each stage, it reads the shared library files and follows the same logic as the individual sub-skills.

Prerequisites

Read these shared library files before proceeding:

  • Read lib/adapter-discovery.md
  • Read lib/manifest-ops.md
  • Read lib/image-processing.md

Step 0: Detect State & Resume

Check if there's an in-progress post:

# Find posts with draft variants (not yet fully published)
for dir in content/posts/*/; do
  if [ -f "$dir/manifest.yaml" ]; then
    has_draft=$(python3 -c "
import yaml
with open('${dir}manifest.yaml') as f:
    m = yaml.safe_load(f)
variants = m.get('variants', {})
drafts = [k for k,v in variants.items() if v.get('status') in ('draft','pending','failed')]
print('yes' if drafts else 'no')
" 2>/dev/null)
    if [ "$has_draft" = "yes" ]; then
      echo "IN_PROGRESS: $dir"
    fi
  fi
done

If an in-progress post is found, use AskUserQuestion: "Found an in-progress post: '<title>'. What would you like to do?"

  • A) Resume this post (continue from where we left off)
  • B) Start a new post
  • C) Finish publishing this post (jump to /media-publish)

Detecting resume stage

Read the manifest to determine which stage to resume from:

  • No source.md → resume from ideation/writing (Stage 1-2)
  • source.md exists but no variants → resume from variant generation (Stage 2, Step 5)
  • Variants exist but no assets → resume from image generation (Stage 3)
  • Assets exist but variants are draft → resume from publishing (Stage 4)

Stage 1: Ideation

Read skills/media-idea/SKILL.md and follow its workflow.

This stage produces a brief.yaml in the post directory.

If a brief.yaml already exists (resume scenario), skip to Stage 2.

Stage 2: Writing

Read skills/media-write/SKILL.md and follow its workflow.

This stage produces:

  • source.md (canonical content)
  • variants/<name>.md for each platform
  • manifest.yaml

If source.md and variants already exist (resume scenario), ask if the user wants to edit or proceed to images.

Stage 3: Image Generation

Read skills/media-image/SKILL.md and follow its workflow.

This stage produces:

  • Images in assets/
  • Platform-resized versions
  • Updated manifest with asset references

If images already exist (resume scenario), ask if the user wants to regenerate or proceed to publishing.

Skip condition: If the user doesn't have an OpenAI API key configured and doesn't want to provide their own images, skip this stage entirely.

Stage 4: Publishing

Read skills/media-publish/SKILL.md and follow its workflow.

This stage:

  • Validates all files
  • Publishes to each configured platform
  • Updates manifest with URLs and status

Stage 5: Complete

After publishing, show the final summary:

=== Content Published! ===

"<title>"

  Source: content/posts/<slug>/source.md (<word count> words)

  Published to:
    [OK] Dev.to → <url>
    [OK] Hashnode → <url>
    [OK] GitHub Pages → <url>

  Images: <count> generated, resized for <count> platforms

  Manifest: content/posts/<slug>/manifest.yaml

What's next?
  - Run /media to write another post
  - Edit source.md and run /media-write --update to regenerate variants
  - Run /media-publish to retry any failed platforms

Error Handling

If any stage fails:

  1. Report the error clearly
  2. Save all progress to disk (manifest, source, variants)
  3. Offer to retry the failed step or skip to the next stage
  4. The user can always resume later — the manifest tracks all state

Keep looking

Skills are one crate of 328,083. Ordering is by how many stacks a row turns up in, so the top of any crate is what has actually been picked rather than what has the most stars.