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SKILL verified MIT Self-run

Media

skill-minara-ai-media-agent-media · by Minara-AI

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Install

$ agentstack add skill-minara-ai-media-agent-media

✓ scanned · ✓ verified, works with Claude Code, Cursor, and more.

Security review

✓ Passed

No issues found. Passed automated security review. · v0.1.0 How review works →

  • ✓ Prompt-injection patterns
  • ✓ Secret / credential exfiltration
  • ✓ Dangerous shell & filesystem operations
  • ✓ Untrusted network calls
  • ✓ Known-malicious package signatures

What it can access

  • ✓ Network access No
  • ✓ Filesystem access No
  • ✓ Shell / process execution No
  • ✓ Environment & secrets No
  • ✓ Dynamic code execution No

From automated source analysis of v0.1.0. “Used” means the capability is present in the source — more access means more to trust, not that it’s unsafe.

View the full security report →

Verified badge

Passed review? Show it. Paste this badge into your README, it links to the public security report.

AgentStack Verified badge Links to your public security report.
[![AgentStack Verified](https://agentstack.voostack.com/badges/verified.svg)](https://agentstack.voostack.com/security/report/skill-minara-ai-media-agent-media)

Reliability & compatibility

✓ Security review passed
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— no reviews yet
○ 5mo ago

Declared compatibility

Claude CodeClaude Desktop

Compatibility is declared by the source manifest. End-to-end runtime verification is coming, see below.

Preview Execution monitoring

We're building live execution health for every listing: tool-call success rate, median latency, uptime, and last-checked timestamps, measured, not self-reported. It isn't live yet, so we don't show numbers we can't stand behind.

How agent discovery & health will work →
Are you the author of Media? Claim this listing to set pricing, connect Stripe payouts, and keep 70% of every sale.
Sign up to claim

About

/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: ''. 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/.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! ===

""

  Source: content/posts//source.md ( words)

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

  Images:  generated, resized for  platforms

  Manifest: content/posts//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

Source & license

This open-source skill is cataloged on AgentStack and links to its original source — we do not rehost the code.

Install and usage instructions live in the source repository linked above.

Reviews

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Versions

  • v0.1.0 Imported from the upstream source.