# Media Write

> |

- **Type:** Skill
- **Install:** `agentstack add skill-minara-ai-media-agent-media-write`
- **Verified:** Yes — security-reviewed for prompt injection and unsafe behavior
- **Seller:** [Minara-AI](https://agentstack.voostack.com/s/minara-ai)
- **Installs:** 0
- **Category:** [Agent Skills](https://agentstack.voostack.com/c/agent-skills)
- **Latest version:** 0.1.0
- **License:** MIT
- **Upstream author:** [Minara-AI](https://github.com/Minara-AI)
- **Source:** https://github.com/Minara-AI/media-agent/tree/main/skills/media-write

## Install

```sh
agentstack add skill-minara-ai-media-agent-media-write
```

Requires the [AgentStack CLI](https://agentstack.voostack.com/docs/cli). Works with Claude Code, Cursor, and any MCP-compatible agent.

## About

# /media-write — Guided Writing & Variant Generation

Write content collaboratively, then generate platform-specific variants.

## Prerequisites

Before starting, read these shared library files:
- Read `lib/adapter-discovery.md` for adapter format.md location
- Read `lib/manifest-ops.md` for manifest creation
- Read `lib/humanize.md` for de-AI writing rules (MUST read before any writing)

## Step 1: Get the Brief

Check if a brief exists from `/media-idea`:
```bash
ls -t content/posts/*/brief.yaml 2>/dev/null | head -1
```

If a brief exists, read it and show the user:
- Topic, angle, outline, target platforms

If no brief exists, ask the user via AskUserQuestion:
1. "What do you want to write about?"
2. "Who is the audience?" (developers, beginners, specific community)
3. "Which platforms should we target?" (show configured platforms)

## Step 2: Create Post Directory

```bash
SLUG=$(echo "" | tr '[:upper:]' '[:lower:]' | sed 's/[^a-z0-9]/-/g' | sed 's/--*/-/g' | sed 's/^-//' | sed 's/-$//')
DATE=$(date +%Y-%m-%d)
POST_DIR="content/posts/${DATE}-${SLUG}"
mkdir -p "$POST_DIR/assets" "$POST_DIR/variants"
```

## Step 3: Guided Section-by-Section Writing

Work through the article section by section:

### Interaction model

1. **Propose an outline** based on the brief/topic. Use AskUserQuestion:
   "Here's my proposed outline for ''. Approve or suggest changes?"
   Show 4-7 sections with one-line descriptions.

2. **For each section:**
   - Propose the section content in chat (2-4 paragraphs)
   - Use AskUserQuestion: "How does this section look?"
     - A) Approve — move to next section
     - B) Shorter / more concise
     - C) More technical / add code examples
     - D) Different angle (provide feedback)
   - On approval, append the section to `source.md` using the Write or Edit tool
   - User can say "go back to section N" to revise earlier sections

3. **The file is the source of truth.** All approved content lives in `source.md`.
   Chat is the collaboration channel for drafting and feedback.

### Writing guidelines

- **Apply `lib/humanize.md` rules from the start.** Do not draft in AI-speak and fix later.
- Write in the user's voice (if brand voice is configured in `content/config/voice.yaml`, read it first)
- Include code examples where relevant for a developer audience
- Use clear headers (## for sections, ### for subsections)
- Keep paragraphs concise (3-5 sentences)
- Add image placeholders where visuals would help: ``
- Avoid the 29 AI patterns listed in `lib/humanize.md` — no significance inflation, no AI vocabulary, no filler phrases
- For Chinese content, follow the 中文去AI味 section: use 口语化 tone, avoid 成语堆砌, add personal perspective

## Step 4: Finalize Source

Once all sections are approved, read the complete `source.md` back to confirm.

Use AskUserQuestion:
"Here's the complete article. Ready to generate platform variants?"
- A) Yes, generate variants
- B) I want to edit more (specify which section)

## Step 5: Humanization Audit

After the user approves the full draft, run a dedicated de-AI pass before generating variants.

### Process

1. Re-read `lib/humanize.md` to refresh the pattern list.
2. Read the complete `source.md`.
3. Scan for each of the 29 AI writing patterns. For Chinese content, also apply the 中文去AI味 checks.
4. For each flagged passage, rewrite it following the "Fix" column in the pattern table.
5. Show the user a summary of changes:
   ```
   Humanization audit —  patterns found and fixed:
     - Section 2: removed significance inflation ("pivotal moment" → "useful")
     - Section 4: replaced AI vocabulary ("leverage" → "use")
     - Section 5: removed filler phrase ("It's worth noting that")
   ```
6. Use AskUserQuestion:
   "Here are the humanization edits. Accept all, or review individually?"
   - A) Accept all
   - B) Review each change
   - C) Skip humanization (keep original)
7. Apply accepted changes to `source.md`.

### Voice calibration (optional)

If `content/config/voice.yaml` exists:
- Compare the draft against the user's writing samples
- Adjust sentence length, vocabulary level, and tone to match
- Voice.yaml traits take priority over generic humanization rules

## Step 6: Generate Platform Variants

For each configured platform adapter:

1. Read the adapter's `format.md`:
   ```bash
   cat adapters//format.md
   ```

2. Following the adaptation rules in `format.md`, generate the variant from `source.md`:
   - Apply frontmatter template
   - Adapt content structure (length, tone, format)
   - Convert image paths as needed
   - Add platform-specific elements (canonical URL, tags, etc.)

3. Write the variant to `/variants/.md`

## Step 7: Create Manifest

Create `manifest.yaml` following the format in `lib/manifest-ops.md`:

```yaml
title: ""
created: 
updated: 
source: source.md
tags: []
language: en
canonical_url: ""

assets: []

variants:
  :
    file: variants/.md
    format: 
    status: draft
    error: null
```

Use the atomic write pattern from `lib/manifest-ops.md`.

## Step 8: Summary

```
Article written and variants generated:

  source.md —  words
  variants/devto.md — Dev.to format (draft)
  variants/hashnode.md — Hashnode format (draft)
  variants/github-pages.md — GitHub Pages format (draft)

Next steps:
  - Run /media-image to generate illustrations
  - Run /media-publish to publish to all platforms
  - Or run /media-publish --dry-run to preview first
```

## Updating Existing Content

When invoked with `--update` flag or on a post that already has `source.md`:

1. Read the existing `source.md` and `manifest.yaml`
2. Ask what the user wants to change
3. Edit the relevant sections
4. Regenerate ONLY the variant files (re-read each adapter's `format.md` and re-adapt)
5. Reset variant statuses to `draft` for regenerated variants
6. Do NOT overwrite variants with status `published` unless the user explicitly confirms

## Source & license

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

- **Author:** [Minara-AI](https://github.com/Minara-AI)
- **Source:** [Minara-AI/media-agent](https://github.com/Minara-AI/media-agent)
- **License:** MIT

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

## Pricing

- **Free** — Free

## Security capabilities

Automated source analysis of v0.1.0 — what this tool can access:

- **Network access:** no
- **Filesystem access:** no
- **Shell / process execution:** no
- **Environment & secrets:** no
- **Dynamic code execution:** no

*"Yes" means the capability is present in the source — more access means more to trust, not that it is unsafe.*


## Versions

- **0.1.0** — security scan: passed — Imported from the upstream source.

## Links

- Listing page: https://agentstack.voostack.com/l/skill-minara-ai-media-agent-media-write
- Seller: https://agentstack.voostack.com/s/minara-ai
- Browse the marketplace: https://agentstack.voostack.com/browse

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Listed on AgentStack — the marketplace for AI agent skills and MCP servers. Every listing is security-reviewed. Creators keep 70%.