Monet Works — Content QA Remediation

Monet Works Content QA Pipeline

Goal Chain: L0 Medici Enterprises → L1 Monet Works → L2 Content Quality

Purpose

This skill is an automated QA and remediation pipeline for all content produced by Monet Works. It detects and automatically fixes common content issues, ensuring brand consistency and quality before publication.

How It Works

The content-qa CLI tool takes a markdown file as input and processes it through a series of checks and fixes. It outputs the remediated content to stdout and a structured JSON report of all changes to stderr.

Checks and Fixes

1. Banned Phrases: * *Detects:* A list of 37+ banned phrases (e.g., "in conclusion," "game-changer," "level up"). * *Fix:* Automatically removes or rephrases them.

2. Missing Disclaimers: * *Detects:* If the content discusses investments, finance, or taxes without the standard legal disclaimer. * *Fix:* Appends the required disclaimer to the end of the document.

3. Missing Call-to-Action (CTA): * *Detects:* If the content does not end with a clear CTA (e.g., a link to a product, a request to subscribe). * *Fix:* Appends a default, context-aware CTA based on the content's topic.

4. Excessive Length: * *Detects:* If the word count exceeds platform-specific limits (e.g., >600 words for LinkedIn). * *Fix:* Uses an AI model to generate a concise summary and offers it as an alternative.

5. AI Writing Patterns: * *Detects:* Integrates with the ogilvy-humanizer skill to detect and fix common AI writing tics. * *Fix:* Applies the humanizer's transformations.

Usage

CLI

# Run the QA pipeline on a draft file
content-qa fix path/to/draft.md > path/to/fixed-draft.md 2> path/to/report.json
Example report.json
{
  "changes": [
    {
      "type": "banned_phrase",
      "action": "removed",
      "original": "In conclusion, this is a great product.",
      "remediated": "This is a great product.",
      "line": 42
    },
    {
      "type": "missing_disclaimer",
      "action": "appended",
      "details": "Appended standard investment disclaimer."
    }
  ],
  "word_count": {
    "original": 750,
    "remediated": 738
  },
  "humanizer_score": {
    "before": 0.68,
    "after": 0.95
  }
}

Integration

This is the final step in the Monet Works content generation pipeline, run just before scheduling a post.

# Part of the main content pipeline script
cat $DRAFT_FILE | content-qa fix > $FINAL_FILE 2> $QA_REPORT_FILE

Configuration

This automated QA process saves hours of manual editing and ensures every piece of content meets our quality standards.

CLI

# Run the QA pipeline on a draft file
content-qa fix path/to/draft.md > path/to/fixed-draft.md 2> path/to/report.json
Example report.json
{
  "changes": [
    {
      "type": "banned_phrase",
      "action": "removed",
      "original": "In conclusion, this is a great product.",
      "remediated": "This is a great product.",
      "line": 42
    },
    {
      "type": "missing_disclaimer",
      "action": "appended",
      "details": "Appended standard investment disclaimer."
    }
  ],
  "word_count": {
    "original": 750,
    "remediated": 738
  },
  "humanizer_score": {
    "before": 0.68,
    "after": 0.95
  }
}

This automated QA process saves hours of manual editing and ensures every piece of content meets our quality standards.