cook-the-blog

This guide explains how to set up, configure, and run the cook-the-blog skill. This AI agent pipeline autonomously researches companies, extracts SEO keywords, generates custom cover images, writes high-converting MDX case studies without AI fluff, uploads assets to cloud storage, and pushes the final code to your designated GitHub repository.

Installation

Prerequisites

You need Node.js installed. It comes with npx built in.

Option 1: npx (All Agents)

npx "@opendirectory.dev/skills" install cook-the-blog --target claude

Supported --target values: claude, gemini, codex, opencode, anti-gravity, openclaw, hermes

Option 2: Native Plugin (Claude Code Only)

Run these two commands inside your Claude Code terminal:

# Add the OpenDirectory marketplace
/plugin marketplace add Varnan-Tech/opendirectory

# Install a skill directly
/plugin install cook-the-blog@opendirectory-marketplace

Option 3: Claude Desktop App

Step 1: Download Click Code → Download ZIP on this repo's GitHub page.

Step 2: Install

1. Open Claude Desktop > Customize > Skills > + > Upload a skill
2. Drop the downloaded zip or extracted folder

Prerequisites & Dependencies

Before running the skill, the AI agent needs access to several external tools, APIs, and environment details.

Agent Instruction: Before executing the pipeline for the first time, you (the AI Agent) must explicitly ask the user for any missing configuration details listed below (Target Repo, GCS Bucket, Email, etc.). Do not hardcode these values into the skill.md file automatically without asking.

1. Tavily Search (Deep Research)

Used for deep, high-quality web research to extract hard metrics, founder details, and GTM strategies.

• Setup: You need a Tavily API key from Tavily.
• Installation: Install the Tavily MCP server so the agent can use it natively.

  npx -y @modelcontextprotocol/server-tavily

• Environment Variable: Set TAVILY_API_KEY in your agent's environment or MCP config.

2. SerpApi (SEO Keyword Research)

Used to pull Google Trends data to find breakout search queries.

• Setup: Get a SerpApi key from SerpApi.
• Installation: Ensure Python 3 and the requests / google-search-results libraries are installed. The user must provide a custom Python script (e.g., blog_seo_research.py) that queries the Google Trends API. The agent must be told the exact file path to this script.
• Environment Variable: SERPAPI_KEY

3. Blog Cover Image CLI

A custom Node.js CLI tool used to generate 16:9 minimalist cover images with company logos.

• Installation: Install the tool globally via npm.

  npm i -g blog-cover-image-cli

• Usage: The agent calls it via blog-cover-cli generate -t "Title" -l "Logo URL" -o "./cover.png".

4. Cloud Storage (e.g., Google Cloud Storage, AWS S3)

Used to host the generated cover images. The user must specify which cloud provider they want to use.

• Setup (Example for GCP): The user needs a Google Cloud Service Account with storage write permissions.
• Installation: Install the Google Cloud SDK (gcloud and gsutil).
• Authentication: The user must provide a service-account.json file to authenticate.

  gcloud auth activate-service-account --key-file=service-account.json

• Target Bucket: The user must provide the target bucket URL (e.g., gs://your-bucket-name/covers/).

5. GitHub CLI & Git

Used for pushing the final MDX file to the target repository.

• Setup: Ensure git and gh (GitHub CLI) are installed on the host.
• Authentication: Log in to the GitHub CLI using a personal access token.

  gh auth login --with-token < token.txt

• Configuration: The agent will need the user's git config user.name and git config user.email to ensure proper commit attribution.

6. Email Notifications (SMTP)

Used to send a final success summary to the admin.

• Setup: The agent creates a Python script (send_summary.py) using the built-in smtplib.
• Credentials: The user must provide a dedicated sender Gmail account and an App Password (not their real password), as well as the destination admin email.

7. Stop Slop (AI Output Quality)

Used to ensure the generated case studies avoid typical AI fluff and maintain a high-quality, human-like tone.

• Setup: Add the Stop Slop skill to your agent's loaded skills before running the generation pipeline.

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Configuration Variables to Ask For

When initializing this skill, the agent must ask the user to provide or confirm the following placeholders before running the pipeline:

1. [TARGET_REPO_URL]: The exact GitHub repository URL or slug (e.g., username/my-blog-repo).
2. [TARGET_BUCKET]: The cloud storage bucket path (e.g., gs://my-images-bucket/blogs/).
3. [PUBLIC_IMAGE_BASE_URL]: The public base URL where the uploaded images will be accessible (e.g., https://storage.googleapis.com/my-images-bucket/blogs/).
4. [GIT_USER_NAME] & [GIT_USER_EMAIL]: The exact name and email to use for Git commit authorship.
5. [ADMIN_EMAIL]: Where to send the final summary report.
6. [SENDER_EMAIL] & [SENDER_APP_PASSWORD]: The credentials for the SMTP Python script.
7. [PATH_TO_SEO_SCRIPT]: The exact path to the Python script that handles the SerpApi Google Trends queries.
8. Brand Promotion Link: The URL and pitch text to inject into the final FAQ of the MDX template (e.g., "If you want to build this, check out MyBrand").

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How to Run

1. Once the user has provided the environment variables and configuration details, place the skill.md file in your agent's workspace.
2. The agent will read skill.md to understand the 8-step execution loop.
3. Trigger the agent by saying: "Run the case study generator for [Company Name]."
4. The agent will autonomously execute the entire pipeline from research to deployment.