Batch Content Factory

v1.0.0

Multi-platform content production line. Automates the entire workflow from topic research to content creation. Suitable for self-media operators producing hi...

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Install

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Best for remote or guided setup. Copy the exact prompt, then paste it into OpenClaw for openlark/batch-content-factory.

Previewing Install & Setup.
Prompt PreviewInstall & Setup
Install the skill "Batch Content Factory" (openlark/batch-content-factory) from ClawHub.
Skill page: https://clawhub.ai/openlark/batch-content-factory
Keep the work scoped to this skill only.
After install, inspect the skill metadata and help me finish setup.
Use only the metadata you can verify from ClawHub; do not invent missing requirements.
Ask before making any broader environment changes.

Command Line

CLI Commands

Use the direct CLI path if you want to install manually and keep every step visible.

OpenClaw CLI

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openclaw skills install batch-content-factory

ClawHub CLI

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npx clawhub@latest install batch-content-factory
Security Scan
Capability signals
CryptoCan make purchases
These labels describe what authority the skill may exercise. They are separate from suspicious or malicious moderation verdicts.
VirusTotalVirusTotal
Benign
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OpenClawOpenClaw
Benign
high confidence
Purpose & Capability
Name/description promise a full multi-platform automated production line (topic research, data-driven analysis, content creation). The included script, however, only generates templates, calendars, and a local-file SEO report; it does not perform web scraping, call AI models, or integrate with platform APIs. This is likely an overclaim rather than malicious behavior.
Instruction Scope
SKILL.md instructs running the included Python script with write/calendar/seo commands, and the script only reads a user-specified local file for SEO. The README's statement that "All analyses are based on actual data obtained by the script" is misleading since the script does not fetch external data. The instructions do not reference unrelated system files or environment variables.
Install Mechanism
There is no install spec (instruction-only), which is low risk. SKILL.md recommends installing pip packages (requests, jinja2, markdown) but the shipped Python code does not import requests, jinja2, or markdown — this mismatch is sloppy but not directly dangerous.
Credentials
The skill declares no required environment variables, no credentials, and no config paths. The script operates on local inputs only and does not attempt to read environment secrets.
Persistence & Privilege
The skill does not request persistent privileges and is not marked always:true. It does not modify other skills or agent-wide settings; it writes only to output paths explicitly supplied by the user.
Assessment
This skill appears to be a safe local template and report generator, not a full automation pipeline. Before installing or running it: (1) accept that it does not fetch web data or call an AI model — it's a helper that formats templates and inspects a local file for SEO; (2) inspect the script (you already have it) and run it in a sandbox or limited environment if you're cautious; (3) do not pass sensitive files to the seo command since it reads and prints file contents in its report; (4) be aware SKILL.md lists pip packages (requests, jinja2, markdown) that the code does not use — you can omit installing unused packages or verify why they were suggested; and (5) if you need true end-to-end automation (publishing to platforms, scraping research, or calling external APIs), expect to add explicit integrations and credentials — this skill does not do that by itself.

Like a lobster shell, security has layers — review code before you run it.

latestvk97b8c1197scvd2092xgdg4wvd85qn21
38downloads
0stars
1versions
Updated 11h ago
v1.0.0
MIT-0

Batch Content Factory

Overview

An automated content creation workflow that supports multi-platform content generation, SEO-optimized writing, and content calendar management. Suitable for bulk content production across platforms such as WeChat Official Accounts, Zhihu, Xiaohongshu, and Twitter.

Trigger Keywords

Content creation, copywriting, content creation, copywriting.

Core Capabilities

Capability 1: Multi-Platform Content Generation

Supports content generation for platforms such as WeChat Official Accounts / Zhihu / Xiaohongshu / Twitter, adjusting content style and format according to the characteristics of each platform.

Capability 2: SEO-Optimized Writing

Automatically inserts keywords and meta descriptions to optimize content visibility in search engines.

Capability 3: Content Calendar Management

Plans weekly publishing schedules and manages content release cadence.

Command List

CommandDescriptionUsage
writeGenerate contentpython scripts/content_factory_tool.py write [parameters]
calendarManage publishing calendarpython scripts/content_factory_tool.py calendar [parameters]
seoSEO optimizationpython scripts/content_factory_tool.py seo [parameters]

Usage Workflow

Scenario 1: Generate an AI Trends WeChat Official Account Article

python scripts/content_factory_tool.py write --platform wechat --topic 'AI Trends'

Scenario 2: Plan Next Week's Content Publishing Calendar

python scripts/content_factory_tool.py calendar --plan next-week

Scenario 3: Optimize Article SEO

python scripts/content_factory_tool.py seo --file article.md

Prerequisites

pip install requests jinja2 markdown

Output Format

Reports generated by the content factory adopt the following format:

# 📊 Content Factory Report

**Generated on**: YYYY-MM-DD HH:MM

## Key Findings
1. [Key finding 1]
2. [Key finding 2]
3. [Key finding 3]

## Data Overview
| Metric | Value | Trend | Rating |
|--------|-------|-------|--------|
| Metric A | XXX | ↑ | ⭐⭐⭐⭐ |
| Metric B | YYY | → | ⭐⭐⭐ |

## Detailed Analysis
[Multi-dimensional analysis content based on actual data]

## Actionable Recommendations
| Priority | Recommendation | Expected Outcome |
|----------|----------------|------------------|
| 🔴 High | [Specific recommendation] | [Quantified expectation] |
| 🟡 Medium | [Specific recommendation] | [Quantified expectation] |
| 🟢 Low | [Specific recommendation] | [Quantified expectation] |

References

Notes

  • All analyses are based on actual data obtained by the script; data is not fabricated
  • Missing data fields are marked "Data Unavailable" rather than guessed
  • It is recommended to combine with human judgment; AI analysis is for reference only
  • Please install Python dependencies before first use: pip install requests jinja2 markdown

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