An advanced writing style analysis engine designed to extract stylistic DNA from samples and generate high-fidelity mimicry guidelines.
Install & Download
1. ClawHub CLI
The fastest way to install a skill directly from the registry.
npx clawhub@latest install article-style-analyzer
2. Manual Installation
Copy the skill folder to one of these locations
~/.openclaw/skills/ <project>/skills/ Priority: Workspace > Local > Bundled
3. Prompt Installation
Copy this prompt to OpenClaw to install it automatically.
Help me install article-style-analyzer using Clawhub. If Clawhub is not installed, install it first (npm i -g clawhub).
Prefer to download?
Get the raw skill files in a ZIP archive.
What is Article Style Analyzer?
The Article Style Analyzer is a specialized tool within the Openclaw Skills ecosystem designed for deep linguistic profiling. It processes one or more text samples to identify unique writing signatures, including thought patterns, structural frameworks, and specific vocabulary choices. By synthesizing these elements, it creates a robust style model that allows users to replicate a specific author's voice or maintain brand consistency across diverse content pieces.
This skill goes beyond simple keyword counting; it performs cross-text validation to distinguish between a writer's permanent traits and thematic adjustments. Whether you are a marketer looking to scale brand content or a researcher analyzing editorial patterns, this skill provides a systematic, data-driven approach to stylistic deconstruction and reconstruction.
Article Style Analyzer Use Cases
- Analyzing the unique writing signature of a specific author or publication.
- Extracting style features to create comprehensive guides for content mimicry.
- Generating new content that strictly adheres to a predefined stylistic framework.
- Comparing multiple articles to identify consistent stylistic patterns and 'evergreen' traits.
How Article Style Analyzer Works
- The user provides one or more article samples (3-5 samples are recommended for high accuracy).
- For multiple samples, the skill performs individual analysis followed by cross-text comparison.
- The engine extracts constant traits (permanent style) and adaptive traits (context-specific shifts).
- A comprehensive style model is constructed, identifying thinking modes and linguistic techniques.
- The final output is generated according to a structured JSON schema, providing a mimicry roadmap.
Article Style Analyzer Setup
To integrate this capability into your workflow, ensure your environment is configured for Openclaw Skills. You can reference the analysis dimensions and output schemas locally:
# Navigate to your skill reference directory
cd references/
# Review the required output schema for JSON integration
cat output-schema.md
# Check the analysis dimensions for stylistic depth
cat analysis-dimensions.md
Article Style Analyzer Data Schema & Taxonomy
The skill organizes its findings into a structured hierarchy to ensure clarity and technical precision. The data is typically exported in JSON format following the schema defined in references/output-schema.md:
| Data Component | Description |
|---|---|
| Stylistic Constants | Features that appear across at least two or more samples. |
| Thinking Modes | The underlying logical structure and cognitive approach of the text. |
| Linguistic Techniques | Specific grammar, vocabulary, and rhetorical devices used. |
| Mimicry Guide | A step-by-step instruction set for replicating the analyzed style. |
| Error Avoidance | A list of common pitfalls to avoid when attempting to mimic the style. |
Article Style Analyzer Advanced Features
- Multi-text cross-validation to filter out statistical noise and identify true 'constant' traits.
- Dual-layer analysis covering both macro-level thinking patterns and micro-level language nuances.
- Automated self-checking mechanism that validates generated content against established mimicry priorities.
- Adaptive style modeling that differentiates between core brand voice and thematic adjustments.
SKILL.md
Loading
Related Openclaw Skills
TikTok Research Kit
A powerful data extraction tool for analyzing TikTok videos, creator profiles, and trending sounds without requiring an official API key.
Memo Collect
A streamlined utility for AI agents to capture, retrieve, and manage personal memos and reminders through simple CLI commands.
Convertible Bond Trading Bot
An automated quantitative trading bot designed to identify stable entries and execute high-sell low-buy strategies for convertible bonds.
X Research Kit
A local-first extraction tool for gathering structured metadata and media information from X (Twitter) without requiring official API access.
My Stock Report Skill
An automated financial analysis engine that generates deep-dive reports on US stocks and archives them directly to DingTalk multidimensional tables.
minium-test-generator
An intelligent utility designed to transform Minium recorded scripts into structured, maintainable test cases and Page Objects while ensuring 100% logic consistency.
Featured*
