content-engine
Create platform-native content systems for X, LinkedIn, TikTok, YouTube, newsletters, and repurposed multi-platform campaigns. Use when the user wants social posts, threads, scripts, content calendars, or one source asset adapted cleanly across platforms.
Best use case
content-engine is best used when you need a repeatable AI agent workflow instead of a one-off prompt.
Create platform-native content systems for X, LinkedIn, TikTok, YouTube, newsletters, and repurposed multi-platform campaigns. Use when the user wants social posts, threads, scripts, content calendars, or one source asset adapted cleanly across platforms.
Teams using content-engine should expect a more consistent output, faster repeated execution, less prompt rewriting.
When to use this skill
- You want a reusable workflow that can be run more than once with consistent structure.
When not to use this skill
- You only need a quick one-off answer and do not need a reusable workflow.
- You cannot install or maintain the underlying files, dependencies, or repository context.
Installation
Claude Code / Cursor / Codex
Manual Installation
- Download SKILL.md from GitHub
- Place it in
.claude/skills/content-engine/SKILL.mdinside your project - Restart your AI agent — it will auto-discover the skill
How content-engine Compares
| Feature / Agent | content-engine | Standard Approach |
|---|---|---|
| Platform Support | Not specified | Limited / Varies |
| Context Awareness | High | Baseline |
| Installation Complexity | Unknown | N/A |
Frequently Asked Questions
What does this skill do?
Create platform-native content systems for X, LinkedIn, TikTok, YouTube, newsletters, and repurposed multi-platform campaigns. Use when the user wants social posts, threads, scripts, content calendars, or one source asset adapted cleanly across platforms.
Where can I find the source code?
You can find the source code on GitHub using the link provided at the top of the page.
Related Guides
AI Agents for Marketing
Discover AI agents for marketing workflows, from SEO and content production to campaign research, outreach, and analytics.
AI Agent for YouTube Script Writing
Find AI agent skills for YouTube script writing, video research, content outlining, and repeatable channel production workflows.
SKILL.md Source
# Content Engine Turn one idea into strong, platform-native content instead of posting the same thing everywhere. ## When to Activate - writing X posts or threads - drafting LinkedIn posts or launch updates - scripting short-form video or YouTube explainers - repurposing articles, podcasts, demos, or docs into social content - building a lightweight content plan around a launch, milestone, or theme ## First Questions Clarify: - source asset: what are we adapting from - audience: builders, investors, customers, operators, or general audience - platform: X, LinkedIn, TikTok, YouTube, newsletter, or multi-platform - goal: awareness, conversion, recruiting, authority, launch support, or engagement ## Core Rules 1. Adapt for the platform. Do not cross-post the same copy. 2. Hooks matter more than summaries. 3. Every post should carry one clear idea. 4. Use specifics over slogans. 5. Keep the ask small and clear. ## Platform Guidance ### X - open fast - one idea per post or per tweet in a thread - keep links out of the main body unless necessary - avoid hashtag spam ### LinkedIn - strong first line - short paragraphs - more explicit framing around lessons, results, and takeaways ### TikTok / Short Video - first 3 seconds must interrupt attention - script around visuals, not just narration - one demo, one claim, one CTA ### YouTube - show the result early - structure by chapter - refresh the visual every 20-30 seconds ### Newsletter - deliver one clear lens, not a bundle of unrelated items - make section titles skimmable - keep the opening paragraph doing real work ## Repurposing Flow Default cascade: 1. anchor asset: article, video, demo, memo, or launch doc 2. extract 3-7 atomic ideas 3. write platform-native variants 4. trim repetition across outputs 5. align CTAs with platform intent ## Deliverables When asked for a campaign, return: - the core angle - platform-specific drafts - optional posting order - optional CTA variants - any missing inputs needed before publishing ## Quality Gate Before delivering: - each draft reads natively for its platform - hooks are strong and specific - no generic hype language - no duplicated copy across platforms unless requested - the CTA matches the content and audience
Related Skills
Socratic Method: The Dialectic Engine
This skill transforms Claude into a Socratic agent — a cognitive partner who guides
vertex-engine-inspector
Inspect and validate Vertex AI Agent Engine deployments including Code Execution Sandbox, Memory Bank, A2A protocol compliance, and security posture. Generates production readiness scores. Use when asked to inspect, validate, or audit an Agent Engine deployment. Trigger with "inspect agent engine", "validate agent engine deployment", "check agent engine config", "audit agent engine security", "agent engine readiness check", "vertex engine health", or "reasoning engine status".
engineering-features-for-machine-learning
This skill empowers Claude to perform feature engineering tasks for machine learning. It creates, selects, and transforms features to improve model performance. Use this skill when the user requests feature creation, feature selection, feature transformation, or any request that involves improving the features used in a machine learning model. Trigger terms include "feature engineering", "feature selection", "feature transformation", "create features", "select features", "transform features", "improve model performance", and similar phrases related to feature manipulation.
feature-engineering-helper
Feature Engineering Helper - Auto-activating skill for ML Training. Triggers on: feature engineering helper, feature engineering helper Part of the ML Training skill category.
content-security-policy-generator
Content Security Policy Generator - Auto-activating skill for Security Fundamentals. Triggers on: content security policy generator, content security policy generator Part of the Security Fundamentals skill category.
conducting-chaos-engineering
This skill enables Claude to design and execute chaos engineering experiments to test system resilience. It is used when the user requests help with failure injection, latency simulation, resource exhaustion testing, or resilience validation. The skill is triggered by discussions of chaos experiments (GameDays), failure injection strategies, resilience testing, and validation of recovery mechanisms like circuit breakers and retry logic. It leverages tools like Chaos Mesh, Gremlin, Toxiproxy, and AWS FIS to simulate real-world failures and assess system behavior.
adk-engineer
Execute software engineer specializing in creating production-ready ADK agents with best practices, code structure, testing, and deployment automation. Use when asked to "build ADK agent", "create agent code", or "engineer ADK application". Trigger with relevant phrases based on skill purpose.
000-jeremy-content-consistency-validator
Validate messaging consistency across website, GitHub repos, and local documentation generating read-only discrepancy reports. Use when checking content alignment or finding mixed messaging. Trigger with phrases like "check consistency", "validate documentation", or "audit messaging".
persona-content-creator
Create, organize, and distribute content across Workspace.
game-engine
Expert skill for building web-based game engines and games using HTML5, Canvas, WebGL, and JavaScript. Use when asked to create games, build game engines, implement game physics, handle collision detection, set up game loops, manage sprites, add game controls, or work with 2D/3D rendering. Covers techniques for platformers, breakout-style games, maze games, tilemaps, audio, multiplayer via WebRTC, and publishing games.
ROS 2 Engineering Skills
A progressive-disclosure skill for ROS 2 development — from first workspace to
using-dbt-for-analytics-engineering
Builds and modifies dbt models, writes SQL transformations using ref() and source(), creates tests, and validates results with dbt show. Use when doing any dbt work - building or modifying models, debugging errors, exploring unfamiliar data sources, writing tests, or evaluating impact of changes.