Jakeschincariol/linkedin-agent-skill
Eleven free Claude skills that run a LinkedIn account: posts off 21 hook formulas, comments, replies, profile score, weekly plan, and a humanizer that strips the AI fingerprint and scores the draft before it goes out.
Star History
Momentum
+20
STARS · LAST 30 DAYS
1
PER DAY
#375
MOST-STARRED Python
| Window | 7 days | 30 days | 90 days |
|---|---|---|---|
| Stars gained | +7 | +20 | +90 |
| Per day | 1 | 1 | 1 |
| Forks gained | +1 | +3 | +10 |
linkedin-agent-skill gained 20 stars in the last 30 days, about 1 a day, and now has 805. It is about 1 year old and has averaged roughly 805 stars a year. It ranks #375 among Python repositories and #2,975 across all languages on GitHubRepo.
Trending Record
6
DAYS ON TRENDING
#118
BEST RANK
Sep 23, 2026
FIRST APPEARANCE
Active
STATUS TODAY
linkedin-agent-skill has maintained a continuous presence across global trending indexes, peaking at #118. Below is the 30-day activity profile:
💡 Overview
linkedin-agent-skill is an open-source project written in Python: Eleven free Claude skills that run a LinkedIn account: posts off 21 hook formulas, comments, replies, profile score, weekly plan, and a humanizer that strips the AI fingerprint and scores the draft before it goes out.
Engineered for speed, consistency, and developer ease, it solves common hurdles in agent-skills, ai-humanizer, claude. It provides clear interfaces, comprehensive configuration options, and seamless integration with existing tools across the modern development stack.
⚡ Key Features
Optimized execution pipeline written in Python for predictable speed.
Zero-friction configuration with comprehensive sensible defaults out of the box.
Cross-platform runtime support across Linux, macOS, and Windows environments.
Strong typing and modular architecture designed for easy extension and maintainability.
Standardized CLI and API interfaces for smooth integration into CI/CD workflows.
Active community maintenance with regular dependency updates and security patches.
📥 Installation
$ pip install linkedin-agent-skill⚙ System Requirements
Platforms
- • macOS
- • Linux
- • Windows
Runtime & Dependencies
Python >= 3.9, pip, virtualenv
Architecture
x86_64, ARM64 (Apple Silicon & Graviton)
🧠 How It Works
linkedin-agent-skill coordinates its core functionality through a modular Python pipeline. It parses configuration parameters, validates inputs, and resolves dependencies asynchronously. By minimizing runtime overhead and keeping allocations localized, it delivers predictable performance in both local development environments and automated production workloads.
🎯 Production Use Cases
Autonomous AI Agents
Orchestrate intelligent workflows and tool-calling routines with linkedin-agent-skill.
Model Inference & Prompting
Integrate fast, local or cloud-hosted generative AI models directly into production code.
Context Memory & RAG
Augment language models with dynamic vector retrieval and structured project memory.
Developer Productivity
Automate repetitive engineering tasks, code generation, and test creation using AI agents.
🚀 Getting Started
Install linkedin-agent-skill using your package manager: `pip install linkedin-agent-skill`
Initialize your project workspace or configuration file for linkedin-agent-skill.
Import linkedin-agent-skill into your codebase or invoke it directly from your terminal.
Execute your test suite or run `linkedin-agent-skill --help` to verify successful setup.
👍 Strengths
⚠️ Considerations
⇄ Alternatives & Direct Competitors
👥 Who Should Use This
Developers and engineering teams building with Python, seeking reliable, tested, and actively maintained tooling for production workloads.
🏆 Nearby in the Rankings
Jakeschincariol/linkedin-agent-skill is currently ranked #2,975 by stars across every repository tracked on GitHubRepo. These are adjacent projects:
| Rank | Repository | Language | Stars | Action |
|---|---|---|---|---|
| #2,969 | noctalia-dev/umbriel | C++ | ★ 810 | Compare ↗ |
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| #2,973 | openabdev/openab | Rust | ★ 807 | Compare ↗ |
| #2,974 | Prithvi-Web/TreeMap-Disk-Visualizer | TypeScript | ★ 806 | Compare ↗ |
| #2,975 | Jakeschincariol/linkedin-agent-skill This Project | Python | ★ 805 | |
| #2,975 | cchanxzy/react-currency-input-field | TypeScript | ★ 805 | Compare ↗ |
| #2,975 | charmbracelet/catwalk | Go | ★ 805 | Compare ↗ |
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Frequently Asked Questions
What does linkedin-agent-skill do? +
Eleven free Claude skills that run a LinkedIn account: posts off 21 hook formulas, comments, replies, profile score, weekly plan, and a humanizer that strips the AI fingerprint and scores the draft before it goes out.
What language is linkedin-agent-skill written in? +
The primary language is Python. Topics include: agent-skills, ai-humanizer, claude, claude-code, claude-skills.
Is linkedin-agent-skill actively maintained? +
Yes, the last recorded push was on Sep 17, 2026 with 7 open issues being tracked.
How many stars does linkedin-agent-skill have? +
linkedin-agent-skill has 805 stars and 128 forks on GitHub.
How does linkedin-agent-skill rank among GitHub repositories? +
With 805 stars, Jakeschincariol/linkedin-agent-skill is ranked #2,975 globally across all repositories tracked on GitHubRepo and #375 among Python projects.
What license is linkedin-agent-skill distributed under? +
The repository reports a MIT license. Always verify the repository LICENSE file for legal terms.
