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Linkedin AI Post Builder and Publisher

Name: Linkedin AI Post Builder and Publisher
Author: yadavabhijeet4

by yadavabhijeet4 · GitHub ↗ · v1.0.0 · MIT-0

cross-platform ⚠ suspicious

307

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Install in OpenClaw

/install linkedin-ai-optimizer

Description

Post updates to LinkedIn, track analytics, and optimize content.

README (SKILL.md)

LinkedIn Skill

Post updates, track performance, and optimize your content for maximum reach.

Setup & Authentication

Create an App: Go to LinkedIn Developers, create an app, and add the "Sign In with LinkedIn" and "Share on LinkedIn" products.

Generate Token: Use the included helper script to generate an OAuth 2.0 Access Token.

# Set your credentials
export LINKEDIN_CLIENT_ID="your_client_id"
export LINKEDIN_CLIENT_SECRET="your_client_secret"
export LINKEDIN_REDIRECT_URI="http://localhost:8000/callback"

# Run the auth helper
uv run /opt/homebrew/lib/node_modules/openclaw/skills/linkedin/scripts/linkedin_auth.py

Save Token: Save the generated token as LINKEDIN_ACCESS_TOKEN in your environment.

Usage

1. Optimize & Feedback Loop (New!)

Analyze your draft against top-performing posts before you publish. Requires GEMINI_API_KEY.

uv run /opt/homebrew/lib/node_modules/openclaw/skills/linkedin/scripts/linkedin_feedback.py "Your draft text here..."

2. Posting

Preview (Default):

uv run /opt/homebrew/lib/node_modules/openclaw/skills/linkedin/scripts/linkedin.py "Your post text"

Publish:

uv run /opt/homebrew/lib/node_modules/openclaw/skills/linkedin/scripts/linkedin.py "Your post text" --confirm

3. Analytics

View Stats: Reads from linkedin_history.jsonl and fetches current stats (Requires r_member_social).

uv run /opt/homebrew/lib/node_modules/openclaw/skills/linkedin/scripts/linkedin_analytics.py

Configuration

LINKEDIN_ACCESS_TOKEN: Valid OAuth 2.0 Access Token.
GEMINI_API_KEY: Required for the Feedback Loop/Optimizer.

Usage Guidance

This skill appears to implement what it says (posting, analytics, optional AI feedback), but the registry metadata incorrectly claims no required credentials. Before installing: (1) Inspect and control where you store LINKEDIN_CLIENT_SECRET and LINKEDIN_ACCESS_TOKEN (prefer ephemeral tokens and minimal scopes like w_member_social only when needed); (2) If you don't want the AI feedback feature, do not set GEMINI_API_KEY or run the feedback scripts; (3) Check any .env file in the working directory—python-dotenv will load it and could surface unrelated secrets; (4) Verify the LinkedIn app scopes and confirm you trust the author (registry owner unknown); (5) Run the scripts in a safe environment (e.g., non-production account) first to confirm behavior. The metadata mismatch lowers trust—if you can, ask the publisher to update declared requirements or obtain a publisher identity before proceeding.

Capability Analysis

Type: OpenClaw Skill Name: linkedin-ai-optimizer Version: 1.0.0 The LinkedIn AI Optimizer bundle is a legitimate tool for managing LinkedIn posts and analytics using OAuth 2.0 and the Gemini API. The scripts (e.g., linkedin.py, linkedin_auth.py) follow standard API integration patterns, and file operations are limited to the local workspace and history logging. There is no evidence of data exfiltration, credential theft, or malicious prompt injection.

Capability Assessment

ℹ Purpose & Capability

The name/description (LinkedIn post builder, analytics, optimizer) matches the scripts and endpoints (LinkedIn API + Google Generative Language). However the skill registry metadata claims no required environment variables or primary credential, while SKILL.md and the scripts clearly require LINKEDIN_CLIENT_ID, LINKEDIN_CLIENT_SECRET, LINKEDIN_ACCESS_TOKEN and optionally GEMINI_API_KEY. That metadata omission is an incoherence and reduces trust.

ℹ Instruction Scope

SKILL.md limits actions to creating a LinkedIn app, running included helper scripts, posting previews/publishing, and reading/writing a local history file. The scripts read/write expected local files (e.g., linkedin_history.jsonl, ~/.openclaw/workspace/memory/research_notes.md) and call LinkedIn and Google generativelanguage APIs. There are no hidden external endpoints beyond those two services. Minor scope note: the scripts use python-dotenv (load_dotenv()) which will parse a .env file in the working directory and could surface any secrets present there—verify your .env contents before running.

✓ Install Mechanism

There is no install spec and no remote download: this is an instruction-only skill with included Python scripts. No external archives or URL-based installs were observed.

⚠ Credentials

The functionality legitimately needs LinkedIn credentials and (optionally) a Gemini API key, but the skill metadata did not declare these required env vars or a primary credential. Requiring LINKEDIN_CLIENT_SECRET and LINKEDIN_ACCESS_TOKEN is sensitive but proportionate to posting and analytics; requiring GEMINI_API_KEY for optimization is optional but should have been declared. Also, python-dotenv's load_dotenv() means the script may read a local .env file—ensure it doesn't contain unrelated secrets you don't want read/exposed.

✓ Persistence & Privilege

The skill does not request 'always: true', does not change other skills' configs, and does not request elevated platform-wide privileges. It reads/writes a local history file (linkedin_history.jsonl) which is expected behavior for logging posts.

How to Use

Make sure OpenClaw is installed (local or Docker)
Run the install command in chat: /install linkedin-ai-optimizer
After installation, invoke the skill by name or use /linkedin-ai-optimizer
Provide required inputs per the skill's parameter spec and get structured output

Version History

v1.0.0

- Initial release of the LinkedIn skill. - Post updates to LinkedIn and preview before publishing. - Track performance with analytics, including stats from your post history. - Optimize draft content using a feedback loop that analyzes against top-performing posts (requires GEMINI_API_KEY). - Simple setup with OAuth 2.0 authentication instructions.

Metadata

Slug linkedin-ai-optimizer

Version 1.0.0

License MIT-0

All-time Installs 0

Active Installs 0

Total Versions 1

Frequently Asked Questions

What is Linkedin AI Post Builder and Publisher?

Post updates to LinkedIn, track analytics, and optimize content. It is an AI Agent Skill for Claude Code / OpenClaw, with 307 downloads so far.

How do I install Linkedin AI Post Builder and Publisher?

Run "/install linkedin-ai-optimizer" in the OpenClaw or Claude Code chat to install it in one step — no extra setup required.

Is Linkedin AI Post Builder and Publisher free?

Yes, Linkedin AI Post Builder and Publisher is completely free, licensed under MIT-0. You can download, install and use it at no cost.

Which platforms does Linkedin AI Post Builder and Publisher support?

Linkedin AI Post Builder and Publisher is cross-platform and runs anywhere OpenClaw / Claude Code is available (cross-platform).

Who created Linkedin AI Post Builder and Publisher?

It is built and maintained by yadavabhijeet4 (@yadavabhijeet4); the current version is v1.0.0.

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