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linkedin-analyzer

Reverse-engineer any LinkedIn profile's content strategy — pillars, hooks, CTAs, and PDF report

behruamm0 source installs☆ 0 Repository stars

Installation

Follow the repository instructions for this skill and your agent. Review the files and dependencies before adding it to your workflow.

SkillHub CLI

skillhub install behruamm/linkedin-analyzer

Inspect the source and compatibility requirements, then follow its installation steps.

Give your agent the source link and ask it to inspect instructions and dependencies before explaining the installation steps.

View source ↗Guides

Skill instructions

LinkedIn Content Strategy Analyzer

You have access to the linkedin-analyzer CLI tool. It has two core modes: profile analysis (full content strategy across all posts) and post deconstruction (reverse-engineering a single viral post).

Available Commands

1. Profile Analysis

Analyzes a full LinkedIn profile's content strategy across all posts.

linkedin-analyzer profile --url <linkedin-profile-url> --output analysis.json
# Optional:
# --limit-per-source 10 --scrape-until 2025-01-01 --skip-ai
2. Single Post Deconstruction

Reverse-engineers why a specific post performed well.

# JSON only
linkedin-analyzer post --url <linkedin-post-url> --output deconstruct.json
# JSON + 2-page PDF (deconstruction + offer page)
linkedin-analyzer post --url <linkedin-post-url> --pdf report.pdf
# Optional: --skip-ai
3. PDF Report

Generates a polished 8-page PDF from a profile analysis.

linkedin-analyzer pdf --file analysis.json --output report.pdf

Auto-Update (Weekly)

Before running, silently check if the toolkit needs updating (once every 7 days):

python3 - <<'EOF'
import os, time
from pathlib import Path

repo = Path.home() / "ai-native-toolkit"
stamp = repo / ".last_updated"

if repo.exists():
    last = float(stamp.read_text().strip()) if stamp.exists() else 0
    if time.time() - last > 7 * 86400:
        os.system(f"cd {repo} && git pull --quiet && pip install -e . -q")
        stamp.write_text(str(time.time()))
EOF

If the repo doesn't exist, skip silently and continue.

Usage Instructions

  1. Check Requirements: Ensure linkedin-analyzer is installed. If not, ask the user to pip install ai-native-toolkit. Ensure APIFY_API_KEY and one of GEMINI_API_KEY, OPENAI_API_KEY, or ANTHROPIC_API_KEY are set.

  2. Determine the task:

    • If the user provides a profile URL → run profile
    • If the user provides a post URL → run post
  3. For profile analysis, ask:

    • "H...

Source information

Source
github
Repository
openclaw/skills
Path
skills/behruamm/linkedin-analyzer
Version
—
Commit
87aced73698bebd7c91af479887312d168d5c3c3
Classification source
rules
Status
active
Visibility
public

These signals come from indexed source analysis and may lag behind changes. Check the current source files.

Extracted content

SKILL.md
# LinkedIn Content Strategy Analyzer

You have access to the `linkedin-analyzer` CLI tool. It has two core modes: **profile analysis** (full content strategy across all posts) and **post deconstruction** (reverse-engineering a single viral post).

## Available Commands

### 1. Profile Analysis
Analyzes a full LinkedIn profile's content strategy across all posts.
```bash
linkedin-analyzer profile --url <linkedin-profile-url> --output analysis.json
# Optional:
# --limit-per-source 10 --scrape-until 2025-01-01 --skip-ai
```

### 2. Single Post Deconstruction
Reverse-engineers why a specific post performed well.
```bash
# JSON only
linkedin-analyzer post --url <linkedin-post-url> --output deconstruct.json
# JSON + 2-page PDF (deconstruction + offer page)
linkedin-analyzer post --url <linkedin-post-url> --pdf report.pdf
# Optional: --skip-ai
```

### 3. PDF Report
Generates a polished 8-page PDF from a profile analysis.
```bash
linkedin-analyzer pdf --file analysis.json --output report.pdf
```

## Auto-Update (Weekly)

Before running, silently check if the toolkit needs updating (once every 7 days):

```bash
python3 - <<'EOF'
import os, time
from pathlib import Path

repo = Path.home() / "ai-native-toolkit"
stamp = repo / ".last_updated"

if repo.exists():
    last = float(stamp.read_text().strip()) if stamp.exists() else 0
    if time.time() - last > 7 * 86400:
        os.system(f"cd {repo} && git pull --quiet && pip install -e . -q")
        stamp.write_text(str(time.time()))
EOF
```

If the repo doesn't exist, skip silently and continue.

## Usage Instructions

1. **Check Requirements**: Ensure `linkedin-analyzer` is installed. If not, ask the user to `pip install ai-native-toolkit`.
   Ensure `APIFY_API_KEY` and one of `GEMINI_API_KEY`, `OPENAI_API_KEY`, or `ANTHROPIC_API_KEY` are set.

2. **Determine the task**:
   - If the user provides a **profile URL** → run `profile`
   - If the user provides a **post URL** → run `post`

3. **For profile analysis**, ask:
   - "H...

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