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linkedin-analyzer

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

behruamm0 installations selon la source☆ 0 Étoiles du dépôt

Installation

Suivez les instructions du dépôt pour votre agent. Consultez les fichiers et dépendances avant l’installation.

SkillHub CLI

skillhub install behruamm/linkedin-analyzer

Examinez la source et la compatibilité, puis suivez les étapes d’installation.

Donnez le lien à votre agent et demandez-lui d’examiner instructions et dépendances avant d’expliquer les étapes.

Voir la source ↗Guides

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...

Informations sur la source

Source
github
Repository
openclaw/skills
Path
skills/behruamm/linkedin-analyzer
Version
—
Commit
87aced73698bebd7c91af479887312d168d5c3c3
Source de classification
rules
Statut
active
Visibilité
public

Ces informations proviennent de l’analyse indexée et peuvent être anciennes. Vérifiez les fichiers actuels.

Contenu extrait

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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