Goose-skills linkedin-profile-post-scraper

install

source · Clone the upstream repo

git clone https://github.com/gooseworks-ai/goose-skills

Claude Code · Install into ~/.claude/skills/

T=$(mktemp -d) && git clone --depth=1 https://github.com/gooseworks-ai/goose-skills "$T" && mkdir -p ~/.claude/skills && cp -r "$T/skills/capabilities/linkedin-profile-post-scraper" ~/.claude/skills/gooseworks-ai-goose-skills-linkedin-profile-post-scraper && rm -rf "$T"

manifest: skills/capabilities/linkedin-profile-post-scraper/SKILL.md

LinkedIn Profile Post Scraper

Scrape recent posts from specific LinkedIn profiles using the Apify

harvestapi/linkedin-profile-posts

actor.

Quick Start

Requires

APIFY_API_TOKEN

env var (or

--token

flag). Install dependency:

pip install requests

# Scrape recent posts from a profile
python3 skills/linkedin-profile-post-scraper/scripts/scrape_linkedin_posts.py \
  --profiles "https://www.linkedin.com/in/marcelsantilli" --max-posts 10

# Multiple profiles with keyword filtering
python3 skills/linkedin-profile-post-scraper/scripts/scrape_linkedin_posts.py \
  --profiles "https://www.linkedin.com/in/person1,https://www.linkedin.com/in/person2" \
  --keywords "AI,growth" --days 30

# Summary table
python3 skills/linkedin-profile-post-scraper/scripts/scrape_linkedin_posts.py \
  --profiles "https://www.linkedin.com/in/marcelsantilli" --output summary

CLI Reference

Flag	Default	Description
`--profiles`	required	LinkedIn profile URL(s), comma-separated
`--max-posts`	20	Max posts to scrape per profile
`--keywords`	none	Keywords to filter (comma-separated, OR logic)
`--days`	30	Only include posts from last N days
`--output`	json	Output format: `json` or `summary`
`--token`	env var	Apify token (prefer `APIFY_API_TOKEN` env var)
`--timeout`	300	Max seconds to wait for the Apify run

Cost

~$2 per 1,000 posts scraped. The script prints a cost estimate before running.

Notes

No native date filtering — dates are filtered client-side on
```
postedAt
```
/
```
postedDate
```
Profile URLs must be full LinkedIn URLs (e.g.
```
https://www.linkedin.com/in/username
```
)