Getting it into your agent
One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.
npx skills add Buzzmatic/awesome-agent-skills --skill brightdata-linkedingit clone --depth 1 https://github.com/Buzzmatic/awesome-agent-skillsWrote this? Show the measurements
A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.
[](https://agentmods.dev/skills/buzzmatic/awesome-agent-skills/brightdata-linkedin)<a href="https://agentmods.dev/skills/buzzmatic/awesome-agent-skills/brightdata-linkedin"><img src="https://agentmods.dev/badge/skills/buzzmatic/awesome-agent-skills/brightdata-linkedin/github.svg" alt="Measured on agentmods" height="20"></a>Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.
<a href="https://agentmods.dev/skills/buzzmatic/awesome-agent-skills/brightdata-linkedin"><img src="https://agentmods.dev/badge/skills/buzzmatic/awesome-agent-skills/brightdata-linkedin.svg" alt="Reviewed on agentmods" width="80" height="20"></a>What it costs to keep this loaded
Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5.1 | $0.00080 | $0.02670 |
| Opus 5 | $0.00040 | $0.01335 |
| Sonnet 5 | $0.00016 | $0.00534 |
| Haiku 4.5 | $0.00008 | $0.00267 |
Grade A, and why
brightdata-linkedin scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 8d ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
How it starts
The opening of the file, as written. The whole thing — 376 lines — stays where its author put it; the contents beside it link to each section on GitHub.
BrightData LinkedIn Scraper
LinkedIn data collection using BrightData's Datasets API (Web Scraper IDE). All operations save results to disk and return summaries to context.
When to Use This Skill
Use brightdata-linkedin (this skill) when:
- Need LinkedIn job search by keyword/location (not just by URL)
- Need to discover posts from company pages or profiles
- Need people search functionality
- Want direct control over the Datasets API parameters
- Need both sync and async modes
Use brightdata (SDK skill) when:
- Scraping general websites, SERP, or Amazon data
- Using simple URL-based LinkedIn scraping
- Prefer the SDK abstraction layer
Overview
This skill provides access to BrightData's LinkedIn scrapers for collecting:
- People Profiles: Full profile data from LinkedIn profile URLs
- Company Information: Company page data from LinkedIn company URLs
- Job Listings: Job details by URL or discover jobs by keyword/location
- Posts: Posts by URL or discover posts by company/profile
- People Search: Search results from LinkedIn people search URLs
Quick Start
Single Profile Scrape:
python skills/brightdata-linkedin/scripts/fetch.py \
--endpoint profiles \
--input "https://www.linkedin.com/in/username"
Bulk Company Scrape:
python skills/brightdata-linkedin/scripts/fetch.py \
--endpoint companies \
--input companies.json \
--batch
Job Search by Keyword:
python skills/brightdata-linkedin/scripts/fetch.py \
--endpoint jobs-search \
--location "Berlin" \
--keyword "software engineer" \
--country DE \
--job-type "Full-time"
Available Endpoints
| Endpoint | Dataset ID | Input Type | Description |
|---|---|---|---|
profiles |
gd_l1viktl72bvl7bjuj0 | Profile URLs | LinkedIn people profile data |
companies |
gd_l1vikfnt1wgvvqz95w | Company URLs | LinkedIn company information |
jobs |
gd_lpfll7v5hcqtkxl6l | Job URLs | LinkedIn job listing details |
jobs-search |
gd_lpfll7v5hcqtkxl6l | Keyword + Location | Discover jobs by search criteria |
posts |
gd_lyy3tktm25m4avu764 | Post URLs | LinkedIn post content |
posts-company |
gd_lyy3tktm25m4avu764 | Company URLs | Posts from company pages |
posts-profile |
gd_lyy3tktm25m4avu764 | Profile URLs | Posts from user profiles |
people-search |
gd_m8d03he47z8nwb5xc | Search URLs | LinkedIn people search results |
What ships with it
4 files beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.
What this file has done since we first saw it
Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.
- 8d ago First seen · 376 lines · 80 tokens per session scan A 67878a04f42d
brightdata-linkedin is a skill published in the GitHub repository Buzzmatic/awesome-agent-skills (1 stars, last pushed 2mo ago), licensed MIT. It adds 80 tokens to every session and 2,670 once invoked, about $0.0004 per session on Opus 5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-31.
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