Linkedin Engager Analytics
sergebulaev/linkedin-skills
Pull the people who liked or commented on any LinkedIn post and segment them by ICP fit (peer / aspirational / prospect / other).
Extract commenters from LinkedIn posts via Apify. An agent skill from gooseworks-ai/goose-skills.
Install Linkedin Commenter Extractor
$ npx skills add gooseworks-ai/goose-skills --skill linkedin-commenter-extractor -a claude-codeProject install by default; add -g for ~/.claude/skills/.
$ gh skill install gooseworks-ai/goose-skills linkedin-commenter-extractor --agent claude-codeProject scope by default; add --scope user for a personal install. Needs GitHub CLI 2.90.0 or later (public preview).
$ git clone --depth 1 https://github.com/gooseworks-ai/goose-skills.git skills-src && mkdir -p .claude/skills && cp -r skills-src/skills/lead-generation/capabilities/linkedin-commenter-extractor .claude/skills/linkedin-commenter-extractor && rm -rf skills-srcUse ~/.claude/skills/ instead of .claude/skills for a personal install. The folder must contain SKILL.md.
Claude Code skills documentation · loads skills from .claude/skills/
Install the "linkedin-commenter-extractor" agent skill from https://github.com/gooseworks-ai/goose-skills/tree/main/skills/lead-generation/capabilities/linkedin-commenter-extractor into .claude/skills/linkedin-commenter-extractor/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "linkedin-commenter-extractor", then confirm the skill loads.Claude Code copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$skill-installer install https://github.com/gooseworks-ai/goose-skills/tree/main/skills/lead-generation/capabilities/linkedin-commenter-extractorType this inside Codex. $skill-installer <name> installs a curated skill from openai/skills. The installer writes to $CODEX_HOME/skills (default ~/.codex/skills). Restart Codex if the skill does not show up.
$ npx skills add gooseworks-ai/goose-skills --skill linkedin-commenter-extractor -a codexProject install goes to .agents/skills/; add -g for ~/.codex/skills/.
$ gh skill install gooseworks-ai/goose-skills linkedin-commenter-extractor --agent codexProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/gooseworks-ai/goose-skills.git skills-src && mkdir -p .agents/skills && cp -r skills-src/skills/lead-generation/capabilities/linkedin-commenter-extractor .agents/skills/linkedin-commenter-extractor && rm -rf skills-srcUse ~/.agents/skills/ instead of .agents/skills for a personal install.
Codex skills documentation · loads skills from .agents/skills/
Install the "linkedin-commenter-extractor" agent skill from https://github.com/gooseworks-ai/goose-skills/tree/main/skills/lead-generation/capabilities/linkedin-commenter-extractor into .agents/skills/linkedin-commenter-extractor/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "linkedin-commenter-extractor", then confirm the skill loads.Codex copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ npx skills add gooseworks-ai/goose-skills --skill linkedin-commenter-extractor -a cursorProject install goes to .agents/skills/; add -g for ~/.cursor/skills/.
$ gh skill install gooseworks-ai/goose-skills linkedin-commenter-extractor --agent cursorProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/gooseworks-ai/goose-skills.git skills-src && mkdir -p .cursor/skills && cp -r skills-src/skills/lead-generation/capabilities/linkedin-commenter-extractor .cursor/skills/linkedin-commenter-extractor && rm -rf skills-srcUse ~/.cursor/skills/ instead of .cursor/skills for a personal install.
Cursor skills documentation · loads skills from .cursor/skills/, .agents/skills/, .claude/skills/, .codex/skills/
Install the "linkedin-commenter-extractor" agent skill from https://github.com/gooseworks-ai/goose-skills/tree/main/skills/lead-generation/capabilities/linkedin-commenter-extractor into .cursor/skills/linkedin-commenter-extractor/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "linkedin-commenter-extractor", then confirm the skill loads.Cursor copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ gemini skills install https://github.com/gooseworks-ai/goose-skills.git --path skills/lead-generation/capabilities/linkedin-commenter-extractor--scope user (default) or --scope workspace; --path is the subfolder of the repo that holds the skill; --consent skips the security confirmation prompt.
$ npx skills add gooseworks-ai/goose-skills --skill linkedin-commenter-extractor -a gemini-cliProject install goes to .agents/skills/; add -g for ~/.gemini/skills/.
$ gh skill install gooseworks-ai/goose-skills linkedin-commenter-extractor --agent gemini-cliProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/gooseworks-ai/goose-skills.git skills-src && mkdir -p .gemini/skills && cp -r skills-src/skills/lead-generation/capabilities/linkedin-commenter-extractor .gemini/skills/linkedin-commenter-extractor && rm -rf skills-srcUse ~/.gemini/skills/ instead of .gemini/skills for a personal install, then run /skills reload.
Gemini CLI skills documentation · loads skills from .gemini/skills/, .agents/skills/
Install the "linkedin-commenter-extractor" agent skill from https://github.com/gooseworks-ai/goose-skills/tree/main/skills/lead-generation/capabilities/linkedin-commenter-extractor into .gemini/skills/linkedin-commenter-extractor/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "linkedin-commenter-extractor", then confirm the skill loads.Gemini CLI copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ gh skill install gooseworks-ai/goose-skills linkedin-commenter-extractorInstalls for Copilot at project scope by default; add --scope user for a personal install. Preview a skill first with gh skill preview. Needs GitHub CLI 2.90.0 or later (public preview).
$ npx skills add gooseworks-ai/goose-skills --skill linkedin-commenter-extractor -a github-copilotProject install goes to .agents/skills/; add -g for ~/.copilot/skills/.
$ git clone --depth 1 https://github.com/gooseworks-ai/goose-skills.git skills-src && mkdir -p .github/skills && cp -r skills-src/skills/lead-generation/capabilities/linkedin-commenter-extractor .github/skills/linkedin-commenter-extractor && rm -rf skills-srcUse ~/.copilot/skills/ instead of .github/skills for a personal install. Commit .github/skills so cloud agent and code review can use it.
GitHub Copilot skills documentation · loads skills from .github/skills/, .claude/skills/, .agents/skills/
Install the "linkedin-commenter-extractor" agent skill from https://github.com/gooseworks-ai/goose-skills/tree/main/skills/lead-generation/capabilities/linkedin-commenter-extractor into .github/skills/linkedin-commenter-extractor/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "linkedin-commenter-extractor", then confirm the skill loads.GitHub Copilot copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ npx skills add gooseworks-ai/goose-skills --skill linkedin-commenter-extractor -a opencodeOpenCode documents no install command of its own. Project install goes to .agents/skills/; add -g for ~/.config/opencode/skills/.
$ gh skill install gooseworks-ai/goose-skills linkedin-commenter-extractor --agent opencodeProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/gooseworks-ai/goose-skills.git skills-src && mkdir -p .opencode/skills && cp -r skills-src/skills/lead-generation/capabilities/linkedin-commenter-extractor .opencode/skills/linkedin-commenter-extractor && rm -rf skills-srcUse ~/.config/opencode/skills/ instead of .opencode/skills for a personal install.
OpenCode skills documentation · loads skills from .opencode/skills/, .claude/skills/, .agents/skills/
Install the "linkedin-commenter-extractor" agent skill from https://github.com/gooseworks-ai/goose-skills/tree/main/skills/lead-generation/capabilities/linkedin-commenter-extractor into .opencode/skills/linkedin-commenter-extractor/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "linkedin-commenter-extractor", then confirm the skill loads.OpenCode copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
Facts
- Skill name
linkedin-commenter-extractor- GitHub stars
- 1.2k
- Used in
- 1 other repo
- Token cost
- ~722 tokens
- SKILL.md length
- 162 words
- Files
- 3 (incl. scripts)
- Skills in repo
- 273
- Repo updated
- First seen
- Licence
- MIT
At a glance
Extract commenters from LinkedIn posts via Apify. An agent skill from gooseworks-ai/goose-skills.
- Works in 5 steps: Takes one or more LinkedIn post URLs → Calls the… → Extracts commenter name, headline (title… → …
- Find warm leads engaging with relevant discussions
- SKILL.md covers Quick Start, How It Works, CLI Reference and Output Schema, plus 1 more section
- Runs Python scripts from its folder; calls python3; reaches linkedin.com; needs APIFY_API_TOKEN
What it does
Linkedin Commenter Extractor is an agent skill from gooseworks-ai/goose-skills. Extract commenters from LinkedIn posts via Apify. Returns commenter names, titles, LinkedIn profile URLs, and comment text. Use to find warm leads engaging with relevant discussions. No LinkedIn cookies required.
Its SKILL.md is about 720 tokens, which your agent loads only when the skill is triggered. The skill folder holds 3 other files, including scripts (for example `scripts/extract_commenters.py` and `skill.meta.json`).
It sits in Writing & Content, covering Social media posts, Web scraping and Resume and CV writing. It works with LinkedIn and Apify. The repository describes itself as: Library of Growth & GTM skills + data APIs for Claude Code, Codex, Cursor to run ads, social, content, lead gen, seo and data scraping. The licence is MIT.
When your agent uses it
- Find warm leads engaging with relevant discussions
- Tasks that involve Social media posts
- Tasks that involve Web scraping
Example prompts
- “/linkedin-commenter-extractor”
Requirements
- Python 3
- A credential in APIFY_API_TOKEN
Workflow steps
5 steps, taken from the first numbered list in SKILL.md.
- Takes one or more LinkedIn post URLs
- Calls the harvestapi~linkedin-post-comments Apify actor (no cookies needed)
- Extracts commenter name, headline (title + company), LinkedIn profile URL, and comment text
- Parses headline into separate title and company fields where possible
- Optionally deduplicates across multiple posts by LinkedIn profile URL
What it can do on your machine
Read from SKILL.md and the folder at commit c650c6d. It shows what the files ask for, not the result of running them.
Tool permissions
Pre-approves nothing: there is no allowed-tools line, so your agent's usual permission prompts apply.
From allowed-tools in the SKILL.md frontmatter.
Runs code
Ships 1 file in scripts/ (Python), which the agent can run.
Shell commands in SKILL.md call:
python3
From the folder's file list and the shell code blocks in SKILL.md.
Network
Hosts in commands or code, which the agent is likely to contact:
linkedin.com
From URLs in SKILL.md, links to its own repository left out.
Credentials
Names these keys or tokens, usually read from environment variables:
APIFY_API_TOKEN
From names ending in _API_KEY, _TOKEN, _SECRET, _KEY or _PASSWORD in SKILL.md.
Context cost
Linkedin Commenter Extractor loads about 722 tokens when it runs. Until then it costs about 60 tokens; SKILL.md has 162 words of instructions outside code blocks.
Estimates: characters ÷ 4, the usual rule of thumb; real counts depend on the model's tokenizer. Scripts and assets cost tokens only if the agent reads them.
Safety
Auto-check passed
The automated check found no risky patterns in SKILL.md.
Automated static check — not a guarantee. Review scripts before installing. It scans the text of SKILL.md for risky patterns (piping downloads into a shell, reading credential files, hidden Unicode, destructive commands); the scripts in this folder are not scanned.
SKILL.md
The full file from gooseworks-ai/goose-skills at commit c650c6d, republished under its MIT licence (© gooseworks-ai). 162 words, ~722 tokens.
Download SKILL.mdSave it as
.claude/skills/linkedin-commenter-extractor/SKILL.md (or your agent's skills folder). This skill also uses 2 other files; get the full folder from GitHub.- name
- linkedin-commenter-extractor
- description
- Extract commenters from LinkedIn posts via Apify. Returns commenter names, titles, LinkedIn profile URLs, and comment text. Use to find warm leads engaging with relevant discussions. No LinkedIn cookies required.
LinkedIn Commenter Extractor
Extract names, titles, companies, LinkedIn URLs, and comment text from people who commented on specific LinkedIn posts. Uses Apify — no LinkedIn cookies required.
Quick Start
Requires requests and APIFY_API_TOKEN environment variable.
# Extract commenters from a single post
python3 skills/linkedin-commenter-extractor/scripts/extract_commenters.py \
--post-url "https://www.linkedin.com/posts/someone_topic-activity-123456789"
# Multiple posts
python3 skills/linkedin-commenter-extractor/scripts/extract_commenters.py \
--post-url URL1 --post-url URL2
# Limit comments per post
python3 skills/linkedin-commenter-extractor/scripts/extract_commenters.py \
--post-url URL --max-comments 50
# Output formats
python3 skills/linkedin-commenter-extractor/scripts/extract_commenters.py --post-url URL --output json
python3 skills/linkedin-commenter-extractor/scripts/extract_commenters.py --post-url URL --output csv
python3 skills/linkedin-commenter-extractor/scripts/extract_commenters.py --post-url URL --output summary
# Deduplicate across multiple posts
python3 skills/linkedin-commenter-extractor/scripts/extract_commenters.py \
--post-url URL1 --post-url URL2 --dedupHow It Works
- Takes one or more LinkedIn post URLs
- Calls the
harvestapi~linkedin-post-commentsApify actor (no cookies needed) - Extracts commenter name, headline (title + company), LinkedIn profile URL, and comment text
- Parses headline into separate title and company fields where possible
- Optionally deduplicates across multiple posts by LinkedIn profile URL
CLI Reference
| Flag | Default | Description |
|---|---|---|
--post-url | required | LinkedIn post URL (can be repeated for multiple posts) |
--max-comments | 100 | Max comments to extract per post |
--output | json | Output format: json, csv, summary |
--dedup | false | Deduplicate commenters across multiple posts |
--token | env var | Apify API token (overrides APIFY_API_TOKEN env var) |
--timeout | 120 | Max seconds to wait for Apify run |
Output Schema
{
"name": "Jane Smith",
"headline": "VP of Finance at Acme Corp",
"title": "VP of Finance",
"company": "Acme Corp",
"linkedin_url": "https://www.linkedin.com/in/janesmith",
"comment_text": "Great insights on AI in accounting...",
"post_url": "https://www.linkedin.com/posts/...",
"profile_image_url": "https://..."
}Cost
Uses harvestapi~linkedin-post-comments Apify actor — ~$2 per 1,000 comments. No LinkedIn cookies or login required.
© gooseworks-ai, MIT. Rendered from Markdown: HTML in the file is shown as text, images as links, and headings moved down two levels. Raw file
Files
SKILL.md and 2 other files (scripts) in skills/lead-generation/capabilities/linkedin-commenter-extractor of gooseworks-ai/goose-skills.
- SKILL.md
- scripts/extract_commenters.py
- skill.meta.json
Open the folder on GitHubat commit c650c6d
Used in 1 other repository
We found 1 copy of this SKILL.md (exact, near-identical or edited) in other folders, from 1 other GitHub owner. This page covers the copy in gooseworks-ai/goose-skills, which our catalogue first saw on October 9, 2026.
Compare with similar skills
Linkedin Commenter Extractor next to the 5 skills that share the most tags, products or categories with it. Stars are the repository's; “used in” counts other GitHub owners with a copy.
| Skill | Stars | Used in | Tokens | Auto-check | Licence | Repo updated |
|---|---|---|---|---|---|---|
| Linkedin Commenter Extractor this skillgooseworks-ai/goose-skills | 1.2k | 1 repos | ~722 | Automated safety check: Pass | MIT | |
| Linkedin Engager Analyticssergebulaev/linkedin-skills | 4.4k | 1 repos | ~1.4k | Automated safety check: Pass | MIT | |
| Post Scorercharlie947/social-media-skills | 3.8k | — | ~2.4k | Automated safety check: Pass | MIT | |
| Unipile Linkedin SDKLeoYeAI/openclaw-master-skills | 2.2k | — | ~4.1k | Automated safety check: Notes | MIT | |
| Fullenrich Content EngagersOthmane-Khadri/YALC-the-GTM-operating-system | 318 | — | ~1.5k | Automated safety check: Warn | MIT | |
| Linkedinmanojbajaj95/claude-gtm-plugin | 105 | — | ~3.2k | Automated safety check: Pass | MIT |
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Related
Categories
Questions about Linkedin Commenter Extractor
What does Linkedin Commenter Extractor do?
Extract commenters from LinkedIn posts via Apify. An agent skill from gooseworks-ai/goose-skills. Linkedin Commenter Extractor is an agent skill from gooseworks-ai/goose-skills. Extract commenters from LinkedIn posts via Apify.
When should I use Linkedin Commenter Extractor?
Linkedin Commenter Extractor fits situations like: find warm leads engaging with relevant discussions; tasks that involve Social media posts; tasks that involve Web scraping.
How do I install Linkedin Commenter Extractor in Claude Code?
Run `npx skills add gooseworks-ai/goose-skills --skill linkedin-commenter-extractor -a claude-code`. Or copy the skill folder (skills/lead-generation/capabilities/linkedin-commenter-extractor in gooseworks-ai/goose-skills) into .claude/skills/linkedin-commenter-extractor in your project. Claude Code loads it when a task matches its description.
How do I install Linkedin Commenter Extractor in Codex?
Run `npx skills add gooseworks-ai/goose-skills --skill linkedin-commenter-extractor -a codex`. Or copy the skill folder (skills/lead-generation/capabilities/linkedin-commenter-extractor in gooseworks-ai/goose-skills) into .agents/skills/linkedin-commenter-extractor in your project. Codex loads it when a task matches its description.
Can I use Linkedin Commenter Extractor in Cursor, Gemini CLI or GitHub Copilot?
Cursor, Gemini CLI, GitHub Copilot and OpenCode also load SKILL.md folders. With the skills CLI, run `npx skills add gooseworks-ai/goose-skills --skill linkedin-commenter-extractor -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/linkedin-commenter-extractor, .gemini/skills/linkedin-commenter-extractor, .github/skills/linkedin-commenter-extractor and .opencode/skills/linkedin-commenter-extractor in your project.
What does Linkedin Commenter Extractor need to run?
Going by SKILL.md and its folder, Linkedin Commenter Extractor needs Python for the scripts in its folder, the command-line tools its instructions call (python3) and credentials named APIFY_API_TOKEN. Our summary lists: Python 3; A credential in APIFY_API_TOKEN.
Does Linkedin Commenter Extractor access the network?
SKILL.md names 1 domain. In commands or code: linkedin.com; the agent is likely to contact it when it follows the instructions. This is read from the text; nothing was executed.
Is Linkedin Commenter Extractor safe to install?
Our automated static check of SKILL.md found no risky patterns, such as piping downloads into a shell, reading credential files or hidden Unicode. It is not a guarantee. The check reads SKILL.md only: the scripts in the folder are not scanned, so read them before running anything.
What licence does Linkedin Commenter Extractor use?
Linkedin Commenter Extractor is published under the MIT licence (the repository's licence). It allows redistribution, so the full SKILL.md is shown on this page.
How many tokens does Linkedin Commenter Extractor use?
About 722 tokens (SKILL.md is roughly 2.9k characters). Agents keep only the skill's name and description in context until a task matches; then they load SKILL.md in full.
What are the alternatives to Linkedin Commenter Extractor?
Skills that share tags, products or a category with Linkedin Commenter Extractor: Linkedin Engager Analytics (sergebulaev/linkedin-skills, 4.4k stars), Post Scorer (charlie947/social-media-skills, 3.8k stars), Unipile Linkedin SDK (LeoYeAI/openclaw-master-skills, 2.2k stars) and Fullenrich Content Engagers (Othmane-Khadri/YALC-the-GTM-operating-system, 318 stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.
Who maintains Linkedin Commenter Extractor?
gooseworks-ai (a GitHub organization) maintains it in gooseworks-ai/goose-skills, which has 1,240 GitHub stars. The repository holds 273 skills in this directory. The repository was last updated on October 8, 2026.
Source: gooseworks-ai/goose-skills on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.