본문으로 건너뛰기
cccskills
무료GitHub에 공개

linkedin-post-research

Search LinkedIn posts by keywords, sorted by engagement or date. Use when researching what people are saying about a topic on LinkedIn, finding high-engagement content, identifying thought leaders, or discovering warm leads through post engagement. Returns author, post text, reactions, comments, shares, post URL, and date. No LinkedIn cookies or login required.

한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.

연동 도구LinkedIn

실행 점수 미검증

설치 방법 보기

포함된 파일(3)

  • SKILL.md5.1 KB
  • scripts/search_posts.py11.0 KB
  • skill.meta.json267 B

SKILL.md(원문)

설치하기 전에 에이전트에게 전달되는 지시 내용을 확인할 수 있습니다.

LinkedIn Post Research

Search LinkedIn for posts matching keywords via Apify. Returns posts sorted by engagement or date, with author info, full text, reaction counts, and direct URLs.

No LinkedIn cookies. No login. Just keywords in, posts out.

When to Auto-Load

Load this skill when:

  • User says "search LinkedIn posts", "what are people saying about X on LinkedIn", "find LinkedIn content about"
  • User wants to find high-engagement posts on a topic
  • User wants to identify who's posting about a specific topic (thought leader discovery)
  • User wants to find posts to extract commenters from (warm lead pipeline)

Prerequisites

Apify API Token

Required for searching LinkedIn posts. Set in .env:

APIFY_API_TOKEN=your_token_here

No LinkedIn cookies, login, or session tokens needed. That's the only setup.


How It Works

  1. Takes one or more keywords
  2. Calls the apimaestro/linkedin-posts-search-scraper-no-cookies Apify actor
  3. Returns posts with author, text, engagement metrics, date, and URL
  4. Deduplicates across keywords by activity_id
  5. Sorts by engagement (total reactions) descending, or by date

Quick Start

# Single keyword search
python3 skills/capabilities/linkedin-post-research/scripts/search_posts.py \
  --keyword "AI sourcing" --max-items 20

# Multiple keywords
python3 skills/capabilities/linkedin-post-research/scripts/search_posts.py \
  --keyword "AI sourcing" --keyword "recruiting automation" --max-items 30

# Sort by date (most recent first)
python3 skills/capabilities/linkedin-post-research/scripts/search_posts.py \
  --keyword "AI agents" --sort-by date_posted --max-items 20

# Output as CSV
python3 skills/capabilities/linkedin-post-research/scripts/search_posts.py \
  --keyword "AI agents" --output csv --output-file results.csv

# Summary table
python3 skills/capabilities/linkedin-post-research/scripts/search_posts.py \
  --keyword "AI agents" --output summary

CLI Reference

FlagDefaultDescription
--keyword, -krequiredKeyword to search (can be repeated for multiple keywords)
--max-items50Max posts to return per keyword
--sort-byrelevanceSort order: relevance or date_posted
--output, -ojsonOutput format: json, csv, summary
--output-filestdoutWrite output to file
--tokenenv varApify API token (overrides APIFY_API_TOKEN env var)
--timeout120Max seconds to wait for Apify run

Apify Actor Details

Actor: apimaestro/linkedin-posts-search-scraper-no-cookies

API call:

curl -X POST "https://api.apify.com/v2/acts/apimaestro~linkedin-posts-search-scraper-no-cookies/runs?token=$APIFY_API_TOKEN" \
  -H "Content-Type: application/json" \
  -d '{
    "keyword": "AI agents",
    "maxItems": 50,
    "sortBy": "date_posted"
  }'

Polling for results:

# Check run status
curl "https://api.apify.com/v2/acts/apimaestro~linkedin-posts-search-scraper-no-cookies/runs/{RUN_ID}?token=$APIFY_API_TOKEN"

# When status is SUCCEEDED, fetch results
curl "https://api.apify.com/v2/datasets/{DATASET_ID}/items?token=$APIFY_API_TOKEN"

Output Schema

{
  "author": "Jane Smith",
  "author_headline": "VP of Sales at Acme Corp",
  "author_profile_url": "https://www.linkedin.com/in/janesmith",
  "keyword": "AI sourcing",
  "reactions": 142,
  "comments": 28,
  "shares": 12,
  "reactions_by_type": {"LIKE": 100, "EMPATHY": 30, "PRAISE": 12},
  "date": "2026-04-01",
  "post_preview": "First 200 chars of the post text...",
  "full_text": "Complete post text...",
  "url": "https://www.linkedin.com/posts/...",
  "activity_id": "7447040447966826496",
  "hashtags": ["#AI", "#sales"],
  "is_repost": false,
  "content_type": "text"
}

Output Columns (CSV)

ColumnDescription
authorPost author name
author_headlineAuthor's LinkedIn headline
author_profile_urlAuthor's LinkedIn profile URL
keywordWhich search keyword matched
reactionsTotal reaction count
commentsComment count
sharesShare count
datePost date (YYYY-MM-DD)
post_previewFirst ~200 characters
urlDirect link to the LinkedIn post
activity_idUnique post identifier
hashtagsComma-separated hashtags

Cost

Apify charges per compute usage. ~50 posts costs approximately $0.01-0.05 depending on the actor's pricing tier. The script prints cost info after each run.

Error Handling

ErrorFix
APIFY_API_TOKEN not setAsk user to add it to .env
Apify run fails or times outRetry once. If still fails, try a broader keyword.
0 resultsKeyword may be too specific. Try broader terms.

리뷰

아직 리뷰가 없습니다. 사용해 본 소감을 남겨 주세요.

댓글

로그인 없이 쓸 수 있습니다. 사용 후기, 질문, 작동하지 않은 환경 등을 편하게 남겨 주세요.

아직 댓글이 없습니다. 첫 댓글을 남겨 보세요.

보내면 바로 공개됩니다. 이메일 주소나 전화번호 같은 개인 정보는 쓰지 마세요. URL은 2개까지입니다.

0 / 1,000자

이 양식은 reCAPTCHA로 보호되며 Google 개인정보처리방침 및 서비스 약관이 적용됩니다.

같은 저장소의 스킬

Research supported advertising promises from a specific buyer's context, current product facts, customer language and observed ads. Turn them into static, video or copy ideas; match video ideas to actual recipes and save a product-scoped angle bank for write-video-ad-script. Product-led discovery can use verified facts without reviews. Reference persistence and reach are observations, not proof of performance.

한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.

gooseworks-ai/goose-skills1.3천2026년 10월 23일 업데이트

Analyze ad campaign performance data (Google, Meta, LinkedIn) to identify what's working, what's wasting budget, and specific cut/scale/test recommendations. Runs statistical analysis, funnel diagnostics, and multi-channel budget reallocation with specific dollar-amount shift recommendations and scenario modeling.

한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.

gooseworks-ai/goose-skills1.3천2026년 10월 23일 업데이트

For paid lead-gen and participant-recruitment ads, replaces vanity CPA with true CAC per qualified lead by joining ad-platform data with downstream funnel events, surfaces tracking gaps, and classifies every creative into Scale / Keep / Investigate / Cut.

한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.

gooseworks-ai/goose-skills1.3천2026년 10월 23일 업데이트

The intake stage of a Meta ad harness. Researches the brand first, states what it assumes, and asks only what it cannot infer and what would change money, claims or legal exposure if guessed wrong — at most four questions a turn, in plain business language. Writes the brand's stable facts (ads/brand.md), the campaign brief, and a log of what was asked vs assumed. Use it when someone wants to run Meta ads and the brand's ad facts are not yet recorded.

한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.

gooseworks-ai/goose-skills1.3천2026년 10월 23일 업데이트

Checks paid ads against the ad platform's rules (Meta, TikTok, Google, LinkedIn and others) and the brand's category rules: the copy, on-image or on-screen text, pictures and people. Rewrites what can be fixed honestly, adds the disclosures that are needed, and flags anything that needs a human or legal review, with one pass, fixed or flag line per ad and platform. Use alone when you already have the ad text or images and know where they will run; otherwise run the playbook for the job (e.g. make-static-ads, make-content, email-lifecycle).

한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.

gooseworks-ai/goose-skills1.3천2026년 10월 23일 업데이트

Analyze the message match between your ads and landing pages. Checks if the promise in the ad copy carries through to the landing page headline, body, and CTA. Flags disconnects that kill conversion rates. Works with Google, Meta, and LinkedIn ads.

한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.

gooseworks-ai/goose-skills1.3천2026년 10월 23일 업데이트

gooseworks-ai의 스킬 모두 보기

이 스킬의 문제 신고