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velasco810velasco810/claude-code-linkedin/skills/leads/SKILL.md

leads

Skill1 starsChanged 7 months agoMITView on GitHub

End-to-end LinkedIn lead generation — scrape a person's network and rank the best sales prospects

5 other projects use a version of this.

Adopted by

Most recently taken up by

  • Other versions5 projects use a version of this.

    Word for word · 0

    None found.

    Edited · 0

    None found.

    Wrote their own version · 5

    1. greglas75/zuvo★ 7same name
    2. donatassimkus/claude-ai-skills★ 1same name
    3. advisorppc-org/advisorseo-claude-plugin★ 0same name
    4. HalberdLLC/leadmerlin-skill★ 0same name
    5. victordelrosal/chairman★ 0same name

    How matches are found. Word for word: the exact same text. Edited: shares passages with this file (“99% same” means 99% of its five-word phrases also appear here; 10% or more counts). Their own version: similar meaning, or, weakest, the same name. We can’t tell which project had it first. Projects are counted among the 200 most-starred candidates, and mentions are links to the repository we found, up to 50 per site, so both counts are a floor.

  • In this repository4 other files it gives its agents.

The file

We split this skill into the rules it gives an agent

8 rules. 0 are common, 6 are distinctive, and 2 are very specific to this project.

  • 0

    Common

    Most of the 5 edited versions we read keep these.

  • 6

    Distinctive

    This author's own choices. Worth a look.

  • 2

    Very specific

    Tied to their project's names, files or tools. Probably skip.

  • Common
  • Distinctive
  • Very specific
  1. Very specific:

    Ask the user for everything you need.

    line 17
  2. Distinctive:

    Look for existing scraped data:

    line 29
  3. Distinctive:

    If data exists, tell the user:

    line 35
  4. Distinctive:

    If no data exists, proceed to scraping.

    line 38
  5. Distinctive:

    Before invoking the scraper, set expectations:

    line 42
  6. Distinctive:

    Wait for it to complete.

    line 55
  7. Very specific:

    After scraping completes, read ${CLAUDE_SKILL_DIR}/../../output/<person>/progress.json and display:

    line 59
  8. Distinctive:

    After analysis completes, provide a final wrap-up:

    line 74

“Common” is measured: kept by at least 6 in 10 of the 5 edited versions of this file we could read. “Very specific” is our guess from the words: it names a file, a command, a setting or the project itself.

Keep what fits and drop the rest. Your version, ready for your agents.
Files
SKILL.md

LinkedIn Leads — Sales Pipeline

Find and rank sales leads from a LinkedIn network based on your ideal customer profile.

Instructions

Step 1: Gather information

Ask the user for everything you need. If they provided details in $ARGUMENTS, use those and only ask for what's missing:

  1. Target person's name — A short label used as the output folder (e.g. "eduardo", "aum")
  2. LinkedIn URL — The connections page or search results URL to scrape
  3. Scrape type — "connections" (their connections list) or "search" (a search results page)
  4. Ideal customer profile — Who are you trying to sell to? Be specific about roles, company type, industry, and size. Examples:
    • "CISOs, Heads of Security, and AI Engineering leaders at AI-native SaaS companies"
    • "CROs, VPs of Sales, and RevOps leaders at companies with 50+ sellers"
    • "CTOs and Heads of Platform at mid-size fintech startups"

Step 2: Check for existing data

Look for existing scraped data:

${CLAUDE_SKILL_DIR}/../../output/<person>/meta.json

If data exists, tell the user:

"I found existing data for [person] — [count] profiles scraped on [date] from [url]. Want to use this data or re-scrape?"

If no data exists, proceed to scraping.

Step 3: Scrape (if needed)

Before invoking the scraper, set expectations:

Starting scrape of [person]'s [connections/search results]

  • A Chromium browser window will open (this is expected)
  • Typical scrape time: 10-15 minutes depending on connection count (one-time — you won't need to re-scrape to run different analyses)
  • You'll see real-time progress in the terminal

Invoke the scrape skill:

/linkedin:scrape <person> <type> <url>

Wait for it to complete.

Step 3.5: Post-scrape report

After scraping completes, read ${CLAUDE_SKILL_DIR}/../../output/<person>/progress.json and display:

Scrape complete: [count] profiles in [duration] ([rate] profiles/min) Starting lead analysis...

Step 4: Analyze

Invoke the analyze skill with the user's ICP and leads mode:

/linkedin:analyze <person> <icp criteria> leads

Step 5: Summary

After analysis completes, provide a final wrap-up:

Pipeline complete

  • Scrape: [count] profiles in [duration]
  • Analysis: [agent_count] agents, ~[tokens]K tokens, [duration]
  • Total wall time: ~[total]
  • Results: [tier1_count] Tier 1 / [tier2_count] Tier 2 / [tier3_count] Tier 3

Then:

  • Top 5 prospects and why they stand out
  • File locations for the full ranked list
  • Offer to format results for WhatsApp, email, or CSV if the user wants to share them

Download now (ZIP)

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