Agent skill · Data & Analytics

linkedin-outreach

End-to-end LinkedIn outreach campaign builder. Takes leads from Supabase, upstream skills, or CSV. Aligns on campaign goal and tone, writes personalized LinkedIn message sequences (connection request + follow-ups + optional InMail), presents for review, and exports for the user's outreach tool (Dripify, Botdog, Expandi, or manual CSV). Logs to Supabase outreach_log.

gooseworks-aigithub.com/gooseworks-aiGitHub ↗
claude-codecodexcursorMIT
Install
npx skills add gooseworks-ai/goose-skills --skill linkedin-outreach --agent claude-code

Same command for any agent — swap --agent for codex, cursor, copilot.

Facts
Files in the skill folder: 9
SKILL.md size: 17 KB
Bundled scripts: none
Path: skills/outreach/capabilities/linkedin-outreach/SKILL.md
Open the folder on GitHub →
Where it comes from
Stars: 1,091
Language: Python

Weekly change comes from our own snapshots, not the repository page — it measures attention, not adoption.

From the SKILL.md

# LinkedIn Outreach The LinkedIn counterpart to `cold-email-outreach`. Takes qualified leads from Supabase, builds personalized LinkedIn message sequences, exports for the user's LinkedIn outreach tool, and logs everything back to Supabase. **Tool-agnostic:** Asks the user which LinkedIn tool they use. All tools are CSV-import based — no API/MCP automation for LinkedIn tools (they're browser-based). Adapters handle column mapping and format differences per tool. ## When to Auto-Load Load this skill when: - User says "LinkedIn outreach", "connect with these leads on LinkedIn", "send LinkedIn messages", "set up a LinkedIn campaign" - An upstream skill connects with "create LinkedIn campaign" or "passes: supabase-eligible-leads" and user specifies LinkedIn - User completes `lead-qualification` and wants to reach out via LinkedIn ## Supported Outreach Tools This skill does NOT assume a specific tool. It asks first, then adapts. | Tool | Integration | How It Works | |------|------------|--------------| | **Dripify** | CSV import | Generate CSV matching Dripify's import format, user uploads manually | | **Botdog** | CSV import | Generate CSV with Botdog-compatible columns | | **Expandi**

What's inside
Steps it walks through
  1. When to Auto-Load
  2. Supported Outreach Tools
  3. Prerequisites
  4. Supabase
  5. LinkedIn Tool
  6. Character Limits
  7. Phase 0: Intake
  8. Campaign Goal
  9. Outreach Tool
  10. Lead Selection
  11. Tone & Style
  12. Sequence Structure
  13. Personalization
  14. Phase 1: Lead Selection from Supabase
Ships with 8 files
  • skill.meta.json
  • templates/sequence-templates/competitor-engagement.md
  • templates/sequence-templates/database-search.md
  • templates/sequence-templates/event-attendee.md
  • templates/sequence-templates/hiring-signal.md
  • templates/sequence-templates/kol-engagement.md
  • templates/sequence-templates/pain-language.md
  • templates/tone-presets.json
More from goose-skills
All skills →
About this skill
What does the linkedin-outreach skill do?

End-to-end LinkedIn outreach campaign builder. Takes leads from Supabase, upstream skills, or CSV. Aligns on campaign goal and tone, writes personalized LinkedIn message sequences (connection request + follow-ups + optional InMail), presents for review, and exports for the user's outreach tool (Dripify, Botdog, Expandi, or manual CSV). Logs to Supabase outreach_log.

How do I install it?

Run `npx skills add gooseworks-ai/goose-skills --skill linkedin-outreach --agent claude-code` — it drops the skill into your project so the agent can pick it up. Swap the --agent value for codex, cursor or copilot if you use one of those.

Where does this skill come from?

From gooseworks-ai/goose-skills, a repository with 1,091 stars. We read it straight from the repository tree rather than a submitted listing, so what you see here is what is actually published.

Is a popular skill a good skill?

Not necessarily. Stars measure attention, not adoption — a repository can trend for a week and be abandoned. That is why we show the weekly change from our own snapshots next to the total, instead of a single flattering number.

Keep going