Detect buying signals from multiple sources, qualify leads, and generate outreach context
npx gooseworks install --claude # Then in your agent: /gooseworks <prompt> --skill signal-detection-pipeline
Monitor multiple signal sources to find companies actively in-market for your client's solution. Combine signals for higher-confidence leads.
Run the sources relevant to the client's ICP. Each is independent — run in parallel.
Skill: job-posting-intent
Companies hiring for roles in the problem area = budget allocated and pain acknowledged.
Skill: funding-signal-monitor
Recently funded companies = budget available, growth mandate.
Skill: luma-event-attendees
People attending events in the problem space = actively engaged.
Skill: reddit-post-finder
People complaining about or discussing the problem = experiencing the pain.
Skill: linkedin-post-research + linkedin-commenter-extractor
People posting about or engaging with the problem = thought leaders or practitioners.
After running relevant sources:
Diagnose Meta Ads campaign performance using Meta's actual system mechanics — Breakdown Effect, Learning Phase, Auction Overlap, Pacing, and Creative Fatigue — and produce structured, testable recommendations that avoid judging segments by average CPA instead of marginal efficiency.
Pre-flight policy check for Meta ads. Takes ad copy plus advertiser context, resolves and fetches the relevant Meta transparency-center policy pages at runtime, and returns a Pass / Fix Required / Block verdict with cited findings and rewrites.
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.