signal-scanner
Detect buying signals across TAM companies and watchlist personas. Three-phase architecture: (1) free diff-based signals from existing data (headcount growth, tech stack changes, funding rounds), (2) Apify-powered signals (job postings, LinkedIn content analysis, profile changes), and (3) post-processing with dedup, scoring, and lead status updates. Writes signals to Supabase signals table for downstream activation.
npx skills add gooseworks-ai/goose-skills --skill signal-scanner --agent claude-code
Same command for any agent — swap --agent for codex, cursor, copilot.
Weekly change comes from our own snapshots, not the repository page — it measures attention, not adoption.
# Signal Scanner Scheduled scanner that detects buying signals on TAM companies and watchlist personas, writes them to the `signals` table, and sets up downstream activation. ## When to Use - After TAM Builder has populated companies and personas - As a recurring scan (daily/weekly) to detect timing-based outreach triggers - When you need to move from static lists to intent-driven outreach ## Prerequisites - `SUPABASE_URL` + `SUPABASE_SERVICE_ROLE_KEY` in `.env` - `APIFY_TOKEN` in `.env` (for Phase 2 signals) - `ANTHROPIC_API_KEY` in `.env` (optional, for LLM content analysis) - TAM companies populated via `tam-builder` - Watchlist personas created for Tier 1-2 companies ## Signal Types | Priority | Signal | Level | Source | Cost | |----------|--------|-------|--------|------| | P0 | Headcount growth (>10% in 90d) | Company | Data diffs | Free | | P0 | Tech stack changes | Company | Data diffs | Free | | P0 | Funding round | Company | Data diffs | Free | | P0 | Job posting for relevant roles | Company | Apify linkedin-job-search | ~$0.001/job | | P1 | Leadership job change | Person | Apify linkedin-profile-scraper | ~$3/1k | | P1 | LinkedIn content analysis | Person | Apify linkedi
- When to Use
- Prerequisites
- Signal Types
- Config Format
- Database Write Policy
- Usage
- Flags
- Output
- Signals table writes
- Other database writes
- Console output
- Activation Score
- Connects To
- File Structure
Dry run first (ALWAYS DO THIS) — detect signals without writing to DB python skills/capabilities/signal-scanner/scripts/signal_scanner.py \ Full scan (only after user reviews dry-run results and approves) Test mode (5 companies max) Free signals only (skip Apify) Set all Apify signals to enabled: false in config
What does the signal-scanner skill do?
Detect buying signals across TAM companies and watchlist personas. Three-phase architecture: (1) free diff-based signals from existing data (headcount growth, tech stack changes, funding rounds), (2) Apify-powered signals (job postings, LinkedIn content analysis, profile changes), and (3) post-processing with dedup, scoring, and lead status updates. Writes signals to Supabase signals table for downstream activation.
How do I install it?
Run `npx skills add gooseworks-ai/goose-skills --skill signal-scanner --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.