Enrich With Signals

I'll wrap signals:enrich. Take a result set, fan out PredictLeads calls (cached 7 days per domain), and surface signal counts + summary per company.

When This Skill Applies

• "enrich these companies with signals"
• "add buying signals to this list"
• "pull intent data for [domain]"
• "check signals for these accounts"
• "fetch jobs and news for these companies"

NOT this skill (use find-lookalikes instead):

• "find similar companies" — that discovers new prospects.

NOT this skill (use qualify-leads --enrich-signals instead):

• "qualify these leads with signals" — that's the qualification pipeline with signal enrichment as a gate.

Workflow

Step 0 — Ask which result set

"Which result set should I enrich? Pass the id, or use the most recent."

Step 1 — Validate result set exists

Step 2 — Ask which signal types

"Which signal types? (default: jobs, funding, tech, news; also available: leadership)"

Step 3 — Shell out

cd ~/Desktop/gtm-os && set -a && source .env.local && set +a && \
  npx tsx src/cli/index.ts signals:enrich --result-set <id> --types <types>

Side-effecting → shell-out per benchmark.

Step 4 — Parse output

CLI emits per-company signal counts + cache hit ratio + total credits consumed.

Step 5 — Render

See references/example-output.md.

Step 6 — Offer follow-ups

"Want me to (a) qualify the enriched set via qualify-leads, (b) launch a campaign segmented by signal type?"

Notes

• ~1 PredictLeads credit per uncached domain per signal type.
• 7-day cache TTL; pass --no-cache to force re-fetch.
• Companies with no signals get an empty entry (still cached so we don't re-query).