enrich-with-signals

Enrich company result sets with PredictLeads buying-intent signals into a SQLite and JSON cache.

277|88|Updated Jan 4, 2026
One-click install
npx skills add https://github.com/Othmane-Khadri/YALC-the-GTM-operating-system --skill enrich-with-signals
Or copy as Structured Prompt for Agent
Please help me install this Agent Skill.
Skill: enrich-with-signals
Source: https://github.com/Othmane-Khadri/YALC-the-GTM-operating-system/tree/main/.claude/skills/enrich-with-signals
Command: npx skills add https://github.com/Othmane-Khadri/YALC-the-GTM-operating-system --skill enrich-with-signals

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill includes references (resource) components.

What problem does it solve?

Enriching a lead/account list with timely buying-intent signals is slow and credit-consuming when done manually, but those signals are needed to prioritize outreach and improve downstream qualification.

Core Features & Use Cases

  • Pulls buying-intent signals for a result set: jobs, news, funding, tech stack signals, and optionally leadership changes, then writes them back to the local cache.
  • Fans out API calls with caching: reuses cached results with a 7-day TTL to reduce PredictLeads credit usage and supports forced refresh with no-cache.
  • Produces a usable enrichment summary: outputs per-company signal counts plus cache-hit and credit-consumption stats, then provides follow-ups for qualification or campaign segmentation.

Quick Start

Run enrich-with-signals for your latest result set by telling the assistant: enrich these companies with signals.

Frequently Asked Questions about enrich-with-signals

High-intent search queries and answers about installing and using this skill.

FAQPage Schema
How do I enrich a list of companies with buying-intent signals?

You can enrich companies with buying-intent signals by fetching jobs, funding, tech, and news data via the PredictLeads API, then persisting the results into a local SQLite and JSON cache for outreach prioritization.

What are buying-intent signals and when do I need them for account research?

Buying-intent signals are data points like job postings, funding rounds, tech stack changes, and news that indicate a company's readiness to buy, needed to prioritize outreach and improve downstream lead qualification.

Can I cache PredictLeads API responses to reduce credit usage?

Yes, you can cache PredictLeads API responses with a 7-day TTL in local SQLite and JSON storage to reduce credit usage, automatically reusing cached results and providing cache-hit and credit-consumption stats in the output summary.

How do I force a refresh of cached company signals?

You can force a refresh of cached company signals by using the no-cache option, which bypasses the 7-day TTL and makes fresh PredictLeads API calls to update the local SQLite and JSON cache with the latest intent data.

Does enrich-with-signals work with an existing CRM result set?

Yes, it validates an existing target result set of companies tied to a domain, fetches their PredictLeads buying-intent signals, and outputs per-company signal counts plus follow-up suggestions for campaign segmentation.

What signal types are available for lead enrichment?

Available buying-intent signals for lead enrichment include jobs, news, funding, tech stack, and optionally leadership changes, all fetched via the PredictLeads API and summarized with per-company signal counts.