LEAD GENERATION

GitHub Stargazer to Attio ICP Enrichment

Watches new stargazers on your dev-tool repo, enriches each person and their company, scores them against your ICP, and creates a qualified lead in Attio.

CategoryLead Generation
Enginesim
Difficultyintermediate
Triggerevent
Steps6
Setup~15 min

How it runs

The automated pipeline, trigger to output.

  • TriggerNew stargazer on repoGitHubGitHub
  • ActionFetch stargazer GitHub profileGitHubGitHub
  • ActionEnrich employer firmographicsExa
  • LogicScore against ICP and branch
  • ActionUpsert person + company in AttioAttio
  • OutputTag record with repo + star dateAttio

What it does

Every time someone stars your repository, this workflow pulls their GitHub profile, enriches their employer with firmographic data, scores the result against your ideal customer profile, and writes a qualified person plus company record into Attio. Low-fit stars are logged and skipped so your CRM stays clean.

When to use it

Run this when stars on an open-source dev tool are a real top-of-funnel signal and you want sales to work the humans behind them instead of a vanity counter. Best for PLG and developer-tool teams doing founder-led or rep-led outbound.

How it works

  1. 1A GitHub trigger fires on each new star (watch event) on the target repo.
  2. 2An action fetches the stargazer's full profile, public email, company string, and bio.
  3. 3An Exa company lookup enriches the employer: domain, size, industry, funding.
  4. 4A logic step scores fit on company size, industry, and seniority signals, then branches qualified vs. not.
  5. 5Qualified leads are upserted into Attio as a person linked to a company; unqualified ones are dropped.
  6. 6The new Attio record is tagged with the source repo and star date for attribution.

Set it up

What you configure once, before turning it on.

  1. 1
    Connect GitHubRepos, issues, pull requests, actions.
  2. 2
    Connect ExaNeural search across the web.
  3. 3
    Connect AttioReal-time CRM with structured data + powerful views.
  4. 4
    Set each agent's modelWe leave models unset so you pick the tier — fast + cheap, or top-quality.
  5. 5
    Tune it to your dataEdit the prompts, filters, and field mappings so it matches how your team works.
  6. 6
    Test, then turn it onRun once against a sample, confirm the output, then enable the trigger.

Run this workflow in your colony.

14-day trial. No DevOps. No Sales call. Provisioned in under a minute.