OpenOutreach: Open-source AI agent for B2B lead generation — describe your product, it finds the people who fit and explains

by eracle · Agent Tool · ★ 2.9k

Last updated: · Indexed by AgentSkillsHub · Auto-synced every 8h

How to install OpenOutreach

docker run --pull always -it -v ~/.openoutreach/data:/app/data ghcr.io/eracle/openoutreach:latest
git clone https://github.com/eracle/OpenOutreach.git

Taken from the project's README on GitHub. Check the security audit before running it.

Security audit verdict: SAFE · quality 67/100

None of the 42 rules matched — no credential harvesting, no data exfiltration, no curl-pipe-shell installer. Scanned against 42 published rules built on the SlowMist agent-security taxonomy, refreshed every 8 hours. Full audit →

The quality score combines nine heuristic checks of the repo and its README: completeness, clarity, specificity, examples, structure, agent readiness, step-by-step content, instruction quality and security notes. It rates how well the project explains itself to an agent, not the code.

agentagenticagentic-marketingagentic-workflowautomationb2bemail-automationicplead-generationlead-qualification

Quick Facts

Stars2,859
Forks536
LanguagePython
CategoryAgent Tool
LicenseGPL-3.0
Quality Score67/100
Last Updated2026-08-31
Created2016-10-07
Platformscli, python
Est. Tokens~17k

About OpenOutreach

Describe your product. Define your target market. The AI finds the leads and emails them for you. Demo: 🚀 What is OpenOutreach? OpenOutreach is a self-hosted, open-source, email-first AI sales agent for B2B lead generation.

Compatible Skills

These tools work well together with OpenOutreach for enhanced workflows:

  • aaron-marketing-skills — semantic(0.39)+complementary+rare_topics+same_lang+similar_pop+shared_platform (73%)
  • ai-marketing-claude — semantic(0.44)+complementary+rare_topics+same_lang+shared_platform (64%)
  • sales — semantic(0.39)+complementary+rare_topics+same_lang+shared_platform (63%)
  • tavily-key-generator — semantic(0.19)+complementary+rare_topics+same_lang+similar_pop+shared_platform (61%)

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How this security grade is produced

Grades come from a rule-based scan built on the SlowMist agent-security taxonomy: 42 published rules, covering credential harvesting, data exfiltration, curl | sh installers and more. It is a first-layer scan, not a manual audit — we say so rather than overstate it.

The scale of the problem is documented independently: Liu et al. (2026), in a study of 31,132 agent skills, report that 26.1% contain security vulnerabilities. Our own full-catalog census is published as a citable open dataset.

Sources & who's responsible:

View on GitHub → Browse Agent Tool tools