What is auto-research-public?

An automated cold-email campaign launcher that turns one company website domain and a client profile into a Smartlead campaign. It researches the company, finds and checks matching contacts, creates personalised email variants, and uploads the campaign.

Use it to create outbound campaigns in Smartlead, with lead research, email validation, company descriptions, per-contact personalisation, and multiple subject and message variants.

It removes much of the manual work of researching a target, finding contacts, writing individual messages, checking addresses, and setting up a campaign.

auto-research-public — Skill for Claude Code and Codex by growthengine

Install

Getting it into your agent

One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.

Any agent

npx skills add growthenginenowoslawski/coldoutboundskills --skill auto-research-public

Clone the repo

git clone --depth 1 https://github.com/growthenginenowoslawski/coldoutboundskills

Made for: Claude Code, Codex.

Wrote this? Show the measurements

A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.

README.md

[![agentmods](https://agentmods.dev/badge/skills/growthenginenowoslawski/coldoutboundskills/auto-research-public/github.svg)](https://agentmods.dev/skills/growthenginenowoslawski/coldoutboundskills/auto-research-public)

Your own site

<a href="https://agentmods.dev/skills/growthenginenowoslawski/coldoutboundskills/auto-research-public"><img src="https://agentmods.dev/badge/skills/growthenginenowoslawski/coldoutboundskills/auto-research-public/github.svg" alt="Measured on agentmods" height="20"></a>

Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.

Your own site · 80×15

<a href="https://agentmods.dev/skills/growthenginenowoslawski/coldoutboundskills/auto-research-public"><img src="https://agentmods.dev/badge/skills/growthenginenowoslawski/coldoutboundskills/auto-research-public.svg" alt="Reviewed on agentmods" width="80" height="20"></a>

Per session 129 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.

When invoked 3,037 The whole file, excluding the scripts and references it only reads on demand.

Security scan A 0 findings. A grade says what 26 rules found in the file — not that it is safe. Third-party audits

NVIDIA SkillSpector warn 7 Sept 2026

SkillSpector: 4 findings, up to medium

These are SkillSpector’s own severities. On a checked sample its high-severity flags on skills were ~96% false positives — a documented command, a public API, a “never do X” rule — so we show them as a caution to read, not a verdict. Why →

medium MCP Rug Pull · line 39
npx commands without a version suffix (e.g. @1.0.0) create a rug-pull risk if the upstream server is compromised and publishes a malicious update.

Fix: Pin the version: npx @scope/[email protected]
medium MCP Rug Pull · line 71
npx commands without a version suffix (e.g. @1.0.0) create a rug-pull risk if the upstream server is compromised and publishes a malicious update.

Fix: Pin the version: npx @scope/[email protected]
medium MCP Rug Pull · line 79
npx commands without a version suffix (e.g. @1.0.0) create a rug-pull risk if the upstream server is compromised and publishes a malicious update.

Fix: Pin the version: npx @scope/[email protected]
medium MCP Rug Pull · line 150
npx commands without a version suffix (e.g. @1.0.0) create a rug-pull risk if the upstream server is compromised and publishes a malicious update.

Fix: Pin the version: npx @scope/[email protected]

How audits are shown

Origin original No closer match found in the catalogue.

Token cost

What it costs to keep this loaded

Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.

Model	Per session	Once invoked
Fable 5.1	$0.00129	$0.03037
Opus 5	$0.00064	$0.01519
Sonnet 5	$0.00026	$0.00607
Haiku 4.5	$0.00013	$0.00304

Measured 12d ago against content hash 548ec7410a01, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-12, from the pricing page.

Security

Grade A, and why

auto-research-public scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 12d ago.

The scan reads SKILL.md. This mod also ships 4 executable files (scripts/phase-enrich.ts, scripts/phase-prospeo.ts, scripts/phase-scrape.ts, …), listed below but not scanned — reading those needs a real analyzer, not pattern matching.

A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.

Nothing flagged

None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.

Origin

Copies of this mod

1 near-identical copy found in the catalogue:

auto-research-public — 100% identical, 0 lines differ

skills/auto-research-public/SKILL.md · 288 lines

How it starts

The opening of the file, as written. The whole thing — 288 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Auto Research (Public)

Automated end-to-end campaign launcher. Feed it one target company domain, get back a live Smartlead campaign with per-lead personalization — in about 20 minutes.

This is the beginner-friendly version of the GEX internal auto-research-v2. All state lives in local JSON files; no Supabase, no Trigger.dev.

What you get

Input: one target company domain + your client-profile.yaml
Output: a running Smartlead campaign with:
- 200-1,000 leads (depending on targeting tightness)
- Per-lead personalization: 9 custom variables (situation, value, CTA × 3 variants)
- A/B/C subject + body variants tested in parallel
- Campaign assigned to your available inboxes
- Schedule: Mon-Fri 8am-5pm your timezone

Prerequisites

Before running:

client-profile.yaml exists (run /icp-onboarding if not)
SMARTLEAD_API_KEY in env
PROSPEO_API_KEY in env
MILLIONVERIFIER_API_KEY in env (for email validation)
At least 20 Smartlead inboxes tagged "active" (run /smartlead-inbox-manager first)
At least 1 campaign template in Smartlead (or the script creates a fresh one)

The orchestration (Claude Code runs this)

Unlike the other skills, this skill orchestrates through the Claude Code conversation itself — Claude does the reasoning (ICP generation, copy writing, personalization), and phase scripts do the heavy API I/O. This is the pattern from the GEX v2 internal.

Phase 1: Scrape the target company

npx tsx scripts/phase-scrape.ts --domain=<target.com> --out=/tmp/auto/scrape.json

Output: JSON with domain + text content from homepage, /about, /product, /pricing, /customers.

Claude reads the output and writes a short analysis to /tmp/auto/company-analysis.md:

What the company does
Who their likely customers are
Social proof signals
Potential angles for outreach

Phase 2: Claude generates ICP filters

Reading /tmp/auto/scrape.json + ~/cold-email-ai-skills/profiles/<slug>/client-profile.yaml, Claude writes Prospeo filters to /tmp/auto/filters.json:

Read the full file on GitHub · 288 lines

Files

What ships with it

4 files beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.

Changes

What this file has done since we first saw it

Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.

12d ago First seen · 288 lines · 129 tokens per session scan A 548ec7410a01

Subscribe to this mod's changes

auto-research-public is a skill published in the GitHub repository growthenginenowoslawski/coldoutboundskills (702 stars, last pushed 25d ago), licensed MIT. It adds 129 tokens to every session and 3,037 once invoked, about $0.0006 per session on Opus 5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-30.

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