| name | auto-research-public |
| description | Autonomous cold email campaign launcher. Takes one target company domain, scrapes their website, generates an ICP with Claude, pulls matching leads via Prospeo, enriches emails + company descriptions, personalizes each lead with parallel Claude Code Task sub-agents (A/B/C variants), and uploads as a live Smartlead campaign. Uses local JSON files for state (no database required). Use for automated daily campaign launches after you have an initial `client-profile.yaml` from /icp-onboarding. Triggers on "auto-research", "launch an automated campaign", "daily campaign", "run the research loop". |
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:
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:
{
"job_titles": ["VP Marketing", "Head of Marketing", ...],
"seniorities": ["Vice President", "Head", "Director"],
"industries": ["Software Development", "Financial Services"],
"company_size_min": 50,
"company_size_max": 500,
"countries": ["US"],
"excluded_industries": ["Religious Institutions", "Government Administration"]
}
Claude MUST use exact Prospeo industry names from ~/cold-email-ai-skills/skills/icp-onboarding/references/prospeo-industries.md.
Phase 3: Prospeo search
npx tsx scripts/phase-prospeo.ts --filters-file=/tmp/auto/filters.json --max-leads=1000 --out=/tmp/auto/leads.json
Output: JSON with leads array. Each lead has: first_name, last_name, email (may be empty), linkedin_url, job_title, company_name, company_domain, company_industry, company_headcount, company_description.
Phase 4: Email waterfall + description enrichment
npx tsx scripts/phase-enrich.ts --leads-file=/tmp/auto/leads.json --out=/tmp/auto/enriched.json
The script:
- Checks each lead for email; if missing, hits Prospeo's
enrich-person endpoint
- If company_description is thin (<50 chars), scrapes company_domain homepage
- Runs MillionVerifier on every candidate email
- Writes enriched leads (only those with valid email) to output
Expect hit rates:
- Retail/SMB: ~99% email found
- B2B tech: ~65-80%
- Healthcare/public sector: ~25-40%
- MV rejection: ~20-30% of found emails
Phase 5: Copy writing (Claude)
Claude generates 3 copy variants (A, B, C) and writes to /tmp/auto/variants.json:
[
{
"variant": "A",
"subject": "<concrete, specific, <60 chars>",
"angle": "<pain observation>",
"body_template": "Hi {{first_name}},\n\n{{situation_line_a}}\n\n{{value_line_a}}\n\n{{cta_line_a}}\n\n%signature%\n\nP.S. If this isn't relevant, just let me know and I won't reach out again."
},
{
"variant": "B",
"subject": "<different angle>",
"angle": "<compliment + transition>",
"body_template": "..."
},
{
"variant": "C",
"subject": "<third angle>",
"angle": "<question>",
"body_template": "..."
}
Rules Claude MUST follow (run /spam-word-checker on output):
- No em dashes (—). Use commas or periods.
- No "leverage", "synergy", "solutions", "world-class", "cutting-edge".
- Body: 50-90 words max.
- Subject: under 60 chars, specific, no clickbait.
- End with
%signature% on its own line.
Phase 6: Personalization via Task sub-agents
Claude fans out to parallel Task sub-agents (one per variant × batch of 20-30 leads). See /personalization-subagent-pattern for the full pattern.
Per lead, each sub-agent writes to /tmp/auto/personalization-<batch>-variant-<X>.json:
[
{
"lead_id": "...",
"situation_line": "One sentence about the company.",
"value_line": "One sentence connecting to our offer.",
"cta_soft": "One soft ask sentence."
}
]
After all sub-agents finish, Claude merges by lead_id into /tmp/auto/personalized.json. Each lead now has 9 personalization fields.
Phase 7: Upload to Smartlead
npx tsx scripts/phase-upload.ts \
--leads-file=/tmp/auto/personalized.json \
--variants-file=/tmp/auto/variants.json \
--domain=<target.com> \
--inboxes-tag=active \
--inbox-count=10 \
--activate
This script:
- Creates a new Smartlead campaign named
[AUTO] <date> <target> Auto
- Saves the 3-variant sequence with campaign-ID-scoped custom vars (
{{situation_line_a_{campaign_id}}})
- Selects N inboxes tagged "active" from Smartlead (LRU — least recently used first)
- Uploads leads in batches of 100 with custom fields mapped to their personalization
- Sets schedule (Mon-Fri 8am-5pm EST) and settings (tracking off, stop on reply)
- Activates the campaign
Outputs: { campaignId, inboxCount, leadsUploaded } to stdout.
Phase 8: Save experiment state (local JSON)
Write to ~/cold-email-ai-skills/profiles/<slug>/experiments/<YYYY-MM-DD>-<target>.json:
{
"date": "2026-04-17",
"target_domain": "example.com",
"smartlead_campaign_id": 123456,
"inboxes_assigned": [...],
"icp_filters": {...},
"variants": [...],
"lead_count_uploaded": 347,
"launched_at": "2026-04-17T14:23:00Z",
"status": "launched"
}
This is your experiment log. /experiment-design reads from here to compare runs. /positive-reply-scoring writes results back to this file after 21 days.
Running the full loop
To run all 8 phases in one command (with Claude orchestrating):
/auto-research-public --domain=<target.com>
Claude Code will execute each phase in order, pausing before phase 5 (copy) and phase 7 (upload) so you can review.
Daily / scheduled runs
Once comfortable, wrap it in a cron or use Claude Code's /loop skill to run daily:
/loop 1d /auto-research-public --domain=$(cat /tmp/auto/next-target.txt)
You need a way to pick the next target each day. Options:
- Maintain a
targets.txt list and pop one per day
- Let Claude pick based on TAM research (see
/GEX:Full-TAM-Waterfall for inspiration)
- Rotate through a list of competitors/lookalikes
State files (local JSON, no database)
Everything the skill needs lives under ~/cold-email-ai-skills/profiles/<slug>/:
profiles/
<business-slug>/
client-profile.yaml # from /icp-onboarding
lead-magnets.md # from /lead-magnet-brainstorm
experiments/
2026-04-16-targetco.json # per-campaign experiment log
2026-04-17-othertarget.json
scores/
123456-2026-05-07.json # from /positive-reply-scoring
Inbox assignment (no Supabase)
The GEX v2 uses a Supabase table auto_research_inbox_assignments to track which inboxes are assigned to which campaigns (to spread load). This public version:
- Queries Smartlead for inboxes tagged "active"
- Pulls each inbox's
daily_sent_count as a proxy for "how recently used"
- Sorts ascending, picks the first N (least-sent-today = least recently used)
- Records the assignment in the local experiment JSON (not a database)
Works for <1000 inboxes. If you scale beyond that, migrate to a real DB.
Common issues
- Prospeo INVALID_FILTERS — Usually "industry name not in the 256 list." Check
/icp-onboarding references/prospeo-industries.md for exact matches.
- Low email hit rate — If <30%, your list is targeting hard-to-find people (niche titles, small companies). Widen ICP or accept the cost.
- Sub-agent personalization repetitive — If you see the same phrasing across leads, rerun that batch with a diversity prompt. See
/personalization-subagent-pattern references/failure-modes.md.
- Smartlead "inbox not allowed" on upload — Inbox is flagged/blocked. The script skips and continues.
- Campaign stuck at 0 sends — Check campaign schedule, inbox warmup status (via
/smartlead-inbox-manager list-health), and that leads actually uploaded.
Cost per run
Typical run (1 target, 1000 leads pulled):
- Prospeo search: ~40 pages × search = ~$0.20
- Prospeo enrich-person (email finding for ~500 leads missing email): ~$5
- MillionVerifier validation: ~$0.50
- Smartlead send cost: ~$0.001/email sent over time
- Claude Code Task sub-agents: (uses your Claude Code plan — no extra API spend)
Total: ~$6-10 per campaign to reach 300-500 valid emails.
Scripts
scripts/phase-scrape.ts — website scrapescripts/phase-prospeo.ts — Prospeo paginated searchscripts/phase-enrich.ts — email waterfall + description enrichment + MillionVerifierscripts/phase-upload.ts — Smartlead campaign creation + uploadscripts/_lib.ts — shared API helpers
References
references/orchestration-checklist.md — full step-by-step for running the loop manuallyreferences/icp-to-prospeo.md — how to translate client-profile.yaml into Prospeo filter JSONreferences/copy-variant-guide.md — how to write 3 distinct A/B/C variants
What to do next
Wait 21 days for the campaign to accumulate reply data, then run /positive-reply-scoring on the launched campaign.
Meanwhile: continue the weekly rhythm via /cold-email-weekly-rhythm. Every Monday, /email-deliverability-audit on the new campaign to catch infrastructure issues early.
Or wait: this skill IS the automation loop. Next action can be "run again tomorrow with a different target domain" or integrate with /schedule skill to run daily.
Related skills
/icp-onboarding — produces client-profile.yaml (required input)/lead-magnet-brainstorm — produces the offer/CTA this campaign asks about/personalization-subagent-pattern — the fan-out pattern used in phase 6/smartlead-inbox-manager — must run BEFORE so inboxes are tagged/warmed/positive-reply-scoring — run AFTER 21 days to score the campaign/experiment-design — how to plan which target to try next
