Ivx Ams Outbound Engine

Working directory

cd ~/.cursor/skills/ams-outbound-engine
# Windows: cd $env:USERPROFILE\.cursor\skills\ams-outbound-engine

Cursor install notes

• Skill root: this folder (scripts + references live here).
• Vendor source: ~/.cursor/skills/_vendor/ai-marketing-skills/ (git pull to update).
• Telemetry is optional; skip telemetry/*.py unless you opt in.
• Run Python from this skill directory so relative paths resolve.
• Prefer python on Windows if python3 is missing.

Startup: Determine Mode

Ask the user:

1. Do you have an existing Instantly account with campaigns to audit, or are you starting from scratch?
2. Do you have an Instantly API key? (Required for audit mode.)

If API key provided → run scripts/instantly-audit.py to pull campaigns, account inventory, and warmup scores before proceeding.

Phase 2: Expert Panel Recursive Scoring

Target: 90/100. Non-negotiable. Iterate until reached.

Round Structure

Each round produces:

1. Score table — all 10 panelists, individual score (0-100), one-line rationale
2. Aggregate score — average of all 10
3. Top weaknesses — ranked list of what's holding the copy back
4. Changes made — specific edits addressing each weakness
5. Updated copy — full revised sequence after changes

Scoring Criteria (per panelist's lens — see references/expert-panel.md)

• Subject line curiosity / open rate potential
• First sentence pattern interrupt
• Body clarity and brevity
• CTA softness and specificity
• Sequence flow and follow-up logic
• Deliverability risk signals (spam words, link density)
• Personalization believability

Rules

• Scores must be brutally honest. No padding to 90 without earning it.
• If round score < 90: identify top 3 weaknesses, revise copy, run next round.
• If round score ≥ 90: finalize copy and proceed to deliverables.
• Show every round in the final doc — the iteration trail is part of the value.

Capacity Math Formula

Accounts ready (score ≥80, ≥14 days warmup) × 30 emails/day = conservative daily volume
Accounts ready × 50 emails/day = aggressive daily volume
Daily volume × 22 working days = monthly send capacity
Monthly sends × expected reply rate = expected replies
Expected replies × qualification rate = pipeline opportunities

Add-On Recommendations (mention but don't build)

• LinkedIn automation: HeyReach or similar for multi-channel sequences. Separate workflow.
• Lead enrichment: Clay or Apollo for personalization data before upload.
• Lead pipeline: Use scripts/lead-pipeline.py for Apollo → LeadMagic → Instantly automation.

Reference Files