personalization-subagent-pattern

Generates per-lead cold email personalization fields using parallel Claude Code Task sub-agents with an approval loop.

Updated May 28, 2025
One-click install
npx skills add https://github.com/meloShaya/insteltech --skill personalization-subagent-pattern-meloshaya
Or copy as Structured Prompt for Agent
Please help me install this Agent Skill.
Skill: personalization-subagent-pattern
Source: https://github.com/meloShaya/insteltech/tree/main/crm/library/skills/personalization-subagent-pattern
Command: npx skills add https://github.com/meloShaya/insteltech --skill personalization-subagent-pattern-meloshaya

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill includes references (resource) components.

What problem does it solve? Writing personalized cold email lines for hundreds of leads by hand is slow, and running a single prompt over a large list without review produces generic or wrong copy. This Skill defines a reusable approval-loop pattern that tunes a personalization prompt on small batches before scaling to the full lead list. ## Core Features & Use Cases - Approval loop before scale: Shows one sample personalization, then batches of 10, collecting user edits until two consecutive rounds pass with zero corrections, then locks the prompt. - Parallel Task sub-agent fan-out: Splits leads into batches of 10-20 and launches multiple Claude Code Task sub-agents (including A/B/C copy variants) that write JSON results to /tmp for merging by lead_id. - Schema and quality guardrails: Enforces a strict output schema (situation_line, value_line, cta_soft), banned-word rules, no-fabrication rules, skip handling for thin data, and spot-check guidance before upload to Smartlead or Instantly. - Use Case: Given 100 enriched leads with company descriptions, tune the prompt on 20 leads across two approved rounds, then fan out 10 parallel sub-agents to generate three personalization variants per lead and map them to custom variables in your sending platform. ## Quick Start Ask Claude to personalize this batch of leads using the personalization sub-agent pattern, starting with one sample lead for approval before fanning out.

Frequently Asked Questions about personalization-subagent-pattern

High-intent search queries and answers about installing and using this skill.

FAQPage Schema
How do I personalize cold emails for hundreds of leads at scale?

Split the lead list into batches of 10-20 and launch parallel Claude Code Task sub-agents, each generating situation_line, value_line, and cta_soft fields per lead. Tune the prompt on small approved batches first, then fan out and merge results by lead_id.

How do I run parallel personalization agents without an Anthropic API key?

Use the Claude Code Task tool to spawn sub-agents directly inside Claude Code, with no SDK calls or external API keys. Multiple Task calls in one message run in parallel, so 100 leads finish in roughly the time of 10.

What batch size should I use for personalization sub-agents?

Use 10-20 leads per sub-agent as the default. Larger batches reduce agent count but degrade quality as the agent loses context, while smaller batches improve quality at higher parent context cost.

When should I not use sub-agent fan-out for personalization?

Skip fan-out for batches under 10-20 leads, where inline personalization in the main conversation is sufficient. Also avoid it for static copy sent identically to every lead, since personalization fields would waste tokens.

Why do personalization sub-agents return malformed or skipped results?

Sub-agents can emit malformed JSON, skip leads with thin company descriptions, or refuse risky content. Validate every result against the output schema, retry missing lead_ids once with a strict prompt, and mark unpersonalizable leads as skipped.

How do I know when the personalization prompt is ready to scale?

The prompt is locked when the user gives zero edits across two consecutive rounds of 10 leads, or explicitly approves scaling. Save the tuned prompt, then launch the parallel fan-out on the remaining leads.