Abm 1 To Many

Organization

LeadMagic

abm-1-to-many

Runs programmatic 1-to-many ABM for 50-200+ accounts: automated personalization, scaled outbound, intent-based targeting, and lookalike expansion. Use when ABM coverage must grow without adding headcount or when the user wants automated account-based outreach. Triggers on: "1-to-many ABM", "programmatic ABM", "scaled ABM", "automated ABM".

Overview

Publisher	LeadMagic
Repository	`gtm-skills`
Skill name	`abm-1-to-many`
Stars	72
Forks	18
Bundled files	3
License	MIT
Links	Skill source Repository Homepage

Markdown instructions
A SKILL.md file the model loads on demand, so it only costs tokens when a request actually matches.
Works with any LLM
AI skills are plain Markdown, not provider-specific code, so this works with GPT, Claude, Gemini, Grok, or a local model.
3 bundled files
Scripts, templates, and references the model can read while it works. Files are read-only and never executed.
Open source
Published by LeadMagic on GitHub. Read the source before you install it.

Installation

Install the Abm 1 To Many AI skill in TypingMind to use it with any LLM, or drop it into another agent that reads SKILL.md.

Install in TypingMind

TypingMind installs a skill straight from its GitHub folder — it reads SKILL.md, bundles the resource files, and stores the result locally.

Open the app and go to Plugins → Skills.
Choose "Install from GitHub".
Paste the skill folder URL below and confirm.
https://github.com/LeadMagic/gtm-skills/tree/main/skills/abm/abm-1-to-many
Enable the skill in any chat where you want it available.

Plugins → Skills → Add skill → From GitHub URL, then paste the folder URL and press Continue.

Install in another agent

Any agent that reads the Agent Skills format can use this skill — copy the folder into that agent's skills directory.

Claude Code — .claude/skills

git clone --depth 1 https://github.com/LeadMagic/gtm-skills.git /tmp/gtm-skills
mkdir -p .claude/skills
cp -r /tmp/gtm-skills/skills/abm/abm-1-to-many .claude/skills/abm-1-to-many

Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Abm 1 To Many in any TypingMind chat and the model takes it from there. Its name and description sit in the system prompt, and the moment a request matches, the model loads the full instructions itself — you never invoke it by hand, and it costs no tokens until it is actually used.

The model loads Abm 1 To Many on its own as soon as a request matches it.

Works with any AI model

AI skills are plain Markdown instructions rather than provider-specific code, so Abm 1 To Many is not tied to the model it was written for. Install it once in TypingMind and use it with GPT-5, Claude, Gemini, Grok, DeepSeek, Mistral, Llama, or a local model you run yourself — all on your own API keys.

Loaded only when it is needed
The system prompt carries just the name and description. The instructions are fetched on the first matching request, so an idle skill costs nothing.
Switch models mid-chat
Because the skill is instructions rather than code, changing model does not break it — the next model reads the same SKILL.md.

Skill instructions

This is the SKILL.md content the model loads. Read it before installing — a skill is instructions your model will follow.

ABM 1-to-Many (Programmatic)

Overview

Programmatic ABM for 50-200+ accounts using automation, lookalike modeling, and scaled personalization. This tier uses the same methodology as 1-to-1 and 1-to-few but replaces manual effort with AI and workflow automation.

Authoritative Foundations

TOPO (now Gartner) — Programmatic ABM — Treat 1:many as automated personalization by segment: shared messaging, intent-triggered plays, and account-level measurement.
Clay — Waterfall enrichment — Waterfall enrichment, Claygent research, and table-based automation for building and refreshing large account lists.
ITSMA — Account-Based Marketing — Tier-based ABM (1:1 / 1:few / 1:many); measure pipeline from target accounts, not lead volume.

When to Use

"Scale ABM to more accounts"
"Programmatic ABM setup"
"Automated account-based outreach"
"Expand ABM coverage without headcount"

Step-by-Step Process

Phase 1: Lookalike Expansion

Start from Tier 1-2 winners and expand:

ICP lookalike: Find accounts matching your top 10% win profile
Intent lookalike: Accounts showing similar buying signals to closed-won
Engagement lookalike: Accounts engaging with content the way winners did pre-opportunity
Trigger lookalike: Accounts with same triggers (funding, hiring, tech change)

Phase 2: Automated Account Intelligence

Use enrichment and AI to auto-build briefs:

Clay workflow: pull firmographics, technographics, news, signals
AI summarizes: company snapshot, pain hypothesis, relevant proof points
Auto-prioritize: score accounts 0-100 and assign to SDR queues

Phase 3: Scaled Personalization

Dynamic landing pages: URL params personalize hero/headline by industry/company
Tokenized email sequences: Merge fields beyond first name — industry, tech stack, signal
Automated LinkedIn: AI drafts personalized connection notes and DMs
Retargeting: Account-based ad audiences on LinkedIn by company name or domain

Phase 4: Automated Cadence Orchestration

SDR assigned accounts per round (rotating to prevent burnout)
Automated task creation in CRM per account
AI drafts first outreach; SDR reviews and sends
AI handles replies (OOO, not interested, wrong person); SDR handles positive replies

Phase 5: Feedback Loop

Weekly review: which accounts engaged, which didn't
Kill accounts after 8 touches with no reply
Feed winners back into lookalike model
Continuously refine ICP based on engagement patterns

Output Format

Programmatic ABM plan with: lookalike criteria, enrichment workflow, personalization templates, SDR routing rules, and optimization framework.

Quality Check

Before delivering, verify:

All required sections are complete
Output matches the user's stated need
Named frameworks are cited for key recommendations
No vague claims — every recommendation has a specific action
Deliverable is ready for operational use, not just conceptual

Common Pitfalls

Treating ABM as a marketing-only initiative. ABM requires tight sales alignment. Without BDRs assigned to specific accounts and shared account briefs, marketing produces content nobody uses. Fix: weekly ABM standups with marketing + BDRs + AEs.
One-size-fits-all tiering. Applying the same playbook to Tier 1 and Tier 3 accounts. Fix: Tier 1 gets custom content and executive engagement; Tier 3 gets automated personalization.
Measuring ABM on MQLs. ABM success is pipeline from target accounts, not lead volume. Fix: track coverage %, engagement depth, pipeline created, and win rate by tier.

Execution Artifacts

references/framework-notes.md — named frameworks, citation anchors, and operating assumptions
templates/output-template.md — copy-paste deliverable structure for the user
scripts/check-output.py — local checklist validator for required sections This skill includes lightweight artifacts the agent can load on demand: Use the artifacts when the user asks for an implementation-ready deliverable, a repeatable workflow, or a quality check rather than generic advice.

Implementation Depth

Use this section when the user asks for a finished asset, not a high-level explanation.

Diagnostic Questions

What is the primary motion: founder-led, sales-led, product-led, partner-led, or lifecycle-led?
Which ICP tier is the output for: small business, mid-market, enterprise, or mixed?
What proof is available today: customer stories, usage data, third-party validation, screenshots, or none?
What system will execute the work: CRM, sequencer, warehouse, support desk, product analytics, or manual workflow?
What decision will the user make from this output: launch, prioritize, route, rewrite, score, coach, or measure?

Framework Application

Map the recommendation explicitly to the named frameworks in this skill:

TOPO Programmatic ABM: apply only the part that directly improves the requested deliverable.
Clay Automation Patterns: apply only the part that directly improves the requested deliverable.
ITSMA — Account-Based Marketing: apply only the part that directly improves the requested deliverable.

Deliverable Standard

A strong output from this skill includes:

A crisp diagnosis of the current situation
A recommended path with tradeoffs, not a generic list
A concrete artifact the user can use immediately: table, script, checklist, scorecard, sequence, dashboard spec, or implementation plan
A measurement plan with leading and lagging indicators
Risks and edge cases called out before execution

Adaptation Rules

For small business: reduce complexity, shorten time-to-value, and prioritize owner/operator clarity.
For mid-market: include workflow ownership, handoffs, integrations, and enablement assets.
For enterprise: include governance, risk, procurement, stakeholder mapping, and proof requirements.

Related Skills

clay-automation, ai-sdr-setup, list-building, signal-scoring, icp-scoring

Bundled files

The model reads these on demand while the skill is loaded. They are exposed as readable files and are never executed.

Frequently asked questions

What does the Abm 1 To Many AI skill do?

Why use Abm 1 To Many on TypingMind?

Because you install it once and use it with any model. Abm 1 To Many is plain Markdown rather than provider-specific code, so the same skill runs on GPT-5, Claude, Gemini, Grok, or a local model — and you can switch model mid-chat without it breaking. TypingMind runs on your own API keys, so you pay providers directly instead of a per-seat subscription, and your skills and chats stay in your own storage.

How do I install Abm 1 To Many in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/LeadMagic/gtm-skills/tree/main/skills/abm/abm-1-to-many. TypingMind reads its SKILL.md and bundles its files and installs it as a skill you can enable per chat.

Which AI models can use Abm 1 To Many?

Any model you connect in TypingMind. AI skills are plain Markdown instructions rather than provider-specific code, so GPT, Claude, Gemini, Grok, and local models can all load this skill when a request matches it.

How many AI models can I use with Abm 1 To Many?

As many as you like. As long as a model supports skills, you can use Abm 1 To Many with it — GPT, Claude, Gemini, Grok, DeepSeek, Mistral, Llama and more — all on TypingMind with your own API keys.

Is the Abm 1 To Many AI skill free?

Yes. It is published on GitHub by LeadMagic under the MIT license. You only pay your own AI provider for the tokens you use.

What are AI skills?

An AI skill is a reusable instruction bundle that teaches an AI model how to do one specific task. It follows the open Agent Skills format: a SKILL.md file with a name and description, plus any scripts, templates or reference files the model may need. The model reads the instructions only when your request matches the skill, so an installed skill costs nothing until it is used.

How are AI skills different from plugins or MCP servers?

A plugin or MCP server gives a model new tools to call — code that runs somewhere and returns a result. An AI skill gives the model knowledge and process instead: how to approach a task, which steps to follow, what good output looks like. Skills are plain Markdown, so they need no server, no API key and no runtime, and they work with any model.

View all

Openai Docs

openai

OrganizationPopular

Use for Codex models/pricing, scheduled tasks, skills, settings, setup, troubleshooting, customization, automations, and self-knowledge—including 'you,' 'your,' 'this app,' or 'this coding agent' when…

Caveman Explore

Read-only repository explorer for cold-start orientation, broad cross-file localization, or when a direct search failed. Skip it when the exact file or symbol is already named. Returns path:line…

Delegate Work

Delegate user-requested work to an existing Paperclip agent, with a durable task reference and clear execution expectations.

Html Ppt Zhangzara Vellum

nexu-io

OrganizationPopular

A humanities lecture: how Renaissance linear perspective reshaped early cartography — sources, argument, and evidence. Built as a decision-grade academic research deck for faculty, graduate seminar.

Overview

Installation

Install in TypingMind

Install in another agent

Use it in TypingMind

Works with any AI model

Skill instructions

ABM 1-to-Many (Programmatic)

Overview

Authoritative Foundations

When to Use

Step-by-Step Process

Phase 1: Lookalike Expansion

Phase 2: Automated Account Intelligence

Phase 3: Scaled Personalization

Phase 4: Automated Cadence Orchestration

Phase 5: Feedback Loop

Output Format

Quality Check

Common Pitfalls

Execution Artifacts

Implementation Depth

Diagnostic Questions

Framework Application

Deliverable Standard

Adaptation Rules

Related Skills

Bundled files

Frequently asked questions

Related AI Skills

Set up your own AI workspace now