account-selection

account-selection is a skill for Claude Code from Frontal-so/outbound-skills. It costs 158 tokens per session (711 once invoked), scanned A, original, MIT.

An account-selection skill for building and prioritizing company lists for account-based marketing, a sales approach focused on chosen organizations.

In plain words
What is it for?
Use it to select accounts using company characteristics, technology clues, customer-history data, and similar-company comparisons, then score and stage them.
Why use it?
It gives teams a repeatable way to decide which companies fit their ideal customer profile and how much effort each deserves.

Skill for Claude Code

Written for Claude Code: installed under .claude/.

Good fit Use it to select accounts using company characteristics, technology clues, customer-history data, and similar-company comparisons, then score and stage them.

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Install with agentmods
npx agentmods add skills/frontal-so/outbound-skills/account-selection
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 Frontal-so/outbound-skills --skill account-selection
Clone the repo
git clone --depth 1 https://github.com/Frontal-so/outbound-skills

Made for: Claude Code.

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.

agentmods badge for account-selection

README.md
[![agentmods](https://agentmods.dev/badge/skills/frontal-so/outbound-skills/account-selection/github.svg)](https://agentmods.dev/skills/frontal-so/outbound-skills/account-selection)
Your own site
<a href="https://agentmods.dev/skills/frontal-so/outbound-skills/account-selection"><img src="https://agentmods.dev/badge/skills/frontal-so/outbound-skills/account-selection/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.

agentmods 80×15 button for account-selection

Your own site · 80×15
<a href="https://agentmods.dev/skills/frontal-so/outbound-skills/account-selection"><img src="https://agentmods.dev/badge/skills/frontal-so/outbound-skills/account-selection.svg" alt="Reviewed on agentmods" width="80" height="20"></a>
Per session 158 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 711 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.
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.

ModelPer sessionOnce invoked
Fable 5.1 $0.00158 $0.00711
Opus 5 $0.00079 $0.00356
Sonnet 5 $0.00032 $0.00142
Haiku 4.5 $0.00016 $0.00071

Measured 10d ago against content hash a3a45187ad78, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-10, from the pricing page.

Security

Grade A, and why

account-selection 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 10d ago.

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.

master-skills/list-building/.claude/skills/account-selection/SKILL.md · 67 lines

How it starts

The opening of the file, as written. The whole thing — 67 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Account Selection for ABM

You help users build, score, stage, and manage target account lists for ABM campaigns.

Reference

Read {SKILL_BASE}/resources/abm/account-selection-framework.md for the complete framework.

Revenue Reverse-Engineering Formula

Start with revenue targets, work backward through conversion benchmarks:

  • Identified → Aware: 55%
  • Aware → Interested: 32%
  • Interested → Considering: 18%
  • Example: $1M ARR target → ~3,367 accounts needed

4-Layer Account Selection Criteria

Layer What It Covers
1. Firmographic Fit Company size, revenue, industry, location, business model
2. Technographic Indicators Competitor usage, tech stack, recent changes
3. CRM Intelligence Closed-lost, lost to competitor, churned customers
4. Lookalike Modeling Built from best existing customers

ICP Scoring Model (0-100)

Tier Score Action
A 90-100 Tier 1 ABM (1:1 custom)
B 70-89 Tier 2 ABM (1:few)
C 50-69 Programmatic ABM
D <50 Exclude

Stage Progression Tracking

Track via LinkedIn engagement metrics and HubSpot workflows:

  • Identified: In target list, no engagement yet
  • Aware: Impressions served, some ad engagement
  • Interested: 5+ clicks OR 10+ engagements
  • Considering: Website visits, content downloads, demo interest

Tools

Clay, BuiltWith, Apollo, HubSpot, LinkedIn Campaign Manager, ZenABM/Fibbler

Examples

Example 1: "How many accounts do I need for my ABM campaign?" → Read account-selection-framework.md. Use revenue reverse-engineering formula with their targets and conversion benchmarks.

Example 2: "How do I tier my account list?" → Apply 4-layer selection criteria, score each account 0-100, assign to tiers A/B/C/D.

Example 3: "How do I track which accounts are progressing?" → Set up stage progression via LinkedIn Campaign Manager + ZenABM/Fibbler → HubSpot properties → automated alerts.

Read the full file on GitHub · 67 lines

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.

  1. 10d ago First seen · 67 lines · 158 tokens per session scan A a3a45187ad78

Subscribe to this mod's changes

account-selection is a skill published in the GitHub repository Frontal-so/outbound-skills (5 stars, last pushed 1mo ago), licensed MIT. It adds 158 tokens to every session and 711 once invoked, about $0.0008 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 2026-08-31.

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