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drivenautoplex1

ICP Modeler

by drivenautoplex1 · GitHub ↗ · v1.0.2 · MIT-0
cross-platform ✓ Security Clean
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Install in OpenClaw
/install icp-modeler
Description
Generate research-backed Ideal Customer Profiles (ICPs) for mortgage and real estate products. Returns full buyer personas, Meta/Google ad targeting paramete...
README (SKILL.md)

ICP Modeler Skill

Know exactly who you're talking to before you write a single word of copy. The ICP Modeler generates battle-tested buyer profiles for mortgage and real estate products — with specific ad targeting parameters, trigger phrases, pain points, and platform routing built in.

Free vs Premium

Free tier (no API key needed):

  • --demo — full crypto-mortgage ICP profile, zero API calls, shows complete output format
  • --list — see all 5 available ICPs
  • --product \x3Cname> — display any pre-built ICP profile (works offline)
  • --output json — export any ICP as structured JSON for your own workflows

Premium tier (ANTHROPIC_API_KEY):

  • --generate-content "3 facebook posts" — LLM writes content specifically tuned to the ICP's triggers, tone, and platform presence
  • --generate-content "30s video script" — ICP-targeted video script
  • --generate-content "email subject lines" — subject lines optimized for this buyer's psychology
  • Unlimited content generation via Claude Haiku (~$0.001 per call)

The pre-built profiles alone are worth installing — most "targeting" is just age/income. This gives you psychology.

What this skill does

For each product, generates a complete buyer intelligence package:

  1. Full buyer persona — age, income, location, occupation, pain points, dream outcome
  2. Trigger phrases — exact words and phrases this buyer types into Google and says out loud
  3. Content tone guide — how to speak to this buyer without triggering skepticism
  4. Platform routing — where this ICP actually hangs out (X, Reddit, LinkedIn, Facebook groups)
  5. Meta ad targeting — ages, interests, placements, custom audience strategy
  6. Google Ads targeting — keywords, match types, negative keywords, audience layers

Available ICPs

Product Headline
crypto-mortgage The Crypto Holder Who Won't Sell
credit-repair The Almost-Ready Buyer
va-loan The Veteran Who Doesn't Know What They Have
realtor-partner The Agent Who Needs a Lender They Can Trust
first-time-buyer The Overwhelmed First-Timer

Aliases work: crypto, va, credit, realtor, first-time

Usage

# See the crypto-mortgage ICP with zero setup
python3 icp_modeler.py --demo

# List all available ICPs
python3 icp_modeler.py --list

# Pull a full ICP profile
python3 icp_modeler.py --product "crypto mortgage"
python3 icp_modeler.py --product va-loan
python3 icp_modeler.py --product first-time-buyer

# Export as JSON (pipe into other tools)
python3 icp_modeler.py --product credit-repair --output json

# Generate ICP-tuned content (requires ANTHROPIC_API_KEY)
python3 icp_modeler.py --product crypto --generate-content "3 facebook posts"
python3 icp_modeler.py --product va-loan --generate-content "30s video script"
python3 icp_modeler.py --product first-time --generate-content "email subject lines"

# Version
python3 icp_modeler.py --version

Example output (crypto-mortgage ICP)

━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━
ICP: Crypto-Backed Mortgage (Fannie Mae / Coinbase / Better)
     "The Crypto Holder Who Won't Sell"
━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━

DEMOGRAPHICS
  age                  30-48
  income               $120K-$400K household
  location             Target metro, key submarkets and growth corridors
  occupation           Software engineer, finance, entrepreneur, executive

PAIN POINTS
  • Doesn't want to sell crypto and trigger $50K-$500K capital gains tax event
  • Doesn't qualify for traditional mortgage because crypto income isn't W2
  • Feels stuck — 'I have the wealth but can't access it for real estate'

TRIGGER PHRASES
  "don't sell your crypto to buy a house"
  "pledge crypto as collateral"
  "no capital gains event"
  "Fannie Mae crypto"

META AD TARGETING
  Ages:      28-50
  Interests: Cryptocurrency, Bitcoin, Ethereum, XRP, DeFi
  Placement: Facebook Feed, Instagram Feed, Instagram Stories
  Income:    Top 25%

Connecting to other skills

Pipe ICP JSON into the content scorer and content calendar:

# Generate ICP → score the content it suggests → build a calendar
python3 icp_modeler.py --product crypto --output json > icp.json
python3 icp_modeler.py --product crypto --generate-content "5 linkedin posts" | \
  python3 ../content-scorer/score_content.py --stdin

Multi-vertical use

The ICP framework applies to:

  • Any mortgage vertical (FHA, VA, USDA, jumbo, crypto-backed, HELOC)
  • Real estate agents targeting specific buyer profiles
  • Credit repair services targeting pre-approval candidates
  • Financial services with segmented buyer journeys
  • Coaching/consulting with defined client personas

Extend by adding your own ICP dict to the ICPS dictionary in icp_modeler.py.

Usage Guidance
This skill appears coherent: the free features work offline and only LLM-powered content needs an ANTHROPIC_API_KEY. Before installing, check two things: (1) confirm how icp_modeler.py makes LLM calls — SKILL.md references generate.py but that file is not included, so ensure the included script runs without missing dependencies or external helper files; (2) installing the 'anthropic' package will enable network calls to Anthropic — only provide an API key if you accept that network usage and billing. Also: be mindful when using generated ad targeting — avoid uploading personally identifiable information to ad platforms and ensure compliance with advertising rules and privacy laws.
Capability Analysis
Type: OpenClaw Skill Name: icp-modeler Version: 1.0.2 The icp-modeler skill is a marketing tool designed to generate research-backed buyer personas for the real estate and mortgage industries. The Python script (icp_modeler.py) contains hardcoded data for several profiles and uses an external LLM wrapper (generate.py) for content generation, which is standard for this framework. No evidence of data exfiltration, malicious execution, or prompt injection was found; the code logic is transparent and aligns with the stated purpose in SKILL.md.
Capability Assessment
Purpose & Capability
Name/description (ICP generation for mortgage/real-estate) align with the code and SKILL.md: a Python CLI with pre-built ICPs and optional LLM content generation. Requesting an ANTHROPIC_API_KEY and installing the 'anthropic' package is consistent with the premium LLM features described.
Instruction Scope
SKILL.md instructs only local CLI operations (--demo, --list, --product) and optional LLM calls for content generation. The instructions do not request unrelated files, system secrets, or odd endpoints. Note: SKILL.md mentions a generate.py LLM backend (local MLX → Haiku fallback) but generate.py is not present in the file manifest; verify how icp_modeler.py invokes the Anthropic API and whether additional runtime files are required.
Install Mechanism
Install spec pulls in an 'anthropic' package (public registry style). This is proportionate for LLM-based content generation. Using a public package is a moderate-risk install mechanism but expected for this functionality — no obscure download URLs or archive extraction is present.
Credentials
Only ANTHROPIC_API_KEY is required and is declared as the primary credential. That matches the documented premium features. No unrelated credentials or filesystem config paths are requested.
Persistence & Privilege
Skill is not always-enabled and is user-invocable. It does not request elevated or persistent system privileges in the provided manifest. Nothing indicates modification of other skills or system-wide configuration.
How to Use
  1. Make sure OpenClaw is installed (local or Docker)
  2. Run the install command in chat: /install icp-modeler
  3. After installation, invoke the skill by name or use /icp-modeler
  4. Provide required inputs per the skill's parameter spec and get structured output
Version History
v1.0.2
icp-modeler v1.0.2 - Added main Python skill file: icp_modeler.py - Added quickstart and Q&A documentation: qa-skill.md - Updated SKILL.md version and metadata for this release
v1.1.0
- Author and homepage URLs updated to "drivenautoplex1". - Example ICPs and usage instructions remain, but DFW-specific locations in sample output are now generalized (e.g., "Target metro, key submarkets and growth corridors"). - Multi-vertical use description no longer positioned as DFW-specific. - Removed files: icp_modeler.py and qa-skill.md, indicating code and QA documentation are no longer included in this version.
v1.0.1
Minor updates
v1.0.0
- Initial release of icp-modeler: actionable, research-backed Ideal Customer Profile (ICP) generation for mortgage and real estate products. - Provides full buyer personas, pain points, trigger phrases, content tone guidelines, and precise ad targeting for Meta/Google. - Free features: demo ICP, list of all profiles, select and export any pre-built ICP (JSON supported). - Premium (with API key): AI-powered, tailored content creation (posts, video scripts, ad copy) aligned with each ICP's behavior and triggers. - Smooth integration with other content and marketing workflows; command-line friendly. - Focuses on practical targeting intelligence—no generic demographics.
Metadata
Slug icp-modeler
Version 1.0.2
License MIT-0
All-time Installs 0
Active Installs 0
Total Versions 4
Frequently Asked Questions

What is ICP Modeler?

Generate research-backed Ideal Customer Profiles (ICPs) for mortgage and real estate products. Returns full buyer personas, Meta/Google ad targeting paramete... It is an AI Agent Skill for Claude Code / OpenClaw, with 144 downloads so far.

How do I install ICP Modeler?

Run "/install icp-modeler" in the OpenClaw or Claude Code chat to install it in one step — no extra setup required.

Is ICP Modeler free?

Yes, ICP Modeler is completely free, licensed under MIT-0. You can download, install and use it at no cost.

Which platforms does ICP Modeler support?

ICP Modeler is cross-platform and runs anywhere OpenClaw / Claude Code is available (cross-platform).

Who created ICP Modeler?

It is built and maintained by drivenautoplex1 (@drivenautoplex1); the current version is v1.0.2.

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