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.
npx skills add AlexisMarasigan/coldoutboundskills --skill icp-onboardinggit clone --depth 1 https://github.com/AlexisMarasigan/coldoutboundskillsWrote 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.
[](https://agentmods.dev/skills/alexismarasigan/coldoutboundskills/icp-onboarding)<a href="https://agentmods.dev/skills/alexismarasigan/coldoutboundskills/icp-onboarding"><img src="https://agentmods.dev/badge/skills/alexismarasigan/coldoutboundskills/icp-onboarding/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.
<a href="https://agentmods.dev/skills/alexismarasigan/coldoutboundskills/icp-onboarding"><img src="https://agentmods.dev/badge/skills/alexismarasigan/coldoutboundskills/icp-onboarding.svg" alt="Reviewed on agentmods" width="80" height="20"></a>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.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5.1 | $0.00101 | $0.01947 |
| Opus 5 | $0.00051 | $0.00974 |
| Sonnet 5 | $0.00020 | $0.00389 |
| Haiku 4.5 | $0.00010 | $0.00195 |
Grade A, and why
icp-onboarding 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 11d 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.
This is a copy
100% identical to icp-onboarding — 0 lines differ, which has more behind it and is treated as the original. This page carries a canonical link to it rather than competing with it.
How it starts
The opening of the file, as written. The whole thing — 162 lines — stays where its author put it; the contents beside it link to each section on GitHub.
ICP Onboarding
Conversational intake. The user arrives with a business; this skill produces a client-profile.yaml every other skill in the repo consumes. Without it, downstream skills guess at targeting and write generic copy.
Why this exists
Most cold email fails because the sender didn't define the ICP tightly enough. "B2B SaaS founders" is not an ICP. "VP of RevOps at 50-500 person B2B SaaS companies in the US that raised Series B in the last 12 months" is an ICP — you can put it into Prospeo and get a list.
This skill forces that precision up front. It also separates hard filters (must match) from soft preferences (nice-to-have), because the #1 mistake beginners make is treating every ICP criterion as required, ending up with a list of 200 leads instead of 5,000.
Inputs
Either:
- Website URL of the user's business (skill will scrape + infer a lot)
- Plain description ("I sell X to Y") if no website
Outputs
A single file: ~/cold-email-ai-skills/profiles/<business-slug>/client-profile.yaml
Steps
1. Ask for the website URL FIRST (required)
Before any interview questions, ask:
"What's the website of the business you're running cold email for?"
If the user provides a URL:
npx tsx scripts/scrape-website.ts --url=https://example.com --out=/tmp/scrape.json
Then READ the scraped JSON and immediately produce a one-paragraph summary for the user:
"Based on your website, here's what I understand about your business:
sells <product/service in one sentence> to <who they sell to, based on case studies + homepage>. Their core value proposition appears to be . Notable social proof: <logos, metrics, awards>. Pricing signal: <free tier / self-serve / enterprise / unclear>.
Proposed ICP starting point: <titles + industries + size inferred from case studies>.
Does that sound right? Any corrections before I start the interview?"
This summary is NOT the final ICP — it's the anchor. The user's corrections here save 5+ minutes in the interview.
What ships with it
2 files beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.
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.
- 11d ago First seen · 162 lines · 101 tokens per session scan A 3812127b620e
icp-onboarding is a skill published in the GitHub repository AlexisMarasigan/coldoutboundskills (4 stars, last pushed 4mo ago), licensed MIT. It adds 101 tokens to every session and 1,947 once invoked, about $0.0005 per session on Opus 5. A static security scan graded it A with 0 findings. It is 100% identical to icp-onboarding, differing in 0 lines, and is treated as a copy.
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