outbound

outbound is a skill for Claude Code, Codex from LuuOW/meridian-mcp. It costs 38 tokens per session (2,199 once invoked), scanned A, original, MIT.

An outbound sales playbook for finding potential customers, contacting them by email, and managing the resulting sales pipeline.

In plain words
What is it for?
Use it to define an ideal customer profile, score leads, design cold-email sequences, handle replies, and connect outreach work with a customer database.
Why use it?
It gives you a structured way to decide who to contact, send relevant follow-ups, protect email delivery, and track whether outreach leads to revenue.

Skill for Claude CodeCodex

Written for no agent in particular: nothing here depends on one.

Good fit Use it to define an ideal customer profile, score leads, design cold-email sequences, handle replies, and connect outreach work with a customer database.

Compare 6 skills from other repositories ↓
Install with agentmods
npx agentmods add skills/luuow/meridian-mcp/outbound
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 LuuOW/meridian-mcp --skill outbound
Clone the repo
git clone --depth 1 https://github.com/LuuOW/meridian-mcp

Made for: Claude Code, Codex.

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 outbound

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

Your own site · 80×15
<a href="https://agentmods.dev/skills/luuow/meridian-mcp/outbound"><img src="https://agentmods.dev/badge/skills/luuow/meridian-mcp/outbound.svg" alt="Reviewed on agentmods" width="80" height="20"></a>
Per session 38 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 2,199 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 $0.00038 $0.02199
Opus 5 $0.00019 $0.01099
Sonnet 5 $0.00008 $0.00440
Haiku 4.5 $0.00004 $0.00220

Measured 9d ago against content hash 1f1bcac5a06b, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-09, from the pricing page.

Security

Grade A, and why

outbound 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 9d 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.

skills/outbound/SKILL.md · 240 lines

How it starts

The opening of the file, as written. The whole thing — 240 lines — stays where its author put it; the contents beside it link to each section on GitHub.

outbound

Covers the full outbound motion: ICP definition, lead sourcing, sequence design, deliverability, and CRM pipeline management. Built from lead-gen-engine patterns.

1) ICP (Ideal Customer Profile) definition

ICP = {
    "firmographic": {
        "company_size":   "10-200 employees",
        "industry":       ["SaaS", "eCommerce", "Agency"],
        "revenue_range":  "$1M-$50M ARR",
        "geography":      ["US", "CA", "UK", "AU"],
        "tech_stack":     ["Shopify", "HubSpot", "Salesforce"],  # technographic signals
    },
    "demographic": {
        "title":          ["Head of Marketing", "VP Growth", "Founder", "CMO"],
        "seniority":      ["Director", "VP", "C-Suite"],
        "department":     "Marketing or Growth",
    },
    "behavioural": {
        "intent_signals": ["hired growth role recently", "raised funding", "launched product"],
        "pain_signals":   ["low organic traffic", "high CAC", "content gaps"],
    },
    "negative":  {
        "exclude":        ["competitors", "agency clients", "students", "job seekers"],
    },
}

2) Lead scoring model

def score_lead(lead: dict) -> float:
    score = 0.0
    # Firmographic fit (0-40 pts)
    if lead.get("company_size") in range(10, 201):    score += 15
    if lead.get("industry") in ICP["firmographic"]["industry"]:  score += 15
    if lead.get("revenue"):                            score += 10
    # Role fit (0-30 pts)
    if any(t in lead.get("title","") for t in ICP["demographic"]["title"]):  score += 20
    if lead.get("seniority") in ICP["demographic"]["seniority"]:             score += 10
    # Intent signals (0-30 pts)
    if lead.get("recent_funding"):    score += 15
    if lead.get("recent_hire"):       score += 10
    if lead.get("tech_stack_match"):  score += 5
    return score  # > 60 = hot, 40-60 = warm, < 40 = cold

BUCKETS = {"hot": 60, "warm": 40, "cold": 0}

3) Cold email sequence structure

Sequence: 5-touch, 14-day window

Day 0  — Email 1: Hook + value prop (3 sentences max)
Day 2  — Email 2: Social proof / case study angle
Day 5  — Email 3: Pain-point reframe
Day 9  — Email 4: Objection pre-emption
Day 14 — Email 5: Breakup ("last email, no hard feelings")

Reply at any point → remove from sequence, route to human

Read the full file on GitHub · 240 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. 9d ago First seen · 240 lines · 38 tokens per session scan A 1f1bcac5a06b

Subscribe to this mod's changes

outbound is a skill published in the GitHub repository LuuOW/meridian-mcp (0 stars, last pushed yesterday), licensed MIT. It adds 38 tokens to every session and 2,199 once invoked, about $0.0002 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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