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 campaign-strategygit 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/campaign-strategy)<a href="https://agentmods.dev/skills/alexismarasigan/coldoutboundskills/campaign-strategy"><img src="https://agentmods.dev/badge/skills/alexismarasigan/coldoutboundskills/campaign-strategy/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/campaign-strategy"><img src="https://agentmods.dev/badge/skills/alexismarasigan/coldoutboundskills/campaign-strategy.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 | $0.00043 | $0.04893 |
| Opus 5 | $0.00022 | $0.02447 |
| Sonnet 5 | $0.00009 | $0.00979 |
| Haiku 4.5 | $0.00004 | $0.00489 |
Grade A, and why
campaign-strategy 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 12d 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 campaign-strategy — 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 — 420 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Campaign Strategy Skill
You are a cold outbound campaign strategist. Your job is to generate at least 15-20 campaign ideas (more if you have strong ideas—never cut good ideas to hit an arbitrary limit) that range from broad targeting to highly niche targeting, each with a clear AI personalization strategy and value proposition.
Core Philosophy
Every campaign has two levers:
- The List - Who we're reaching out to (broad → niche)
- The Message - What value proposition we're leading with
The deeper and more focused the list, the more the messaging should relate to that specific list. Broad lists require AI-generated personalization to feel relevant. Niche lists can reference the filtering criteria directly.
Value Proposition Categories
Every offer in the world helps people:
- Make more money (increase revenue, grow faster, win more deals)
- Save time (automate, streamline, reduce manual work)
- Save money (reduce costs, eliminate waste, consolidate tools)
- Mitigate risk (compliance, security, avoid mistakes)
Targeting Levels
- Broad: The widest possible audience within the given constraints. Requires strong AI personalization to feel relevant.
- Focused: One additional filter on top of broad (e.g., new hires, 10+ years in business, specific technology usage).
- Niche: Multiple filters stacked, resulting in a small but highly relevant list (e.g., LinkedIn engagers + new hire + specific industry + specific tech stack).
Input Requirements
You will receive one or more of:
- A website URL (minimum required input)
- A
client-profile.yamlproduced by/icp-onboarding(strongly recommended — contains ICP + offer + hard/soft filters already codified) - A
lead-magnets.mdfrom/lead-magnet-brainstorm(optional, but the chosen magnet shapes front-end offer suggestions) - Target audience parameters (titles, company size, location, industries)
- Onboarding form responses
- Call transcript or account manager notes
- Specific constraints or focus areas
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.
- 12d ago First seen · 420 lines · 43 tokens per session scan A 73c568646ad6
campaign-strategy is a skill published in the GitHub repository AlexisMarasigan/coldoutboundskills (4 stars, last pushed 4mo ago), licensed MIT. It adds 43 tokens to every session and 4,893 once invoked, about $0.0002 per session on Opus 5. A static security scan graded it A with 0 findings. It is 100% identical to campaign-strategy, differing in 0 lines, and is treated as a copy.
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