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 agentmods add skills/ad-superpowers/ad-superpowers-plugin/channel-selection-frameworknpx skills add Ad-Superpowers/ad-superpowers-plugin --skill channel-selection-frameworkgit clone --depth 1 https://github.com/Ad-Superpowers/ad-superpowers-pluginWrote 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/ad-superpowers/ad-superpowers-plugin/channel-selection-framework)<a href="https://agentmods.dev/skills/ad-superpowers/ad-superpowers-plugin/channel-selection-framework"><img src="https://agentmods.dev/badge/skills/ad-superpowers/ad-superpowers-plugin/channel-selection-framework.svg" alt="Measured on agentmods" 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 | $0.00095 | $0.04475 |
| Opus 5 | $0.00048 | $0.02237 |
| Sonnet 5 | $0.00019 | $0.00895 |
| Haiku 4.5 | $0.00010 | $0.00447 |
Grade A, and why
channel-selection-framework 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 4d 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.
How it starts
The opening of the file, as written. The whole thing — 432 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Channel Selection Framework for Advertising
Purpose
Enable agencies and advertisers to make data-driven decisions about which advertising channels to use for specific campaigns. Move from intuition-based channel selection to systematic, objective-matched decisions.
When to Use This Skill
Invoke when user mentions:
- Channel selection: "Which platform should I use?"
- Platform comparison: "Meta vs Google Ads"
- Media mix: "How should I split budget across channels?"
- New campaign planning: "Starting a new campaign, where should I advertise?"
- Channel fit: "Is TikTok right for my audience?"
- Budget decisions: "How much do I need for LinkedIn?"
- Funnel stage: "Best platform for awareness/conversion?"
Part 1: Channel Selection Decision Tree
Quick Decision Framework
START: What is your PRIMARY objective?
│
├─► AWARENESS (Reach, Brand Recognition)
│ │
│ ├─► Budget > €5,000/month?
│ │ ├─► YES: Meta + TikTok + YouTube
│ │ └─► NO: Meta (best reach per €)
│ │
│ └─► Target Audience?
│ ├─► 18-34: TikTok primary, Meta secondary
│ ├─► 35-54: Meta primary, YouTube secondary
│ └─► 55+: Meta primary, Google Display secondary
│
├─► CONSIDERATION (Engagement, Traffic, Interest)
│ │
│ ├─► B2B or B2C?
│ │ ├─► B2B: LinkedIn + Google Search + Meta
│ │ └─► B2C: Meta + TikTok + Google Display
│ │
│ └─► Content Type?
│ ├─► Video: TikTok, YouTube, Meta
│ ├─► Written: LinkedIn, Google
│ └─► Visual: Meta, Pinterest
│
├─► CONVERSION (Sales, Leads, Signups)
│ │
│ ├─► Product Type?
│ │ ├─► E-commerce: Google Shopping + Meta + TikTok Shop
│ │ ├─► SaaS/B2B: Google Search + LinkedIn + Meta
│ │ ├─► Local Service: Google Local + Meta
│ │ └─► App: Meta App + TikTok + Google App
│ │
│ └─► Sales Cycle?
│ ├─► Impulse (<24h): Google Search + Meta retargeting
│ ├─► Short (1-7 days): Meta + Google
│ ├─► Medium (7-30 days): Full multi-touch
│ └─► Long (30+ days): LinkedIn + Content + Retargeting
│
└─► FULL FUNNEL (Brand + Performance)
│
└─► Budget Level?
├─► <€5k/mo: Pick ONE platform, full funnel within it
├─► €5-15k/mo: 2 platforms, complementary roles
├─► €15-50k/mo: 3 platforms, defined roles per funnel stage
└─► €50k+/mo: 4+ platforms, sophisticated attribution
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.
- 4d ago First seen · 432 lines · 95 tokens per session scan A f63ab25f8315
channel-selection-framework is a skill published in the GitHub repository Ad-Superpowers/ad-superpowers-plugin (5 stars, last pushed 6d ago), licensed MIT. It adds 95 tokens to every session and 4,475 once invoked, about $0.0005 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.
Other skills, from other repositories
analytics
Growth analytics authority — GA4 event tracking, conversion funnels, attribution models, cohort analysis, A/B testing, Supabase analytics queries, and revenue reporting patterns.
attribution-scope
GA4 has three distinct attribution scopes. Using the wrong scope gives misleading results. Choose based on the question you are answering.
bot-traffic-detection
Identify and exclude bot, scraper, and spam sessions from GA4 data.
traffic-diagnosis
Systematically diagnose why traffic changed — spike, drop, or shift in mix. Follow these steps in order. Each step narrows the hypothesis.
analytics
Use when instrumenting product or web analytics — GA4/PostHog SDK wiring, event taxonomy, funnels, double-counted events, consent gating, PII scrubbing. NOT charting that data (that is dashboard), NOT choosing which metrics matter (that is kpi-framework), NOT experiment math (that is ab-testing), NOT cookie-policy…
_mureo-shared
Skill "_mureo-shared" from logly/mureo, covering mureo shared patterns, installation, setup, claude code (recommended) and manual configuration.