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 coleschaffer/copywritingskills-rmbc --skill media-buying-briefgit clone --depth 1 https://github.com/coleschaffer/copywritingskills-rmbcWrote 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/coleschaffer/copywritingskills-rmbc/media-buying-brief)<a href="https://agentmods.dev/skills/coleschaffer/copywritingskills-rmbc/media-buying-brief"><img src="https://agentmods.dev/badge/skills/coleschaffer/copywritingskills-rmbc/media-buying-brief/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/coleschaffer/copywritingskills-rmbc/media-buying-brief"><img src="https://agentmods.dev/badge/skills/coleschaffer/copywritingskills-rmbc/media-buying-brief.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 | $0.00032 | $0.01862 |
| Opus 5 | $0.00016 | $0.00931 |
| Sonnet 5 | $0.00006 | $0.00372 |
| Haiku 4.5 | $0.00003 | $0.00186 |
Grade A, and why
media-buying-brief 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 13d 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 — 193 lines — stays where its author put it; the contents beside it link to each section on GitHub.
media-buying-brief
Purpose
Generate a complete media buying brief — everything a media buyer needs to set up, launch, and optimize a paid campaign. This is the operational counterpart to the creative brief: while the creative brief tells the designer what to make, the media buying brief tells the buyer where to place it, who to target, how much to spend, and what success looks like. Grounded in RMBC principles — audience targeting reflects Research, ad structure reflects the Mechanism-to-CTA arc.
Inputs
| Input | Required | Description |
|---|---|---|
product_description |
Yes | What the product is, price point, margins if known |
target_audience |
Yes | Who the prospect is — demographics, behaviors, interests, purchase patterns |
monthly_budget |
Yes | Total monthly media spend in USD |
primary_platform |
Yes | One of: meta, youtube, native, tiktok |
campaign_goal |
Yes | One of: awareness, consideration, conversion |
aov |
No | Average order value — improves ROAS/CPA target accuracy |
existing_data |
No | Any past campaign data — winning audiences, CPAs, ROAS benchmarks |
Execution Protocol
Step 1 — Load Framework Context
Read rmbc-context/SKILL.md to load RMBC framework definitions. Media buying operationalizes the Research phase — audience targeting is Research translated into platform parameters. The testing framework mirrors the iterative approach RMBC applies to copy.
Step 2 — Define Audience Architecture
Build a layered targeting strategy:
| Layer | Purpose | Example |
|---|---|---|
| Core | Highest-intent audiences | Lookalike 1% from purchasers, retargeting site visitors |
| Expansion | Broader but still relevant | Interest stacks, lookalike 1-3%, engagement audiences |
| Prospecting | Cold, broad targeting | Broad/open targeting with creative doing the filtering |
For each layer, specify:
- Interest targets (specific names, not categories)
- Exclusions (existing customers, employees, irrelevant demographics)
- Lookalike sources and percentages (if applicable)
- Custom audience definitions (site visitors, email lists, video viewers)
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.
- 13d ago First seen · 193 lines · 32 tokens per session scan A ed8e99b4ea41
media-buying-brief is a skill published in the GitHub repository coleschaffer/copywritingskills-rmbc (30 stars, last pushed 5mo ago), licensed MIT. It adds 32 tokens to every session and 1,862 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 2026-08-30.
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