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 rampstackco/claude-skills --skill paid-media-strategygit clone --depth 1 https://github.com/rampstackco/claude-skillsWrote 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/rampstackco/claude-skills/paid-media-strategy)<a href="https://agentmods.dev/skills/rampstackco/claude-skills/paid-media-strategy"><img src="https://agentmods.dev/badge/skills/rampstackco/claude-skills/paid-media-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/rampstackco/claude-skills/paid-media-strategy"><img src="https://agentmods.dev/badge/skills/rampstackco/claude-skills/paid-media-strategy.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector pass
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 | $0.00142 | $0.04664 |
| Opus 5 | $0.00071 | $0.02332 |
| Sonnet 5 | $0.00028 | $0.00933 |
| Haiku 4.5 | $0.00014 | $0.00466 |
Grade A, and why
paid-media-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 8d 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 — 261 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Paid Media Strategy
A senior performance marketer's playbook for running paid media that produces real outcomes.
The default state of paid media is wasted spend. Most accounts have campaigns running because they always have, audiences targeting because the rep suggested it, bid strategies on auto because manual is hard, creative not refreshed because there is no system. The cost compounds. A 20% efficiency gain on a $500K-per-year account is $100K back to the business. A 50% gain on a $5M-per-year account is $2.5M.
This skill is the discipline that produces those gains. It assumes you have a paid media platform (Google Ads, Meta, LinkedIn, TikTok, or aggregators like Synter) connected. It assumes you have working analytics and conversion tracking. The hard part is the strategic discipline behind the spend, and that is what is here.
When to use this skill: any time you are designing a paid media plan, evaluating whether to scale or kill a campaign, allocating budget across channels, or auditing an existing account.
What this skill is for
This skill spans paid media strategy and operations. It does not cover ad creative production (use ads-creative-development), result interpretation in depth (use ads-performance-analytics), or platform-specific MCP tooling (consult each ad platform's official documentation for current MCP setup, auth, and example prompts).
The audience is a performance marketer (in-house or agency), a growth lead allocating spend across channels, or a founder making early paid budget decisions. The voice is tactical. There is no "evaluate every option yourself with no opinion." Paid media decisions have shape, and a senior practitioner can map a situation to a defensible plan in an afternoon.
Hypothesis discipline for paid spend
Most paid media failures start with a vague reason for spending. A real spend hypothesis has five parts: audience, offer, channel, outcome metric, and magnitude. Missing any of them and the campaign cannot be evaluated honestly.
What ships with it
7 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.
- references/ads-platform-comparison.md 7.1 KB
- references/audience-segmentation-patterns.md 6.6 KB
- references/bid-strategy-reference.md 6.3 KB
- references/budget-allocation-templates.md 5.6 KB
- references/campaign-type-reference.md 8.0 KB
- references/channel-decision-matrix.md 5.8 KB
- references/common-failures.md 8.4 KB
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.
- 8d ago First seen · 261 lines · 142 tokens per session scan A 2bb4597636c5
paid-media-strategy is a skill published in the GitHub repository rampstackco/claude-skills (838 stars, last pushed 4d ago), licensed MIT. It adds 142 tokens to every session and 4,664 once invoked, about $0.0007 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 2026-09-03.
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