paid-advertising

paid-advertising is a skill for Claude Code from cbrock84/headcount. It costs 78 tokens per session (789 once invoked), scanned A, original, MIT.

A guide for planning, running, and reviewing paid advertising on search engines, social networks, and display networks. It covers campaign structure, audiences, adverts, bids, budgets, and conversion tracking.

In plain words
What is it for?
Use it to create or reorganize campaigns, write and test advert copy, investigate rising costs or falling performance, and decide whether to increase spending or stop.
Why use it?
It helps avoid spending money before tracking works, the destination page is ready, and the acceptable customer-acquisition cost is known. It also helps distinguish poor campaign setup from genuinely weak results.

Skill for Claude Code

Written for Claude Code: shipped in a Claude Code plugin.

Part of the demand-generation plugin — 12 skills shipped together

Good fit Use it to create or reorganize campaigns, write and test advert copy, investigate rising costs or falling performance, and decide whether to increase spending or stop.

Compare 6 skills from other repositories ↓
Install with agentmods
npx agentmods add skills/cbrock84/headcount/paid-advertising
About the project

headcount is an organization of independently installable Claude Code plugins, each grouping skills for a department such as finance, security, or demand generation. Claude Code users install the departments they need and invoke their skills for specialized work; the catalogue entries are skills and related agent tooling from that organization.

cbrock84/headcount · 1,356 stars · on GitHub · cbrock84.github.io

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 cbrock84/headcount --skill paid-advertising
Clone the repo
git clone --depth 1 https://github.com/cbrock84/headcount

Made for: Claude Code.

Or install demand-generation, the plugin that ships this one along with the rest of its 12 skills.

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 paid-advertising

README.md
[![agentmods](https://agentmods.dev/badge/skills/cbrock84/headcount/paid-advertising/github.svg)](https://agentmods.dev/skills/cbrock84/headcount/paid-advertising)
Your own site
<a href="https://agentmods.dev/skills/cbrock84/headcount/paid-advertising"><img src="https://agentmods.dev/badge/skills/cbrock84/headcount/paid-advertising/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 paid-advertising

Your own site · 80×15
<a href="https://agentmods.dev/skills/cbrock84/headcount/paid-advertising"><img src="https://agentmods.dev/badge/skills/cbrock84/headcount/paid-advertising.svg" alt="Reviewed on agentmods" width="80" height="20"></a>
Per session 78 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 789 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. Third-party audits
  • NVIDIA SkillSpector pass 7 Sept 2026
How audits are shown
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 $0.00078 $0.00789
Opus 5 $0.00039 $0.00394
Sonnet 5 $0.00016 $0.00158
Haiku 4.5 $0.00008 $0.00079

Measured 8d ago against content hash df6b780bb17e, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-11, from the pricing page.

Security

Grade A, and why

paid-advertising 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.

plugins/demand-generation/skills/paid-advertising/SKILL.md · 80 lines

How it starts

The opening of the file, as written. The whole thing — 80 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Paid is the fastest way to buy a result and the fastest way to buy nothing. The difference is mostly discipline before launch.

Before spending

  • Know the ceiling. Maximum acceptable acquisition cost, derived from margin and payback period, not from what feels affordable.
  • Conversion tracking verified end to end, with a test conversion confirmed in the platform. Optimizing against broken tracking teaches the algorithm the wrong thing, and that damage persists.
  • The destination is ready. Paid traffic to a page that does not convert is a donation. Fix the page first — it is cheaper.

Structure

Structure follows intent, since intent determines what a click is worth.

  • Search — separate by intent tier: brand, high-intent problem terms, category terms, broad research. Never one budget across all four; the broad terms will consume it.
  • Social — structure by audience, since creative fatigue and audience saturation are the two variables and you need to see them separately.
  • Enough volume per campaign to exit the learning phase. Over-segmentation starves every campaign of the data it needs.

Naming conventions

Decide the convention before the first campaign, because renaming later breaks historical reporting on every platform.

A workable pattern encodes, in fixed order: channel, objective, audience or intent tier, geography, and creative theme — separated consistently, with no spaces. It should be possible to filter a report by any one of those segments without opening a campaign.

Apply it to every level: campaign, ad set, and ad. Inconsistent naming is why cross-channel reporting takes a week to assemble and why nobody trusts it when it arrives.

Creative

Creative is the biggest lever on paid social and the most neglected.

  • Test genuinely different angles, not variations of one. Five headlines around one idea is one test.
  • The first frame or line does the work. Assume the rest is not seen.
  • Match the ad's promise to the landing page exactly. Mismatch shows up as a bounce you will misdiagnose as a targeting problem.
  • Expect fatigue and plan refreshes on a schedule; rising cost with flat conversion rate is usually fatigue, not competition.

Read the full file on GitHub · 80 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. 8d ago Changed · +12 lines df6b780bb17e
  2. 12d ago First seen · 68 lines · 78 tokens per session scan A b32fe33d6e85

Subscribe to this mod's changes

paid-advertising is a skill published in the GitHub repository cbrock84/headcount (1,356 stars, last pushed 9d ago), licensed MIT. It adds 78 tokens to every session and 789 once invoked, about $0.0004 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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