forsvn-labs/meta-skills

create-paid-campaign

Create and evaluate a focused paid-media test. Use for Meta, Google, LinkedIn, TikTok, or another ad network when the user needs audience and offer strategy, finished ads, creative direction, landing-page congruence, budget logic, policy awareness, and a measurement decision.

First seen Aug 21, 2026

Installation

$ npx skills add forsvn-labs/meta-skills --skill create-paid-campaign

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More details

Agent compatibility

Declared targets from SKILL.md / docs. Unmarked agents are not listed — the skill may still install via the CLI.

Claude Code Not declared
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Repository health

Stars 14
License LICENSE
Default branch main
Open issues 1
Status Active

Skill metadata

Parsed from SKILL.md frontmatter.

Version2.0.0
More metadata
version
2.0.0

Package contents

Files included with this skill beyond the listing page.

  • skill md SKILL.md 2,345 B
  • docs SUMMARY.md 304 B

History

  1. First seen on skills.sh
  2. First recorded snapshot · 2 installs

SKILL.md

Create a paid campaign

Design the smallest paid test that can answer a consequential question. Do not treat spend, reach, or clicks as the strategy.

Establish the ad contract

Choose one network, one audience segment, one temperature, one offer, and one destination per test. Verify current network formats, targeting availability, and policy when they affect the work.

Define:

  • costly moment and audience qualification;
  • promise, mechanism, proof, and main objection;
  • offer and proportionate next action;
  • what the landing page must repeat;
  • primary business signal and diagnostic platform metrics.

Do not invent customer proof, performance benchmarks, targeting precision, or policy clearance.

Create discriminating variants

Write finished network-native ads. Variants must test different hypotheses—not synonyms. For each, provide the required components, such as primary text, headline, description, CTA, search headline, or video hook.

Brief creative around product evidence, mechanism, or a real transformation. Keep ad, creative, offer, and destination congruent. Identify claims or visual behavior that must be verified before launch.

Budget learning

Use current auction/input evidence when available. Fund the minimum viable test that can answer its question, or recommend zero spend.

Specify:

  • budget ceiling and allocation;
  • sample or observation requirement;
  • primary decision signal;
  • diagnostics and guardrails;
  • keep, revise, stop, and reallocation conditions;
  • attribution limits and likely confounders.

Evaluate one network/segment at a time. A high click-through rate cannot override poor qualified conversion or a safety/compliance failure.

Deliver

Return the audience/offer contract, finished ad set, creative direction, destination requirements, budget/test table, evaluation plan, and exact human approval boundary. Never launch, spend, upload audiences, or change a live account without explicit approval for that action.