Paid-Media-MCP: Skill for Claude Code

.claude/skills/ads-strategy-plan/SKILL.md

ads-strategy-plan is a skill for Claude Code from Pauesome/Paid-Media-MCP. It costs 80 tokens per session (1,352 once invoked), scanned A, original, MIT.

A guided paid-advertising planning skill for a Spanish client. It covers campaign choices, budgets, creative work, tracking, and rollout planning.

In plain words
What is it for?
It helps choose advertising platforms, organize campaigns, plan budgets and creatives, set up tracking, and prepare a phased launch.
Why use it?
It turns scattered advertising decisions into a structured kickoff and planning process with Spain-specific references and compliance guidance.

Skill for Claude Code

Written for Claude Code: installed under .claude/.

This is Pauesome/Paid-Media-MCP's own configuration. It tells Claude Code how to work on Paid-Media-MCP itself, so it is not a mod to install elsewhere. Copy it as a starting point and replace the rules that are about this project. Everything Paid-Media-MCP configures →

Reuse

Borrowing it

Nothing to install: this file belongs to Pauesome/Paid-Media-MCP. Take a copy, put it at the same path in your own repository, and replace the rules that are about this project with yours.

Copy the file
curl -O https://raw.githubusercontent.com/Pauesome/Paid-Media-MCP/main/.claude/skills/ads-strategy-plan/SKILL.md
Clone the repo
git clone --depth 1 https://github.com/Pauesome/Paid-Media-MCP

Made for: Claude Code.

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README.md
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Per session 80 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 1,352 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.
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 $0.00080 $0.01352
Opus 5.5 $0.00032 $0.00541
Sonnet 5.5 $0.00016 $0.00270
Haiku 4.5 $0.00008 $0.00135

Measured 2mo ago against content hash 7f2ba9d22b4f, method: parsed. Prices are Anthropic first-party input rates as of 2026-10-07, from the pricing page.

Security

Grade A, and why

ads-strategy-plan 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 2mo 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.

.claude/skills/ads-strategy-plan/SKILL.md · 149 lines

How it starts

The opening of the file, as written. The whole thing — 149 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Strategic Paid Advertising Plan — Spain

This skill is human-in-the-loop (interactive by design). Use it for kickoffs and strategy refreshes.

All numbers reference .claude/references/benchmarks-spain.md; all regulatory language references .claude/references/compliance-eu-spain.md; creative specs reference .claude/references/platform-specs.md.

Process

1. Discovery

Ask the user:

  • Business type, offer, target audience (Spain / EU / LATAM?)
  • Current advertising status (list_clients to see configured accounts and platforms)
  • Goals: awareness / lead gen / e-commerce sales / app installs
  • Monthly budget range in EUR
  • In-house creative capacity vs outsourced

2. Competitive analysis (lightweight)

  • Identify 3–5 competitors (user-provided)
  • Check presence on Meta Ad Library, Google Ads Transparency Center, TikTok Creative Center (DSA Ad Repositories — user opens in browser, not scraped)
  • Note messaging themes, creative approaches, keyword / audience gaps

3. Platform selection

Use the Platform Selection Matrix from ads-budget-review (same matrix; Spanish-client calibrated). Load matching industry pattern:

  • SaaS B2B
  • E-commerce (retail / wellness / DTC)
  • Local service (reformas, clínicas, legal, asesorías)
  • Fashion / Beauty / Food (D2C)
  • Wellness / Salud (avoid Rx-drug-to-consumer — illegal in Spain per Ley 29/2006)

4. Campaign architecture

Naming convention:

[Platform]_[Objective]_[Audience]_[Geo]_[Date]

Example: META_CONV_Prospecting_ES_2026Q2

Template:

Account
├── Brand Campaign (always-on)
├── Non-Brand Prospecting
│   ├── Top Funnel — Awareness
│   ├── Mid Funnel — Consideration
│   └── Bottom Funnel — Conversion
├── Retargeting
│   ├── Website visitors (7–30 days)
│   ├── Engaged users (video views, social engagement)
│   └── Cart abandoners / form starters
└── Testing
    └── New audiences / formats / messaging

5. Budget planning

Apply 70/20/10:

  • 70% proven — primary platforms with proven ROI
  • 20% scaling — platforms showing promise
  • 10% testing — new strategies

Read the full file on GitHub · 149 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. 2mo ago First seen · 149 lines · 80 tokens per session scan A 7f2ba9d22b4f

Subscribe to this mod's changes

ads-strategy-plan is a skill published in the GitHub repository Pauesome/Paid-Media-MCP (2 stars, last pushed 4mo ago), licensed MIT. It adds 80 tokens to every session and 1,352 once invoked, about $0.0003 per session on Opus 5.5. 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.

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