paid-media-ops

paid-media-ops is a skill for Claude Code from shalintripathi/saas-marketing-agents. It costs 1,035 tokens per session (6,333 once invoked), scanned A, original, MIT.

A set of operating guidelines for paid advertising for business-to-business software companies. It covers advertising channels, campaign planning, measurement, budgets, creative work, and brand context.

In plain words
What is it for?
Use it for pay-per-click strategy, Google Ads, LinkedIn Ads, social and programmatic advertising, creative planning, attribution, budget allocation, return-on-ad-spend improvement, and media-spend optimization.
Why use it?
It helps teams coordinate paid campaigns while keeping claims tied to documented company evidence. It also provides a defined process for handling missing brand information and assumptions.

Skill for Claude Code

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

Part of the saas-marketing plugin — 19 skills, 91 agents shipped together

Good fit Use it for pay-per-click strategy, Google Ads, LinkedIn Ads, social and programmatic advertising, creative planning, attribution, budget allocation, return-on-ad-spend improvement, and media-spend optimization.

Compare 6 skills from other repositories ↓
Install with agentmods
npx agentmods add skills/shalintripathi/saas-marketing-agents/paid-media-ops
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 shalintripathi/saas-marketing-agents --skill paid-media-ops
Clone the repo
git clone --depth 1 https://github.com/shalintripathi/saas-marketing-agents

Made for: Claude Code.

Or install saas-marketing, the plugin that ships this one along with the rest of its 19 skills, 91 agents.

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-media-ops

README.md
[![agentmods](https://agentmods.dev/badge/skills/shalintripathi/saas-marketing-agents/paid-media-ops/github.svg)](https://agentmods.dev/skills/shalintripathi/saas-marketing-agents/paid-media-ops)
Your own site
<a href="https://agentmods.dev/skills/shalintripathi/saas-marketing-agents/paid-media-ops"><img src="https://agentmods.dev/badge/skills/shalintripathi/saas-marketing-agents/paid-media-ops/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-media-ops

Your own site · 80×15
<a href="https://agentmods.dev/skills/shalintripathi/saas-marketing-agents/paid-media-ops"><img src="https://agentmods.dev/badge/skills/shalintripathi/saas-marketing-agents/paid-media-ops.svg" alt="Reviewed on agentmods" width="80" height="20"></a>
Per session 1,035 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 6,333 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 $0.01035 $0.06333
Opus 5.5 $0.00414 $0.02533
Sonnet 5.5 $0.00207 $0.01267
Haiku 4.5 $0.00103 $0.00633

Measured yesterday against content hash 39e3f36f5e77, method: parsed. Prices are Anthropic first-party input rates as of 2026-10-07, from the pricing page.

Security

Grade A, and why

paid-media-ops 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 yesterday.

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/saas-marketing/skills/paid-media-ops/SKILL.md · 345 lines

How it starts

The opening of the file, as written. The whole thing — 345 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Step 0 (always first): Load brand context

Before producing any deliverable, look for a brand-context.md file in the user's project root (also check ./.claude/brand-context.md and ./docs/brand-context.md). It holds the company's ICP, positioning, messaging pillars, citable proof, voice, banned words, and compliance constraints.

  • If it exists: read it in full and treat it as binding for this run. Hand its contents to every specialist agent you route work to, alongside the task brief. Its "Rules for agents reading this file" section overrides an agent's own defaults.
  • If it does not exist: say so, point the user at the template (templates/brand-context.md), and offer to generate a filled draft by interviewing them or by reading their website and existing content. Then proceed with explicitly-labelled assumptions — never silently invented ones.

Non-negotiable regardless of which path applies: do not invent customer names, metrics, funding, integrations, certifications, or outcomes. Only proof recorded in brand-context.md (or supplied directly in the request) may be used as fact. Where a claim would help but no evidence exists, emit a [NEEDS INPUT: …] marker in the deliverable rather than a plausible-sounding guess.


What This Is

The Paid Media Operations skill brings together 8 specialized agents to manage end-to-end paid advertising for B2B SaaS companies. From strategic budget allocation and campaign setup to daily optimization, creative strategy, and attribution analysis, this team handles Google Ads, LinkedIn Ads, social advertising, programmatic buying, the conversion signal the bidding algorithms learn from, and the media bought directly from publishers — newsletter, podcast and community sponsorships, paid review-site listings, and pay-per-lead content syndication. This skill enables you to achieve predictable cost-per-acquisition, maximize return on ad spend (ROAS), and scale acquisition channels with confidence.

Read the full file on GitHub · 345 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. yesterday Changed · +1 lines · +84 tokens per session 39e3f36f5e77
  2. 5d ago Changed · +1 lines · +18 tokens per session ab0132b052c0
  3. 6d ago Changed · +1 lines · +35 tokens per session 2212109a48ac
  4. 9d ago Changed · +1 lines · +69 tokens per session 310e229a17d2
  5. 14d ago Changed · +36 tokens per session 3882c1976a45
  6. 18d ago Changed · +115 tokens per session 0d36990bb9a3
  7. 22d ago Changed · +1 lines · +82 tokens per session 61642f9403e0
  8. 26d ago Changed · +7 lines · +170 tokens per session 0dc6572fecdf
  9. 1mo ago Changed · +5 lines · +157 tokens per session 32b9ee1a0872
  10. 1mo ago First seen · 328 lines · 269 tokens per session scan A 8320c7f22e69

Subscribe to this mod's changes

paid-media-ops is a skill published in the GitHub repository shalintripathi/saas-marketing-agents (30 stars, last pushed yesterday), licensed MIT. It adds 1,035 tokens to every session and 6,333 once invoked, about $0.0041 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.