linkedin-ads

linkedin-ads is a skill for Claude Code, Codex from swan-gtm/gtm-skills. It costs 129 tokens per session (1,409 once invoked), scanned A, original, MIT.

A guide and routing system for managing LinkedIn Ads for business-to-business software companies. It covers campaign planning, audiences, budgets, bidding, creative, account audits, and performance analysis.

In plain words
What is it for?
Use it to create media plans, size audiences, allocate budgets, structure campaigns, choose bids, audit accounts, analyse benchmarks, and develop LinkedIn ad copy and formats.
Why use it?
It gives teams a consistent way to plan and review LinkedIn advertising across the buyer journey. It also helps identify which guidance to use for setup, reporting, or account audits.

Skill for Claude CodeCodex

Written for no agent in particular: nothing here depends on one.

Good fit Use it to create media plans, size audiences, allocate budgets, structure campaigns, choose bids, audit accounts, analyse benchmarks, and develop LinkedIn ad copy and formats.

Compare 6 skills from other repositories ↓
Install with agentmods
npx agentmods add skills/swan-gtm/gtm-skills/linkedin-ads
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 swan-gtm/gtm-skills --skill linkedin-ads
Clone the repo
git clone --depth 1 https://github.com/swan-gtm/gtm-skills

Made for: Claude Code, Codex.

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 linkedin-ads

README.md
[![agentmods](https://agentmods.dev/badge/skills/swan-gtm/gtm-skills/linkedin-ads/github.svg)](https://agentmods.dev/skills/swan-gtm/gtm-skills/linkedin-ads)
Your own site
<a href="https://agentmods.dev/skills/swan-gtm/gtm-skills/linkedin-ads"><img src="https://agentmods.dev/badge/skills/swan-gtm/gtm-skills/linkedin-ads/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 linkedin-ads

Your own site · 80×15
<a href="https://agentmods.dev/skills/swan-gtm/gtm-skills/linkedin-ads"><img src="https://agentmods.dev/badge/skills/swan-gtm/gtm-skills/linkedin-ads.svg" alt="Reviewed on agentmods" width="80" height="20"></a>
Per session 129 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 1,409 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 $0.00129 $0.01409
Opus 5 $0.00064 $0.00705
Sonnet 5 $0.00026 $0.00282
Haiku 4.5 $0.00013 $0.00141

Measured 9d ago against content hash 4b4f35c32999, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-12, from the pricing page.

Security

Grade A, and why

linkedin-ads 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 9d 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.

skills/ivan-falco/linkedin-ads/SKILL.md · 70 lines

How it starts

The opening of the file, as written. The whole thing — 70 lines — stays where its author put it; the contents beside it link to each section on GitHub.

LinkedIn Ads Management

Orchestrator for all LinkedIn Ads tasks. Route to the correct sub-skill based on the user's request.

Methodology

This skill implements a full-funnel, 5-Stage Demand Engine approach to LinkedIn Ads that prioritizes audience precision, Thought Leader Ads, and systematic scaling through audience penetration.

Routing Logic

Determine what the user needs and load the relevant reference files:

User Intent Load These Files When to Use
Build a new campaign plan references/full-funnel-framework.md, references/campaign-structures.md, references/audience-sizing.md, references/bidding-strategy.md, references/launch-checklist.md New client onboarding, new campaign setup, media plan creation, budget allocation
Analyze performance data references/benchmarks.md, references/bidding-strategy.md, references/scaling-strategy.md Weekly/monthly reporting, diagnosing underperformance, optimization recommendations
Audit an existing account references/audit-checklist.md, references/benchmarks.md, references/audience-sizing.md New client audit, periodic health check, account takeover, identifying issues
Creative development references/creative-strategy.md, references/copy-audit-framework.md, references/conversation-ads.md, references/document-ads.md Ad copy, creative briefs, format selection
Scaling decisions references/scaling-strategy.md, references/bidding-strategy.md, references/audience-sizing.md Increasing budgets, adding campaigns, expanding audiences

Knowledge Base

All recommendations must be grounded in the knowledge base. Before executing any sub-skill, read the relevant reference files:

File Contains Read When
full-funnel-framework.md TOF/MOF/BOF structure, budget allocation, timeline Campaign planning, strategy discussions
audience-sizing.md Audience size ranges, targeting rules, exclusions, job functions vs titles, splitting audiences, audience expansion models Building audiences, reviewing targeting, scaling audiences
campaign-structures.md 6 campaign group structure models, naming conventions, 5-Stage Demand Engine campaign groups framework, splitting methodology Setting up campaign structure, scaling structure
launch-checklist.md 8-part pre-launch checklist Before launching any campaign
bidding-strategy.md Bidding approach, weekly optimization, audience penetration rules, group budget optimization Optimizing bids, weekly management, budget decisions
benchmarks.md CTR/CPC/CPL benchmarks by stage Performance analysis, setting expectations
creative-strategy.md Creative by awareness stage, 12 angles with rationale, TLA strategy, templates Creative development, ad copy
conversation-ads.md Conversation ad best practices: copy, CTAs, sender, testing, TLA combo Conversation ad campaigns, inbox messaging
document-ads.md Document ad best practices: 7-slide formula, copy principles, design, audience variants Document ad / carousel campaigns, MOF nurture
copy-audit-framework.md 5-layer copy audit: accuracy, tone, structure, design, audience fit Reviewing any ad copy before launch, quality control
landing-pages.md Landing page strategy per funnel stage, Lead Gen Form optimization Campaign planning, conversion optimization
scaling-strategy.md Scaling progression (1 campaign to multiple accounts), penetration rules, 5-Stage Demand Engine campaign groups, forecasting, group budgets, objective experiments Scaling campaigns, increasing budgets, advanced strategy
audit-checklist.md Full audit checklist with priorities Account audits, health checks

Read the full file on GitHub · 70 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. 9d ago First seen · 70 lines · 129 tokens per session scan A 4b4f35c32999

Subscribe to this mod's changes

linkedin-ads is a skill published in the GitHub repository swan-gtm/gtm-skills (153 stars, last pushed 2d ago), licensed MIT. It adds 129 tokens to every session and 1,409 once invoked, about $0.0006 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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