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.
npx skills add amekala/ads-mcp --skill adspirer-linkedin-adsgit clone --depth 1 https://github.com/amekala/ads-mcpWrote 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.
[](https://agentmods.dev/skills/amekala/ads-mcp/adspirer-linkedin-ads)<a href="https://agentmods.dev/skills/amekala/ads-mcp/adspirer-linkedin-ads"><img src="https://agentmods.dev/badge/skills/amekala/ads-mcp/adspirer-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.
<a href="https://agentmods.dev/skills/amekala/ads-mcp/adspirer-linkedin-ads"><img src="https://agentmods.dev/badge/skills/amekala/ads-mcp/adspirer-linkedin-ads.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector pass
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.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5.1 | $0.00065 | $0.00661 |
| Opus 5 | $0.00032 | $0.00331 |
| Sonnet 5 | $0.00013 | $0.00132 |
| Haiku 4.5 | $0.00006 | $0.00066 |
Grade A, and why
adspirer-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 12d 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.
How it starts
The opening of the file, as written. The whole thing — 68 lines — stays where its author put it; the contents beside it link to each section on GitHub.
LinkedIn Ads
Everything on LinkedIn goes through the linkedin_ads router. Follow adspirer-mcp for the
two-step.
Account parameter: account_id, as a string. Budgets are in the account's currency.
Every campaign belongs to a campaign group
LinkedIn will not create a bare campaign. Pass either an existing campaign_group_id, or a
campaign_group_name to create one. There is no default and no implicit group — omitting both
fails.
List the existing groups before you invent a new one; most accounts already have a structure the user cares about.
Build order
Campaign group → campaign → creative. Campaigns are created paused.
select_linkedin_campaign_type picks the format when the user hasn't said. Then
create_linkedin_image_campaign, _video_campaign, _carousel_campaign, or _text_campaign.
Creatives attach with add_linkedin_creative and its variants.
Targeting is the point
LinkedIn's value is the professional graph: job title, seniority, function, company, company size, industry, skills, and groups. That's what the user is paying LinkedIn's CPMs for — a broad, demographic-only LinkedIn campaign is a waste of money and you should say so.
search_linkedin_targeting resolves a name ("VP of Engineering", "Financial Services") to the
facet id you need. research_business_for_linkedin_targeting turns a company description into a
targeting proposal. Don't guess facet ids.
LinkedIn enforces a minimum audience size (about 300 members). Over-narrow targeting simply won't run — check the estimated size before you build.
Costs are high, so structure matters
LinkedIn CPCs run many times Google's. That changes the advice:
- Budgets under roughly $25/day rarely gather enough data to optimize.
- Lead-gen forms convert far better than sending people to a landing page. Prefer them for lead objectives.
- Because clicks are expensive, creative fatigue bites sooner.
analyze_linkedin_creative_performanceshows which creative is carrying the campaign.
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.
- 12d ago First seen · 68 lines · 65 tokens per session scan A 9660f1cab867
adspirer-linkedin-ads is a skill published in the GitHub repository amekala/ads-mcp (90 stars, last pushed 5d ago), licensed MIT. It adds 65 tokens to every session and 661 once invoked, about $0.0003 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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