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 matteotitta/genesys-skills --skill paid-ads-reportgit clone --depth 1 https://github.com/matteotitta/genesys-skillsWrote 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/matteotitta/genesys-skills/paid-ads-report)<a href="https://agentmods.dev/skills/matteotitta/genesys-skills/paid-ads-report"><img src="https://agentmods.dev/badge/skills/matteotitta/genesys-skills/paid-ads-report/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/matteotitta/genesys-skills/paid-ads-report"><img src="https://agentmods.dev/badge/skills/matteotitta/genesys-skills/paid-ads-report.svg" alt="Reviewed on agentmods" width="80" height="20"></a>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 | $0.00202 | $0.02495 |
| Opus 5 | $0.00101 | $0.01247 |
| Sonnet 5 | $0.00040 | $0.00499 |
| Haiku 4.5 | $0.00020 | $0.00249 |
Grade A, and why
paid-ads-report 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.
How it starts
The opening of the file, as written. The whole thing — 141 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Paid Ads Report — brand-bound WoW LinkedIn Ads report
Turn the linkedin-ads MCP's live analytics into a single-page, on-brand week-over-week report. Reads spend / CTR / CPL / demographics / trend via the MCP's free read tools, computes the WoW deltas, writes a three-sentence "what changed and why" opener, and renders the whole thing via /dashboard bound to the client's DESIGN.md tokens. The reader gets the story first, the tables second.
Adapted from danielpopamd/linkedin-ads-mcp's generate-dashboard.ts + compare_performance/get_daily_trends (MIT) via 0726 /steal — see .claude/discovery/0726-linkedin-ads-mcp-steal-analysis.md (items M4 + M6). The upstream renders a stock HTML file; this renders a Genesys-branded report through /dashboard.
Doctrine inherited
Output complies with:
output-tenets.md— the seven tenets (the auto-insight opener IS the SQCA lead).output-simplicity.md— single-page report discipline (30–40 lines of narrative + the visual); length by reader.quantitative-evidence-floors.md— a WoW delta is a verdict only above the volume floor. "Spend up 22%, CPL down 9%" on thin volume gets the "too early" caveat, not a crown.design-production.md— DESIGN.md token contract + banned visual patterns (no gradient text, no generic drop shadows, ≤2 font weights, one accent).linkedin-ads-spend.md— read tools only. This skill never calls a write tool. If a write is ever needed, it's a separate gated action, not part of the report.storage-policy.md+pii-redaction.md— ads data is client-confidential; route to the client folder, never commit raw exports or the rendered dashboard to git.
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.
- 9d ago First seen · 141 lines · 202 tokens per session scan A 3de5fc2c5f7b
paid-ads-report is a skill published in the GitHub repository matteotitta/genesys-skills (36 stars, last pushed 1mo ago), licensed MIT. It adds 202 tokens to every session and 2,495 once invoked, about $0.0010 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.
Other skills, from other repositories
gingiris-b2b-growth
🇺🇸 B2B SaaS Growth — PLG vs SLG Playbook — Diagnose whether your problem is distribution, pricing, or PMF. PLG/SLG selection by ACV and sales cycle, the 5-stage path from $0 to $10M ARR, NRR discipline, affiliate & channel motion, enterprise tiering. Built from HeyGen, Deel, Vercel, Supabase, Snowflake patterns.…
gr-b2b-growth
A guide to growing a business-to-business software product from early user research to large-scale sales. B2B software is sold to companies rather than individual consumers.
go-to-market-playbook
A reusable Go-to-Market strategy template for both B2B and B2C launches. Covers positioning, messaging, ICP definition, channel selection, and competitive analysis frameworks. By @WeiYipei.
gingiris-go-global
🇺🇸 AI Product / SaaS Go-Global Complete SOP — From competitor research to launch to monetization. A full-cycle playbook covering Phase 0-5 (market validation, positioning, first 100 users, user interviews, beta-to-growth) plus open-source launch, Product Hunt, Reddit, SEO/GEO, conversion, and org principles.…
gr-competitor-research
Your competitor just launched. You have no idea how they grew so fast. Should you reverse-engineer their website? Track their social media? Map their growth flywheel? This gives you the complete SOP — from Wayback Machine snapshots to X/Twitter propagation analysis to growth flywheel scoring. Built from 150+ AI…
ai-launch-playbook
Launch your AI product to global attention — the playbook behind Manus, Devin, and AFFiNE's breakout launches. Covers AI-specific GTM strategy, hype cycle management, waitlist tactics, and multi-market rollout for maximum day-one impact.