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 naveedharri/benai-skills --skill adsgit clone --depth 1 https://github.com/naveedharri/benai-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/naveedharri/benai-skills/ads)<a href="https://agentmods.dev/skills/naveedharri/benai-skills/ads"><img src="https://agentmods.dev/badge/skills/naveedharri/benai-skills/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/naveedharri/benai-skills/ads"><img src="https://agentmods.dev/badge/skills/naveedharri/benai-skills/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 | $0.00166 | $0.02261 |
| Opus 5 | $0.00083 | $0.01130 |
| Sonnet 5 | $0.00033 | $0.00452 |
| Haiku 4.5 | $0.00017 | $0.00226 |
Grade A, and why
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 11d 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 — 196 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Ads — Multi-Platform Paid Advertising Audit & Optimization
Comprehensive ad account analysis across all major platforms (Google, Meta, LinkedIn, TikTok, Microsoft). Orchestrates 11 specialized sub-skills and 6 subagents.
Quick Reference
| Command | What it does |
|---|---|
/ads audit |
Full multi-platform audit with parallel subagent delegation |
/ads google |
Google Ads deep analysis (Search, PMax, YouTube) |
/ads meta |
Meta Ads deep analysis (FB, IG, Advantage+) |
/ads youtube |
YouTube Ads specific analysis |
/ads linkedin |
LinkedIn Ads deep analysis (B2B, Lead Gen) |
/ads tiktok |
TikTok Ads deep analysis (Creative, Shop, Smart+) |
/ads microsoft |
Microsoft/Bing Ads deep analysis (Copilot, Import) |
/ads creative |
Cross-platform creative quality audit |
/ads landing |
Landing page quality assessment for ad campaigns |
/ads budget |
Budget allocation and bidding strategy review |
/ads plan <business-type> |
Strategic ad plan with industry templates |
/ads competitor |
Competitor ad intelligence analysis |
/ads creative |
Cross-platform creative quality audit + brand context setup + creative generation |
Orchestration Logic
When the user invokes /ads audit, delegate to subagents in parallel:
- Collect account data (exports, screenshots, or API access details)
- Detect business type and identify active platforms
- Spawn subagents: audit-google, audit-meta, audit-creative, audit-tracking, audit-budget, audit-compliance
- Collect results and generate unified report with Ads Health Score (0-100)
- Create prioritized action plan with Quick Wins
For individual commands (/ads google, /ads meta, etc.), load the relevant
sub-skill directly.
Industry Detection
Detect business type from ad account signals:
- SaaS: trial_start/demo_request events, pricing page targeting, long attribution windows
- E-commerce: purchase events, product catalog/feed, Shopping/PMax campaigns
- Local Service: call extensions, location targeting, store visits, directions events
- B2B Enterprise: LinkedIn Ads active, ABM lists, high CPA tolerance ($50+), long sales cycle
- Info Products: webinar/course funnels, lead gen forms, low-ticket offers
- Mobile App: app install campaigns, in-app events, deep linking
- Real Estate: listing feeds, property-specific landing pages, geo-heavy targeting
- Healthcare: HIPAA compliance flags, healthcare-specific ad policies
- Finance: Special Ad Categories declared, financial products compliance
- Agency: multiple client accounts, white-label reporting needs
What ships with it
14 files beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.
- references/benchmarks.md 6.2 KB
- references/bidding-strategies.md 11 KB
- references/brand-context.md 4.3 KB
- references/budget-allocation.md 7.5 KB
- references/compliance.md 7.7 KB
- references/conversion-tracking.md 9.5 KB
- references/creative-volume.md 8.9 KB
- references/google-audit.md 15 KB
- references/linkedin-audit.md 7.4 KB
- references/meta-audit.md 10 KB
- references/microsoft-audit.md 7.9 KB
- references/platform-specs.md 8.4 KB
- references/scoring-system.md 7.6 KB
- references/tiktok-audit.md 8.5 KB
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.
- 11d ago First seen · 196 lines · 166 tokens per session scan A 6cbde7e1b5d1
ads is a skill published in the GitHub repository naveedharri/benai-skills (61 stars, last pushed 7d ago), licensed MIT. It adds 166 tokens to every session and 2,261 once invoked, about $0.0008 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.
Other skills, from other repositories
project
A single starting point for setting up an AI-assisted project in Claude Cowork. It asks questions about the work, reviews available add-ons, and creates project instructions, custom agents, and connected workflows.
cs-channel-message
A channel-message writing tool for search ads, advertising, customer relationship messages, and app notifications. It uses the NCM sequence—Need, Channel, Moment, Message, and CTA—to adapt wording to where and when customers see it.
design-sync-upload
An uploader for design-system files such as DESIGN.md, tokens, logos, fonts, and images into Claude Design. It can either use an authenticated connection or prepare a folder and guide for manual upload.
design-tokens-transformer
A converter for design tokens, which are named values for colors, fonts, spacing, borders, shadows, and motion. It translates one shared token source into CSS variables and Tailwind or shadcn-style theme files, and can convert them back for checking.
doc-html-slide
A renderer that turns presentation content into a single HTML slide deck that opens directly in a browser. It creates a 16:9 slide sequence with navigation, fullscreen viewing, printing to PDF, and speaker-note controls.
finance-investor-relations
An investor-relations tool for preparing pitch decks and three-year financial models for fundraising. An IR, or investor-relations, deck explains a company to potential investors, while the model covers sales, profit, cash flow, and valuation.