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 ads-metagit 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-meta)<a href="https://agentmods.dev/skills/naveedharri/benai-skills/ads-meta"><img src="https://agentmods.dev/badge/skills/naveedharri/benai-skills/ads-meta/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-meta"><img src="https://agentmods.dev/badge/skills/naveedharri/benai-skills/ads-meta.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 | $0.00066 | $0.01376 |
| Opus 5 | $0.00033 | $0.00688 |
| Sonnet 5 | $0.00013 | $0.00275 |
| Haiku 4.5 | $0.00007 | $0.00138 |
Grade A, and why
ads-meta 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 — 131 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Meta Ads Deep Analysis
Process
- Collect Meta Ads data (Ads Manager export, Events Manager screenshot, EMQ scores)
- Read
ads/references/meta-audit.mdfor full 46-check audit - Read
ads/references/benchmarks.mdfor Meta-specific benchmarks - Read
ads/references/scoring-system.mdfor weighted scoring - Evaluate all applicable checks as PASS, WARNING, or FAIL
- Calculate Meta Ads Health Score (0-100)
- Generate findings report with action plan
What to Analyze
Pixel / CAPI Health (30% weight)
- Meta Pixel installed and firing on all pages
- Conversions API (CAPI) active (30-40% data loss without it post-iOS 14.5)
- Event deduplication configured (event_id matching, ≥90% dedup rate)
- Event Match Quality (EMQ) ≥8.0 for Purchase event
- All standard events configured (ViewContent, AddToCart, Purchase, Lead)
- Custom conversions created for non-standard events
- Aggregated Event Measurement (AEM) configured for iOS
- Domain verification completed
- Server-side events include customer_information parameters
- Pixel fires with correct currency and value parameters
Creative (30% weight)
- ≥3 creative formats active (image, video, carousel, collection)
- ≥5 creatives per ad set (Meta recommendation)
- Creative fatigue detection: CTR drop >20% over 14 days = FAIL
- Video creative: 15s max for Stories/Reels, 30s max for Feed
- UGC/testimonial creative tested
- Dynamic Creative Optimization (DCO) tested
- Ad copy: headline under 40 chars, primary text under 125 chars
- Creative refresh cadence: every 2-4 weeks for high-spend
Account Structure (20% weight)
- Campaign Budget Optimization (CBO) vs Ad Set Budget (ABO) intentional
- Campaign consolidation: ≤5 active campaigns per objective type
- Learning phase health: <30% ad sets in "Learning Limited" (FAIL >50%)
- Budget per ad set: ≥5x target CPA (minimum for learning phase exit)
- Ad set audience overlap <30% (Audience Overlap tool)
- Campaign naming conventions consistent and descriptive
- Advantage+ Shopping Campaigns (ASC) active for e-commerce
- Simplified campaign structure (fewer, larger ad sets preferred)
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 · 131 lines · 66 tokens per session scan A bfc94ff58e8b
ads-meta is a skill published in the GitHub repository naveedharri/benai-skills (61 stars, last pushed 8d ago), licensed MIT. It adds 66 tokens to every session and 1,376 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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