Claude Ads is a Claude Code skill for managing paid-media operations across 12 advertising platforms, using account data or exports to produce audits, plans, creative workflows, experiments, monitoring, and reports. Agencies, consultants, and in-house performance teams use it for source-based analysis and controlled account work. The catalogue entries are its platform-specific skills, workers, and supporting instructions.
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 AgriciDaniel/claude-ads --skill ads-reportgit clone --depth 1 https://github.com/AgriciDaniel/claude-adsWrote 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/agricidaniel/claude-ads/ads-report)<a href="https://agentmods.dev/skills/agricidaniel/claude-ads/ads-report"><img src="https://agentmods.dev/badge/skills/agricidaniel/claude-ads/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/agricidaniel/claude-ads/ads-report"><img src="https://agentmods.dev/badge/skills/agricidaniel/claude-ads/ads-report.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- Socket pass
- Snyk pass
- 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 | $0.00047 | $0.00210 |
| Opus 5 | $0.00023 | $0.00105 |
| Sonnet 5 | $0.00009 | $0.00042 |
| Haiku 4.5 | $0.00005 | $0.00021 |
Grade A, and why
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 10d 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.
What it actually says
Render Paid Media Reports
- Accept a validated versioned report bundle, never loose worker prose.
- Confirm run completeness, evidence coverage, privacy class, branding choice, requested audience, and output formats.
- Render all formats from the same canonical data and deterministic templates.
- Preserve findings, confidence, evidence references, contradictions, missing inputs, actions, owners, and measurement windows.
- Run structural checks, then visual/layout checks for HTML and PDF.
- Write atomically inside the run directory and update its manifest.
Do not include credentials, customer lists, private paths, raw research, internal agent transcripts, or promotional copy unless the operator explicitly enabled branding. Never hide partial or insufficient-evidence status in an executive summary.
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.
- 10d ago First seen · 21 lines · 47 tokens per session scan A 3174b83b076c
ads-report is a skill published in the GitHub repository AgriciDaniel/claude-ads (9,090 stars, last pushed 1mo ago), licensed MIT. It adds 47 tokens to every session and 210 once invoked, about $0.0002 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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