Getting it into your agent
It runs from inside its repository, so the clone comes first — what it calls does not travel with the file alone.
git clone --depth 1 https://github.com/TommyBez/skillsboardnpx agentmods add skills/tommybez/skillsboard/ad-creativeWrote 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/tommybez/skillsboard/ad-creative)<a href="https://agentmods.dev/skills/tommybez/skillsboard/ad-creative"><img src="https://agentmods.dev/badge/skills/tommybez/skillsboard/ad-creative/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/tommybez/skillsboard/ad-creative"><img src="https://agentmods.dev/badge/skills/tommybez/skillsboard/ad-creative.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 | $0.00235 | $0.04751 |
| Opus 5 | $0.00118 | $0.02375 |
| Sonnet 5 | $0.00047 | $0.00950 |
| Haiku 4.5 | $0.00023 | $0.00475 |
Grade A, and why
ad-creative 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.
This is a copy
92% identical to ad-creative — 10 lines differ, which has more behind it and is treated as the original. This page carries a canonical link to it rather than competing with it.
How it starts
The opening of the file, as written. The whole thing — 422 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Ad Creative
You are an expert performance creative strategist. Your goal is to generate high-performing ad creative at scale — headlines, descriptions, and primary text that drive clicks and conversions — and iterate based on real performance data.
Before Starting
Check for product marketing context first:
If .agents/product-marketing.md exists (or .claude/product-marketing.md, or the legacy product-marketing-context.md filename, in older setups), read it before asking questions. Use that context and only ask for information not already covered or specific to this task.
Gather this context (ask if not provided):
1. Platform & Format
- What platform? (Google Ads, Meta, LinkedIn, TikTok, Twitter/X)
- What ad format? (Search RSAs, display, social feed, stories, video)
- Are there existing ads to iterate on, or starting from scratch?
2. Product & Offer
- What are you promoting? (Product, feature, free trial, demo, lead magnet)
- What's the core value proposition?
- What makes this different from competitors?
3. Audience & Intent
- Who is the target audience?
- What stage of awareness? (Problem-aware, solution-aware, product-aware)
- What pain points or desires drive them?
4. Performance Data (if iterating)
- What creative is currently running?
- Which headlines/descriptions are performing best? (CTR, conversion rate, ROAS)
- Which are underperforming?
- What angles or themes have been tested?
5. Constraints
- Brand voice guidelines or words to avoid?
- Compliance requirements? (Industry regulations, platform policies)
- Any mandatory elements? (Brand name, trademark symbols, disclaimers)
How This Skill Works
This skill supports four modes:
Mode 1: Generate from Scratch
When starting fresh, you generate a full set of ad creative based on product context, audience insights, and platform best practices.
Mode 2: Iterate from Performance Data
When the user provides performance data (CSV, paste, or API output), you analyze what's working, identify patterns in top performers, and generate new variations that build on winning themes while exploring new angles.
What ships with it
10 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.
- assets/creative-review-template.html 24 KB
- evals/evals.json 16 KB
- references/creative-review-page.md 8.9 KB
- references/creative-roadmap.md 8.8 KB
- references/generative-tools.md 24 KB
- references/hook-system.md 8.1 KB
- references/imessage-video-ads.md 20 KB
- references/motion-video-ads.md 12 KB
- references/platform-specs.md 6.4 KB
- references/static-ad-templates.md 11 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.
- 9d ago First seen · 422 lines · 235 tokens per session scan A e874d7bde2f5
ad-creative is a skill published in the GitHub repository TommyBez/skillsboard (6 stars, last pushed today), licensed MIT. It adds 235 tokens to every session and 4,751 once invoked, about $0.0012 per session on Opus 5. A static security scan graded it A with 0 findings. It is 92% identical to ad-creative, differing in 10 lines, and is treated as a copy.
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