chs_ad-creative
When the user wants to generate, iterate, or scale ad creative — headlines, descriptions, primary text, or full ad variations — for any paid advertising…
Skill by boarlabsxyz
Install
Works with Claude Code, Claude apps, Codex, Cursor, Gemini CLI, GitHub Copilot, VS Code, OpenCode, Goose, Windsurf. Read the repository before you give any tool access to your data.
npx agentmarket install skill/boarlabsxyz-chs-ad-creative
Asks which of your tools to add it to (Claude Code, Codex, Cursor, VS Code, Windsurf, Gemini CLI, Claude Desktop) and shows the change first. See https://agentmart.dev/cli.
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About
Use cases: testing, writing, marketing
Reviews
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Permissions
What this skill can do and what it asks for, from its SKILL.md. Checked Oct 25, 2026.
- Tools
- No tools found
- Secrets
- None asked for
- Install scripts
- None found
Network hosts it talks to 1
codeload.github.com· found in install command
Files it touches
~/.claude/skills/chs-ad-creative
What's inside
- Skill name
chs_ad-creative- Description
- When the user wants to generate, iterate, or scale ad creative — headlines, descriptions, primary text, or full ad variations — for any paid advertising platform. Also use when the user mentions 'ad copy variations,' 'ad creative,' 'generate headlines,' 'RSA headlines,' 'bulk ad copy,' 'creative testing,' 'write me some ads,' 'Facebook ad copy,' 'Google ad headlines,' 'LinkedIn ad text,' 'static ads,' 'ad templates,' 'iMessage ad,' 'ChatGPT ad,' 'creative strategy,' 'creative roadmap,' 'creative retro,' 'hook writing,' 'creative review page,' 'motion video ad,' 'faceless video ad,' 'UGC ad,' 'greenscreen ad,' 'TikTok/Reels ad format,' 'Meta ad format tier list,' or 'creative format taxonomy.' Use it to produce or iterate ad copy at scale. Copy avoids AI tells like 'it's not X, it's Y' reveals. For campaign strategy and targeting, see chs_ads. For landing page copy, see chs_copywriting. Test hypotheses must be falsifiable, naming the metric, the comparison, and the expected direction.
- License
- MIT
- Metadata
- version: 2.12.1
- Instructions
- 471 lines in SKILL.md · view on GitHub
Agent Skills spec issues
- name: only lowercase letters, digits and single hyphens allowed
Files (14)
- SKILL.md
- creative-review-template.html · assets/
- evals.json · evals/
- awareness-headlines.md · references/
- creative-review-page.md · references/
- creative-roadmap.md · references/
- generative-tools.md · references/
- hook-system.md · references/
- imessage-video-ads.md · references/
- meta-creative-formats.md · references/
- motion-video-ads.md · references/
- platform-specs.md · references/
- short-form-video-specs.md · references/
- static-ad-templates.md · references/
SKILL.md (first lines)
# 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.
Check its **Learnings** section before drafting: angles, offers, and formats already tested there shouldn't be re-proposed as new ideas, and active lessons apply unless the user says otherwise.
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.
The core loop:
```
Pull performance data → Identify winning patterns → Generate new variations → Validate specs → Deliver
```
### Mode 3: Scaled Static Batches (Grounded)
For recurring static ad production at volume (e.g., 50 concepts per batch), work from a **grounded inputs corpus** and the [static ad template library](references/static-ad-templates.md). Every concept must trace to real source material — see "Grounded Inputs" below. To run this on a daily or weekly cadence, see the daily-creative-drop loop in **chs_marketing-loops**. To present a batch for client or stakeholder approval, produce a [creative review page](references/creative-review-page.md).
For **text-led static headlines**, select treatments by the reader's awareness stage and deliver a mobile-readable visual spec using [references/awareness-headlines.md](references/awareness-headlines.md). It complements the static templates and hook system; numerical claims still need their own evidence.
### Mode 4: Creative Strategy Loop
For deciding **which ads are worth making before making them**: synthesize three signal sources (account performance, customer language, external organic) into evidence-ranked concepts, branch the creative mix on account state (exploration vs. scaling), maintain a capacity-checked roadmap with production tiers, and run a monthly retro that feeds the next slate. The full system lives in [references/creative-roadmap.md](references/creative-roadmap.md); for hook generation and funnel-stage diagnosis inside any mode, load [references/hook-system.md](references/hook-system.md).
---
## Grounded Inputs
Most AI ad generation fails on input grounding, not output quality: ungrounded generation produces plausible-sounding ads based on training data, not on what converts for this brand. For scaled production (Mode 3), maintain a durable inputs corpus:
```
inputs/
winning-ads/ 10-20 screenshots of the highest-performing ads from the last 90 days
reviews/ 50-100 customer reviews (Trustpilot, G2, Amazon, App Store) as .md/.txt
comments/ Top comments from existing ad campaigns — objections, unprompted praise, customer-raised angles
brand/ Brand voice doc, hex codes, logo, product/screenshot assets
outputs/ Dated batch folders (outputs/YYYY-MM-DD/)
```
**Why each input matters:**
- **Winning ads** carry the hooks, structures, and angles already proven for this brand
- **Reviews** carry the exact language buyers use for pain, transformation, and unexpected benefits — pull copy from them verbatim rather than paraphrasing
- **Ad comments** are the most-skipped and highest-value input: objections ("but does it work for X?") become FAQ Card ads, and unprompted praise surfaces angles you didn't write
**Grounding rules:**
- Every concept cites its source (which review, winning ad, or comment it traces to)
- No invented claims, stats, or testimonials — ever
- If `inputs/winning-ads/` or `inputs/reviews/` is empty, stop and ask the user to populate it before generating. Do not generate ungrounded concepts as a fallback.
- Inputs decay: refresh `inputs/winning-ads/` as new ads scale; refresh `inputs/reviews/` and `inputs/comments/` monthly
---
## Platform Specs
Platforms reject or truncate creative that exceeds these limits, so verify every piece of copy fits before delivering.
### Google Ads (Responsive Search Ads)
| Element | Limit | Quantity |
|---------|-------|----------|
| Headline | 30 characters | Up to 15 |
| Description | 90 characters | Up to 4 |
| Display URL path | 15 characters each | 2 paths |
**RSA rules:**
- Headlines must make sense independently and in any combination
- Pin headlines to positions only when necessary (reduces optimization)
- Include at least one keyword-focused headline
- Include at least one benefit-focused headline
- Include at least one CTA headline
### Meta Ads (Facebook/Instagram)
| Element | Limit | Notes |
|---------|-------|-------|
| Primary text | 125 chars visible (up to 2,200) | Front-load the hook |
| Headline | 40 characters recommended | Below the image |
| Description | 30 characters recommended | Below headline |From boarlabsxyz/skills, MIT.
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Signals
- Stars
- 0
- Forks
- 0
- Open issues
- 0
- Last commit (this folder)
- Oct 21, 2026 (9 days ago)
From GitHub (fetched Oct 24, 2026).
Details
- Version
- 2.12.1
- License
- MIT
- Repository
- github.com/boarlabsxyz/skills
- First seen
- Oct 24, 2026
- Last checked
- Oct 24, 2026
- Source
- GitHubgithub-graphql
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Cite this page
chs_ad-creative skill. Agent Mart. https://agentmart.dev/skills/boarlabsxyz-chs-ad-creative (last updated 2026-10-24)