固定上游版本 7868cb9251fa,包含 12 个文件。 加搜已生成可下载技能包、原始文件镜像及 7 种 Agent 安装页面。
海外广告投放 · ad-creative
广告创意批量生产 Skill
广告创意批量生产会把品牌素材、买家评论和历史数据转化成符合各平台字数限制的批量广告文案与短视频脚本。
当需要为 Google 或 Meta 批量制作广告变体,或基于 ROAS 数据做广告迭代时使用。这套方法会读取历史跑量广告和真实买家评论,提炼出不同的文案角度,并逐条核对字数。产出的物料可直接导入广告后台进行素材测试。
WHAT IT SOLVES
解决的营销问题
广告创意批量生产会把品牌素材、买家评论和历史数据转化成符合各平台字数限制的批量广告文案与短视频脚本
广告创意批量生产会把品牌素材、买家评论和历史数据转化成符合各平台字数限制的批量广告文案与短视频脚本。跑完你拿到的是包含标题、描述和正文且符合各平台字数限制的 CSV 批量上传表格,中间一共 8 步。
最适合的真实场景
- 01
海外广告投手需要为 Google RSAs 写满 15 条不同角度的标题与 4 条描述
- 02
DTC 品牌操盘手根据现有 Meta 广告的点击率数据做下一批迭代素材
- 03
效果广告优化师把亚马逊与 G2 的高赞买家评论提取成 Facebook 静态图文案
- 04
广告美术为测试跑量素材策划 iOS 原生聊天气泡与备忘录 reveal 视频脚本
- 05
品牌营销人员用历史跑量广告截图与品牌视觉规范生成 50 条静态广告版式
- 06
优化师把跑量差的广告素材提取出来分析败因并测试全新的文案角度
你要先准备的资料
- 过去 90 天内 ROAS 或 CTR 排名前十的广告素材截图与对应的数据报表
- 包含 50 到 100 条真实客户评价的 txt 或 md 格式文件,需要剔除刷单评价
- 现有广告的评论区留言记录,特别是客户提出的异议与自发好评
- 包含卖点、目标受众痛点描述以及禁用词清单的品牌视觉规范文档
- 各平台广告后台的只读权限或导出的 CSV 交接文档,用于核对历史表现
跑完你会拿到什么
- 包含标题、描述和正文且符合各平台字数限制的 CSV 批量上传表格
- 按痛点、结果、从众等角度分类的文案变体 Markdown 文档
- 15 种静态广告版式的文案填充方案,每条文案附带原评论或原广告引用出处
- 带分镜时间轴、旁白文本和画面动作说明的短视频脚本方案
- 记录当前测试轮次、优胜素材规律与停用角度的迭代日志文档
METHOD
Skill 工作流程
采集基础素材 → 诊断跑量数据 → 划分文案角度 等 8 个环节
一共 8 步。其中 7 项能力决定了换个 AI 会不会更麻烦。
- 采集基础素材收集过去 90 天跑量最好的 10 到 20 条广告截图,以及包含 50 到 100 条客户评价的 txt 或 md 格式文件,提取买家真实原话作为基础文案库。
- 诊断跑量数据读取现有广告的 CTR 与 ROAS 数据报表,对比跑量好与跑量差的素材,分离出产生转化的文案句式、痛点方向和字数规律。
- 划分文案角度基于受众痛点与认知阶段,设定 3 到 5 个互不重叠的文案切入角度,比如痛点切入、结果展示、从众背书或是竞品对比。
- 生成变体文案围绕设定好的角度产出多条变体文案,替换同义词、具体数字或语气,把买家评论里的原话直接填入文案中。
- 校验平台限制逐条核对各平台的字符数限制,比如 Google 标题限制 30 字符、描述限制 90 字符,超出字数的文案直接截断并附带修改版。
- 排布静态版式把写好的文案填入 15 种静态广告模板,比如对比图、数据高亮图或创始人留言图,每张图都标注对应的文案来源。
- 撰写视频脚本针对 iOS 原生聊天气泡或无声动效视频,按秒数拆分镜头,写出每一句旁白、对应的画面动作与字幕提示。
- 整理交付表格把文案和分镜打包成结构化表格,比如直接生成可导入后台的 CSV 批量上传文件,或者带日期和来源索引的 Markdown 文档。
这个 Skill 用到的能力: 打开网页取正文读本地资料中文办公文档批处理页面预览运行脚本写本地文件 。不同 AI 对这些能力的支持程度不一样,所以同一个 Skill 换个 AI,有几步做法会变。
WORKED EXAMPLE
业务示例
DTC 家居品牌 Meta 静态图文案批量化测试
DTC 家居品牌 Meta 静态图文案批量化测试
一个海外家居品牌需要测试新一批 Meta 静态图素材。团队手上有一份包含 200 条亚马逊好评的 txt 文件,以及过去三个月 CTR 表现最好的 15 条历史广告截图。优化师需要在不虚构卖点的前提下,输出 30 条新图文案,并要求每一条都能追溯到具体客户评论。最终交付物还要包括可直接提交给设计团队的排版说明。
- 从亚马逊评价 txt 文件中提取出现频率最高的痛点词与结果词
- 对照历史跑量广告截图拆解其标题结构与描述字数规律
- 基于提取的高频词写 30 条变体文案并匹配 6 种不同的切入角度
- 把 30 条文案填入 15 种静态广告模板中,并标注每条文案的评论出处
- 对照 Meta 广告字符数限制截断超字数文案并打包 CSV 文件
预期结果:交付了一份包含 30 条按角度分类的文案表,每条文案标注了源自哪一条具体买家评论。同时交付了 15 种版式的文案填充指南,其中包含图片主视觉建议。优化师还需要人工检查品牌商标词拼写是否准确,并决定最终使用哪 10 条进行排期测试。
PITFALLS · VERIFICATION
能力边界与常见问题
文案直接超出 Google RSAs 的 30 字符标题限制导致无法直接粘贴使用
最常踩的坑
- 文案直接超出 Google RSAs 的 30 字符标题限制导致无法直接粘贴使用
- 把买家评论里的口语化表达强行改成书面语,丢失了原本的转化吸引力
- 为了凑够 15 条 RSA 标题,生成了 3 条以上意思雷同的废话文案
- 视频脚本里的聊天气泡画面时长过短,导致后期配音与字幕完全对不上
- 引用了没有经过法务确认的买家原话,导致广告触犯平台合规政策
怎么确认这次跑对了
- 已经形成可检查的包含标题、描述和正文且符合各平台字数限制的 CSV 批量上传表格,关键判断能回到输入资料或过程证据。
- 已经形成可检查的按痛点、结果、从众等角度分类的文案变体 Markdown 文档,关键判断能回到输入资料或过程证据。
- 已经形成可检查的15 种静态广告版式的文案填充方案,每条文案附带原评论或原广告引用出处,关键判断能回到输入资料或过程证据。
- 已逐项检查「文案直接超出 Google RSAs 的 30 字符标题限制导致无法直接粘贴使用」等高频问题,并记录需要人工确认的下一步。
广告创意批量生产 Skill适合哪些岗位使用?
海外广告投手、效果广告优化师、DTC 品牌操盘手、广告美术。典型场景包括海外广告投手需要为 Google RSAs 写满 15 条不同角度的标题与 4 条描述;DTC 品牌操盘手根据现有 Meta 广告的点击率数据做下一批迭代素材;效果广告优化师把亚马逊与 G2 的高赞买家评论提取成 Facebook 静态图文案。
开始前需要准备什么资料?
至少需要过去 90 天内 ROAS 或 CTR 排名前十的广告素材截图与对应的数据报表、包含 50 到 100 条真实客户评价的 txt 或 md 格式文件,需要剔除刷单评价、现有广告的评论区留言记录,特别是客户提出的异议与自发好评。资料越具体,结果越能直接用于决策。
最后能得到什么可检查的结果?
包含标题、描述和正文且符合各平台字数限制的 CSV 批量上传表格、按痛点、结果、从众等角度分类的文案变体 Markdown 文档、15 种静态广告版式的文案填充方案,每条文案附带原评论或原广告引用出处。每项都可以逐条核对来源和数字。
哪些情况下结果会不可靠?
文案直接超出 Google RSAs 的 30 字符标题限制导致无法直接粘贴使用;把买家评论里的口语化表达强行改成书面语,丢失了原本的转化吸引力。出现这些情况时需要人工复核。
支持哪些 AI Agent?
已适配 WorkBuddy、OpenClaw、Hermes Agent、Codex、Claude Code、TRAE、ZCode 共 7 种,每种都有独立的安装说明和能力对照。
ORIGINAL SOURCE
完整 Skill 内容与版本资料
12 个原始文件,207 个文档章节,固定在 7868cb92
上游原文完整保留在加搜服务器上,可逐节查看,也可以直接下载。 当前镜像共 12 个文件、159.1 KB。
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.
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. 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 marketing-loops. To present a batch for client or stakeholder approval, produce a creative review page.
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; for hook generation and funnel-stage diagnosis inside any mode, load 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/orinputs/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; refreshinputs/reviews/andinputs/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 |
| URL display link | 40 characters | Optional |
LinkedIn Ads
| Element | Limit | Notes |
|---|---|---|
| Intro text | 150 chars recommended (600 max) | Above the image |
| Headline | 70 chars recommended (200 max) | Below the image |
| Description | 100 chars recommended (300 max) | Appears in some placements |
TikTok Ads
| Element | Limit | Notes |
|---|---|---|
| Ad text | 80 chars recommended (100 max) | Above the video |
| Display name | 40 characters | Brand name |
Twitter/X Ads
| Element | Limit | Notes |
|---|---|---|
| Tweet text | 280 characters | The ad copy |
| Headline | 70 characters | Card headline |
| Description | 200 characters | Card description |
For detailed specs and format variations, see references/platform-specs.md.
Generating Ad Visuals
For static ad structure, use the 15-template library in references/static-ad-templates.md — layout frameworks (Us vs. Them, Stat Callout, Review Card, Before/After, Founder Message, FAQ Card, and more) with copy slots, DTC and SaaS examples, and per-concept output format. Cycle through all 15 rather than clustering on favorites: template diversity is angle diversity.
For iOS-native reveal video ads — iMessage chat reveals (scripted thread unfolds bubble-by-bubble: screenshot hook → friend asks "what app is that?" → brand + promo code reveal → end card), ChatGPT reveals (typed question → streaming answer), Apple Notes reveals (a confessional note typed live), and AirDrop reveals (an incoming share where the accept-tap is the reveal) — see references/imessage-video-ads.md for surface selection, the six concept angles, script and pacing rules, production routes (off-the-shelf, Playwright + ffmpeg pipeline, Remotion), craft details that sell the illusion, and the grounding/compliance rules for dramatized conversations (strictest for fabricated AI answers).
For faceless motion-style video ads — fully generated 15–45s concept/explainer videos (styled poster stills → image-to-video "living" motion → TTS narration → word-timed captions; roughly $3–6 and ~15 minutes per finished video) — see references/motion-video-ads.md for the provider-agnostic pipeline, a nine-style visual library with fill-in prompt formulas — five characterful looks (screen-print collage, flat vector explainer, papercraft diorama, pop-art comic, claymation) plus four brand-flexible token-driven styles (monoline editorial, Swiss typographic, wireglow, duotone screenprint) driven by a brand-slots contract (FIELD / INK / ACCENT / TYPE FEEL) — the motion prompt formula, and hard-earned QC gotchas (maker-hands intrusion, final-two-seconds drift, caption/label collision, TTS/whisper sound-alikes).
For image and video generation tools, see references/generative-tools.md for the complete guide covering:
- Image generation — Nano Banana Pro (Gemini), Flux, Ideogram for static ad images
- Video generation — Veo, Kling, Runway, Sora, Seedance, Higgsfield for video ads
- Voice & audio — ElevenLabs, OpenAI TTS, Cartesia for voiceovers, cloning, multilingual
- Code-based video — Remotion for templated, data-driven video at scale
- Platform image specs — Correct dimensions for every ad placement
- Cost comparison — Pricing for 100+ ad variations across tools
Recommended workflow for scaled production:
- Generate hero creative with AI tools (exploratory, high-quality)
- Build Remotion templates based on winning patterns
- Batch produce variations with Remotion using data feeds
- Iterate — AI for new angles, Remotion for scale
Generating Ad Copy
Step 1: Define Your Angles
Before writing individual headlines, establish 3-5 distinct angles — different reasons someone would click. Each angle should tap into a different motivation.
Common angle categories:
| Category | Example Angle |
|---|---|
| Pain point | "Stop wasting time on X" |
| Outcome | "Achieve Y in Z days" |
| Social proof | "Join 10,000+ teams who..." |
| Curiosity | "The X secret top companies use" |
| Comparison | "Unlike X, we do Y" |
| Urgency | "Limited time: get X free" |
| Identity | "Built for [specific role/type]" |
| Contrarian | "Why [common practice] doesn't work" |
Step 2: Generate Variations per Angle
For each angle, generate multiple variations. Vary:
- Word choice — synonyms, active vs. passive
- Specificity — numbers vs. general claims
- Tone — direct vs. question vs. command
- Structure — short punch vs. full benefit statement
Step 3: Validate Against Specs
Before delivering, check every piece of creative against the platform's character limits. Flag anything that's over and provide a trimmed alternative.
Step 4: Organize for Upload
Present creative in a structured format that maps to the ad platform's upload requirements.
Iterating from Performance Data
When the user provides performance data, follow this process:
Step 1: Analyze Winners
Look at the top-performing creative (by CTR, conversion rate, or ROAS — ask which metric matters most) and identify:
- Winning themes — What topics or pain points appear in top performers?
- Winning structures — Questions? Statements? Commands? Numbers?
- Winning word patterns — Specific words or phrases that recur?
- Character utilization — Are top performers shorter or longer?
Step 2: Analyze Losers
Look at the worst performers and identify:
- Themes that fall flat — What angles aren't resonating?
- Common patterns in low performers — Too generic? Too long? Wrong tone?
Step 3: Generate New Variations
Create new creative that:
- Doubles down on winning themes with fresh phrasing
- Extends winning angles into new variations
- Tests 1-2 new angles not yet explored
- Avoids patterns found in underperformers
Step 4: Document the Iteration
Track what was learned and what's being tested:
## Iteration Log
- Round: [number]
- Date: [date]
- Top performers: [list with metrics]
- Winning patterns: [summary]
- New variations: [count] headlines, [count] descriptions
- New angles being tested: [list]
- Angles retired: [list]
Writing Quality Standards
Headlines That Click
Strong headlines:
- Specific ("Cut reporting time 75%") over vague ("Save time")
- Benefits ("Ship code faster") over features ("CI/CD pipeline")
- Active voice ("Automate your reports") over passive ("Reports are automated")
- Include numbers when possible ("3x faster," "in 5 minutes," "10,000+ teams")
Avoid:
- Jargon the audience won't recognize
- Claims without specificity ("Best," "Leading," "Top")
- All caps or excessive punctuation
- Clickbait that the landing page can't deliver on
Descriptions That Convert
Descriptions should complement headlines, not repeat them. Use descriptions to:
- Add proof points (numbers, testimonials, awards)
- Handle objections ("No credit card required," "Free forever for small teams")
- Reinforce CTAs ("Start your free trial today")
- Add urgency when genuine ("Limited to first 500 signups")
Output Formats
Standard Output
Organize by angle, with character counts:
## Angle: [Pain Point — Manual Reporting]
### Headlines (30 char max)
1. "Stop Building Reports by Hand" (29)
2. "Automate Your Weekly Reports" (28)
3. "Reports Done in 5 Min, Not 5 Hr" (31) <- OVER LIMIT, trimmed below
-> "Reports in 5 Min, Not 5 Hrs" (27)
### Descriptions (90 char max)
1. "Marketing teams save 10+ hours/week with automated reporting. Start free." (73)
2. "Connect your data sources once. Get automated reports forever. No code required." (80)
Bulk CSV Output
When generating at scale (10+ variations), offer CSV format for direct upload:
headline_1,headline_2,headline_3,description_1,description_2,platform
"Stop Manual Reporting","Automate in 5 Minutes","Join 10K+ Teams","Save 10+ hrs/week on reports. Start free.","Connect data sources once. Reports forever.","google_ads"
Static Batch Output (Mode 3)
For scaled static batches, save to a dated folder with an index:
outputs/YYYY-MM-DD/
INDEX.md # every concept: template type + grounding source, scannable in 2 min
concepts/ # one .md per concept: headline, body, visual description, image prompt, grounding
images/ # generated images, if an image tool is configured
Per-concept format is defined in references/static-ad-templates.md. The human workflow this supports: open the folder, scan INDEX.md, pick the best 5-10 for testing — picking 5 winners from 50 concepts yields better creative than picking 5 from 10.
Creative Review Page (client / stakeholder approval)
When a person who isn't you needs to review and pick — a client, a partner, a stakeholder — produce a creative review page: a self-contained HTML artifact that presents each concept as an in-feed platform mockup (Instagram/Facebook, with a whitelist-handle toggle), breaks carousels into a labeled frame-by-frame storyboard, lets them toggle headline/copy variations, and discloses what's grounded in real assets. It's the visual upgrade to INDEX.md — a decision made off one link instead of by reading markdown. The template ships at assets/creative-review-template.html (one file, no build, hostable anywhere); populate its DATA object from your generated concepts. Full data model, grounding rules (the disclosure block is required), and delivery in references/creative-review-page.md.
Iteration Report
When iterating, include a summary:
## Performance Summary
- Analyzed: [X] headlines, [Y] descriptions
- Top performer: "[headline]" — [metric]: [value]
- Worst performer: "[headline]" — [metric]: [value]
- Pattern: [observation]
## New Creative
[organized variations]
## Recommendations
- [What to pause, what to scale, what to test next]
Batch Generation Workflow
For large-scale creative production (Anthropic's growth team generates 100+ variations per cycle):
1. Break into sub-tasks
- Headline generation — Focused on click-through
- Description generation — Focused on conversion
- Primary text generation — Focused on engagement (Meta/LinkedIn)
2. Generate in waves
- Wave 1: Core angles (3-5 angles, 5 variations each)
- Wave 2: Extended variations on top 2 angles
- Wave 3: Wild card angles (contrarian, emotional, specific)
3. Quality filter
- Remove anything over character limit
- Remove duplicates or near-duplicates
- Flag anything that might violate platform policies
- Ensure headline/description combinations make sense together
Common Mistakes
- Writing headlines that only work together — RSA headlines get combined randomly
- Ignoring character limits — Platforms truncate without warning
- All variations sound the same — Vary angles, not just word choice
- No CTA headlines — RSAs need action-oriented headlines to drive clicks; include at least 2-3
- Generic descriptions — "Learn more about our solution" wastes the slot
- Iterating without data — Gut feelings are less reliable than metrics
- Generating without grounding — Ungrounded concepts read like every other ad in the feed; feed the skill winning ads, reviews, and comments first
- Skipping the comments input — Ad comments hold the objections and angles customers raise themselves; those usually convert best
- Testing too many things at once — Change one variable per test cycle
- Retiring creative too early — Allow 1,000+ impressions before judging
Tool Integrations
For pulling performance data and managing campaigns, see the tools registry.
| Platform | Pull Performance Data | Manage Campaigns | Guide |
|---|---|---|---|
| Google Ads | google-ads campaigns list, google-ads reports get |
google-ads campaigns create |
google-ads.md |
| Meta Ads | meta-ads insights get |
meta-ads campaigns list |
meta-ads.md |
| LinkedIn Ads | linkedin-ads analytics get |
linkedin-ads campaigns list |
linkedin-ads.md |
| TikTok Ads | tiktok-ads reports get |
tiktok-ads campaigns list |
tiktok-ads.md |
Workflow: Pull Data, Analyze, Generate
# 1. Pull recent ad performance
node tools/clis/google-ads.js reports get --type ad_performance --date-range last_30_days
# 2. Analyze output (identify top/bottom performers)
# 3. Feed winning patterns into this skill
# 4. Generate new variations
# 5. Upload to platform
Related Skills
- ads: For campaign strategy, targeting, budgets, and optimization
- marketing-loops: For running static batch generation on a recurring cadence (the daily-creative-drop loop)
- customer-research: For mining reviews and comments when building the grounded inputs corpus
- copywriting: For landing page copy (where ad traffic lands)
- ab-testing: For structuring creative tests with statistical rigor
- marketing-psychology: For psychological principles behind high-performing creative
- copy-editing: For polishing ad copy before launch
当前镜像保留 12 个文件,共 159.1 KB。点击文件名可查看加搜服务器上的原始内容。
| 文件 | 大小 | 内容指纹 |
|---|---|---|
| SKILL.md | 20,854 B | e874d7bde2f5… |
| UPSTREAM_LICENSE.txt | 1,069 B | b70d71e24e40… |
| assets/creative-review-template.html | 24,459 B | 12f7ec21a574… |
| evals/evals.json | 16,348 B | d5f598144384… |
| references/creative-review-page.md | 9,103 B | dbf69e95e79c… |
| references/creative-roadmap.md | 9,010 B | a0be737841d8… |
| references/generative-tools.md | 24,104 B | c95da2868f39… |
| references/hook-system.md | 8,339 B | fc5db396eb43… |
| references/imessage-video-ads.md | 20,359 B | 89ed0d9a8802… |
| references/motion-video-ads.md | 11,801 B | c64e83199f03… |
| references/platform-specs.md | 6,525 B | de6975316107… |
| references/static-ad-templates.md | 10,968 B | 8e066632e044… |
评价将按 Skill 与版本归档,帮助营销人了解真实任务中的使用体验。敬请期待。
来源与版本声明
本页面由加搜科技整理业务说明并托管安装文件。原始 Skill 来源渠道:GitHub; 原始项目名称:ad-creative; 固定版本:7868cb9251fa; 许可证:MIT。技能包内保留完整出处和许可证说明。
各 Agent 能力说明参考对应官方文档。页面不提供外部跳转。
INSTALL
三种安装方式
广告创意批量生产 Skill v1.0.0,ZIP 带 SHA256 校验
默认做法是把提示词复制给 AI Agent,让它自己下载并安装。提示词里已经写清要用完整 ZIP、装完报告目录、并先跑一个小任务验证。
METHOD 01 · 交给 AI 自己装
复制提示词
适合大多数情况。Agent 会下载 ZIP、解压、放到正确目录,并在缺少权限时告诉你需要手工做哪一步。
请帮我把「广告创意批量生产 Skill」安装到我正在使用的 AI Agent。 1. 下载完整 Skill ZIP:https://www.vibemarketing.work/packages/skill-ad-creative/1.0.0/skill-ad-creative.zip 注意:网页 HTML 不能当作 Skill 文件安装,必须使用 ZIP 里的完整文件。 2. 解压后保留 SKILL.md 及全部配套文件,按你所用 Agent 的 Skill 目录规则安装。 3. 安装完成后告诉我实际安装目录。 4. 用一个只读小任务验证 Skill 已被识别。 5. 如果你没有联网、下载或写目录权限,请直接告诉我哪几步需要我手工完成。 参考:原始 SKILL.md https://www.vibemarketing.work/raw/skill-ad-creative/SKILL.md;安装指南 https://www.vibemarketing.work/agent-install/skill-ad-creative.md
METHOD 02 · 自己下载
下载完整 ZIP
包内含 SKILL.md 与全部配套文件,附 manifest.json 与 SHA256 校验值,可离线安装与版本冻结。
METHOD 03 · 手动放目录
手动安装
解压 ZIP 后,按所用 Agent 的目录规则放入:
- WorkBuddy
技能 → 添加技能 → 上传技能 → 选择本地技能包 - OpenClaw
openclaw skills install ./skill-ad-creative --as ad_creative_skill - Hermes Agent
mkdir -p ~/.hermes/skills && cp -R ./skill-ad-creative ~/.hermes/skills/ - Codex
mkdir -p ~/.codex/skills && cp -R ./skill-ad-creative ~/.codex/skills/ - Claude Code
mkdir -p ~/.claude/skills && cp -R ./skill-ad-creative ~/.claude/skills/ - TRAE
在 Skills 设置中导入包含 SKILL.md 的 skill-ad-creative 目录;项目级 Skill 可放入 .agents/skills/skill-ad-creative - ZCode
mkdir -p ~/.zcode/skills && cp -R ./skill-ad-creative ~/.zcode/skills/
HTML 业务页面不能直接当作 Skill 文件安装。AI 需要下载完整 ZIP 并保留配套文件。
BY AGENT
适配的 AI Agent
7 个 Agent 里,7 项能力决定了差异
同一个 Skill,换个 AI 做法就不一样。点进去能看到它在这 8 步里能直接跑通几步、哪几步得你自己补、装完先跑什么验证。
- WorkBuddy 广告创意批量生产 Skill 中文办公、本地资料和企业协作
- OpenClaw 广告创意批量生产 Skill 本地工作区、目录化 Skill、命令和批处理
- Hermes Agent 广告创意批量生产 Skill 长任务、消息入口和阶段进度
- Codex 广告创意批量生产 Skill 本地文件、数据、代码和正式交付物
- Claude Code 广告创意批量生产 Skill 项目上下文、文件、终端和 MCP
- TRAE 广告创意批量生产 Skill 营销工作与网站、落地页和程序化 SEO
- ZCode 广告创意批量生产 Skill 长上下文、长任务、项目文件和远程跟进
FURTHER READING
广告创意批量生产 Skill 相关的实操文章
别人做同类任务时踩过的坑和总结,动手前后都值得翻一下。
广告团队用上AI之后,最常见的假进度是:一晚上生成几十条文案和二十张图,全部丢进同一个广告组。后台看起来很忙,结论却读不出来——赢的是开头那句、是证据、是画面,还是出价碰巧变了,分不清。批量生产只有在
用 AI 辅助内容生产不等于把选题丢给模型、把输出直接发布。没有 SOP 的 AI 内容生产通常表现为两种结果:要么输出质量不可控,要么人工修改成本甚至高于从头写。这份 SOP 的目标是建立一套可重复
品牌语气提示词的作用,是把"我们品牌的文案应该是这种感觉"这句模糊要求,翻译成 AI 能逐条对照执行的约束。本文给出一个四层模板:品牌事实、语气维度、改写示例、输出自检。你替换方括号里的变量后即可直接
发布前的第一道关不是错别字,是事实。AI 文章的事实核查按四层走:先看信息来源处于哪个层级,再对价格、版本、功能状态这类时效性条目当天核验,然后逐条审数字与断言,最后把改动写进修订记录。文末附一张可以
出海投放的规划顺序是先目标、再渠道、再预算、最后验素材。业务目标决定渠道组合;预算按“验证优先”分配,小范围跑通再放量;素材上线前过本地化验收清单;开投前再过一遍治理检查。顺序反了——比如先选渠道再想
营销简报怎么写才能让AI产出不跑偏:一份可替换的Brief模板
营销简报(Brief)是 Vibe Marketing 里表达意图的核心输入:AI 产出跑偏,多数时候是简报没写清意图、受众、约束和验收标准。本文给出一份可替换变量的完整 Brief 模板,逐模块拆解
搭配使用
海外社区论坛推广 Skill、专家评审 Skill、导航站收录 Skill、LinkedIn Ads 投放 Skill、TikTok Ads 投放 Skill、TikTok 营销 Skill
按这个 Skill 的产出能不能直接被下一个 Skill 用上来推荐,不是固定名单。多数情况下按顺序跑完一组,比单独用一个效果更好。
海外社区论坛推广 Skill
把论坛发帖和社群邀请的执行规则,整理成包含渠道选择、发帖文案和邀请触点的行动清单。
专家评审 Skill
自动组建 7 到 10 人的虚拟专家团队,对文案、落地页或营销方案进行打分并提出修改建议,直到评分达到 90 分。
导航站收录 Skill
把产品基础信息转为分层的导航站收录档案,按梯队分发到 Product Hunt 与 AI 工具集,获取外链与曝光。
LinkedIn Ads 投放 Skill
为 B2B 获客设计 LinkedIn 广告目标、受众、素材、表单和预算结构。
TikTok Ads 投放 Skill
规划 TikTok 广告格式、受众、像素事件、Spark Ads、素材和预算测试。
TikTok 营销 Skill
为 TikTok 生成适配平台节奏的短视频选题、脚本、字幕、标题和标签。
- 01
海外社区论坛推广 Skill
这个 Skill 产出的copy、creative_matrix,正好是它需要的输入,可以直接接着跑
- 02
专家评审 Skill
这个 Skill 产出的copy、creative_matrix,正好是它需要的输入,可以直接接着跑
- 03
导航站收录 Skill
这个 Skill 产出的copy、creative_matrix,正好是它需要的输入,可以直接接着跑
- 04
LinkedIn Ads 投放 Skill
这个 Skill 产出的copy、creative_matrix,正好是它需要的输入,可以直接接着跑
- 05
TikTok Ads 投放 Skill
这个 Skill 产出的copy、creative_matrix,正好是它需要的输入,可以直接接着跑
- 06
TikTok 营销 Skill
这个 Skill 产出的copy、creative_matrix,正好是它需要的输入,可以直接接着跑