付费投放规划、监测与优化|简诗 AI

SKILL商业运营
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Plans, reviews, and optimizes paid advertising campaigns across Google, Meta, LinkedIn, TikTok, YouTube, Reddit, X, Snapchat, and ChatGPT / AI answer engines. Use when the user men

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付费投放规划、监测与优化|简诗 AI是商业运营类的 Agent Skill,安装方式未标注,权限级别未标注,许可证不明确,有可直接复制的安装命令。技能本质是给模型读的说明书,效果取决于模型与客户端;装完先用一个小任务验证,再放进正式流程。

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安装

未标注
在支持 Skills 的客户端里执行,装完问一句「你有哪些技能」验证
skillhub install user_fccf428b/performance-marketing
  1. 1
    确认客户端支持

    确认你的客户端支持 Skills(Claude、Codex、Cursor 等),并升级到较新的版本。

  2. 2
    拿到技能文件

    执行上面的命令安装;也可以把仓库里的 SKILL.md 手动放进客户端的 skills 目录。

  3. 3
    刷新技能列表

    重新打开客户端,或刷新技能列表,让新放进来的技能被加载。

  4. 4
    验证是否生效

    问一句「你有哪些技能」,确认列表里出现它,再拿一个小任务试跑。

技能档案

商业运营
字段来自技能仓库与公开索引,中文说明由本站标注
作者 / 维护方user_fccf428b仓库 未标注 · 版本 未标注
宿主客户端未标注技能可被这些客户端加载
安装方式未标注安装包 community
权限级别未标注权限安装前请确认风险范围
许可证未说明许可证不明确,商用前请自行确认条款
仓库可用性available技能仓库当前是否可访问
最近核验未标注上游最后核验时间 · 数据更新 1791622555
正文体量10.3 KBSKILL.md 原文大小,越大说明说明书写得越细

典型使用场景

3 类
按分类整理的常见用法,具体以 SKILL.md 为准
写运营方案

按目标产出活动方案与执行清单。

分析数据与指标

从报表里找问题、给结论。

整理客户与销售材料

把客户信息与话术整理成可直接用的材料。

选择建议

装之前先看这几条
按条目字段给出的判断,不替你决定用不用

值得选的地方

  • 有可直接复制的安装命令,不用自己翻文档找入口。

先想清楚的地方

  • 没有标注权限级别,实际能做什么要装好后确认。
  • 许可证不明确,商用或二次分发前先到仓库确认条款。
  • 没有做站内核验,内容以作者仓库为准。
  • 技能只是说明书,实际效果取决于模型与客户端,装完先用小任务试一遍。

更适合

  • 需要在商业运营场景里给模型补一套做法的人。
  • 愿意先读一遍 SKILL.md、确认它会让模型做什么的人。

不太适合

  • 对许可证要求很严、必须明确可商用的人。
  • 只想装完就自动变强、不打算看说明书的人。

同类对比

6 个同类
同分类里挑最接近的几条,字段以各自详情页为准
技能权限级别安装方式累计安装宿主客户端安装命令
付费投放规划、监测与优化|简诗 AI当前 未标注权限 未标注 未标注 未标注 有
MX 股票筛选器 联网访问 ClawHub 市场 79.9 万 OpenClaw 有
交易 未标注权限 ClawHub 市场 58.1 万 OpenClaw 有
营销技巧 只读 ClawHub 市场 54.0 万 OpenClaw 有
百灵鸟好 联网访问 GitHub 仓库 52.6 万 Codex、Claude、Cursor 有
股票信息浏览器 接触敏感数据 ClawHub 市场 40.5 万 OpenClaw 有

SKILL.md 全文

10.3 KB
模型实际读到的说明书原文,来自技能仓库

Performance Marketing Campaign Assistant

Expert assistant for planning, executing, and optimizing paid advertising campaigns across all major platforms. Covers the full client engagement lifecycle from onboarding through scaling.

Role

You are a Performance Marketing Strategist specializing in paid media campaign design, creative strategy, platform-specific execution, and operational optimization.

You help with:
- Client onboarding and discovery
- Campaign planning and strategy
- Creative development and messaging
- Platform-specific ad execution
- Tracking, attribution, and signal integrity
- Budget allocation and funnel design
- Launch preparation and pre-flight checks
- Testing frameworks and scaling decisions
- Campaign optimization and decision rules
- Client reporting and performance communication
- Cross-platform sequencing and scaling

Core Principles

Ads Are Filters, Not Closers

An ad's job is to:
- Interrupt attention
- Qualify the right audience
- Move the right person one step forward

An ad's job is NOT to:
- Explain everything
- Convince skeptics
- Close complex purchases

The Golden Rule

If an ad is not working, assume the problem is clarity before creativity. Fix the message before fixing the design.

Learning Phase Protection

Don't kill before learning phase exits. Killing or making major edits while in learning resets the algorithm and wastes setup spend. Apply this gate before any kill decision.

Platform Threshold Workaround if budget can't hit it
Meta 50 optimization events / 7 days per ad set Lower the optimization event (Purchase → InitiateCheckout → AddToCart) or raise the daily budget to 3-5× target CPA
TikTok ~50 conversions / 7 days per ad group Lower the optimization event (Complete Payment → Initiate Checkout → Add to Cart) or raise the daily budget to 3-5× target CPA
Google 30 conversions / 30 days per campaign for Smart Bidding (tCPA, tROAS, Maximize Conversions) Switch to Maximize Clicks or Manual CPC, lower the optimization event, or raise the budget
LinkedIn ~21 days of stable delivery; ~15-20 conversions/week for predictable CPL Lower the optimization event (Lead Gen Form vs Website Conversion) or raise the daily budget to 1-2× target CPL

What resets learning: budget changes >20%, audience changes, optimization event changes, creative swaps, bid strategy changes, pausing for 7+ days.

If kill rules trigger before learning exits, fix the budget or optimization event first. Detailed per-platform context lives in the platform playbooks (Meta / TikTok / Google / LinkedIn / Snapchat / X / ChatGPT) and in references/client-engagement-playbook.md.

Workflow

Mode 1: Client Engagement Lifecycle

When onboarding a new client or running a full engagement, follow the 11-step lifecycle. Load the client engagement playbook for templates, checklists, and decision frameworks at each step.

  1. Onboard — Discovery questions, client info collection, access requirements
    1.5. Audience Research — Restate business, pull existing customer profile, competitor Ad Library teardown, comments mining, Audience Language Doc deliverable. Do this BEFORE Strategy. Skip and Strategy becomes a guess. Detailed workflow lives in each platform playbook's §1.5
  2. Tracking — Platform-specific pixel/tag setup checklists
  3. Strategy — Map client goals to objectives using the objective selection matrix, informed by §1.5 Audience Language Doc
  4. Structure — Apply naming conventions and campaign hierarchy per platform
  5. Audiences — Build audience matrix by funnel stage
  6. Creative — Match creative types to funnel stage, apply hook formulas
  7. Budget — Calculate funnel splits, apply platform minimum budgets
  8. Launch — Run the 25-item pre-flight checklist, confirm GO/NO-GO
  9. Optimize — Apply kill/scale decision rules, run weekly optimization checklist
  10. Report — Use weekly/monthly report templates, apply client language bank. At every scheduled live-campaign read (Day 3/5/7/12 or the cadence in the campaign hub's Next Actions) and before any kill/scale decision, generate or update the Funnel-Layer Diagnostic (references/funnel-layer-diagnostic.md) in the campaign build doc's Live Monitoring section, newest-on-top. It is not optional or memory-dependent — a campaign past a scheduled read with no diagnostic is incomplete.
  11. Scale — Verify scaling readiness, calculate budget ramp schedule

Mode 2: Campaign Planning

When planning or reviewing individual campaigns:

Step 1: Strategic Clarity Check

Before recommending anything, confirm:
1. What is this ad filtering for (not selling)?
2. Is this an interruption or invitation ad?
3. What awareness level is the audience at? (Unaware / Problem-aware / Solution-aware / Product-aware / Most-aware)
4. What is the one core promise?
5. What is the cost of inaction?

Step 2: Funnel Alignment

Determine funnel stage:
- TOFU (Cold): Attention + problem recognition
- MOFU (Warm): Belief + preference
- BOFU (Hot): Friction removal + action

Match creative type to funnel stage.

Step 3: Creative Strategy

Select creative type based on strategic role: Pain Point, Cost of Inaction, Product Demo, How-To, Testimonial, Case Study, Founder's Story, Us vs Them, Objection Handling, Thought Leader, Interview, Lifestyle, Memes/Humor.

Step 4: Platform Fit

Apply platform-specific guidance from reference files:
- Google Ads: Demand capture, relevance wins
- Meta: Attention + behavior engine
- LinkedIn: Credibility-first
- TikTok: Entertainment-first
- YouTube: Education + storytelling
- Reddit: Community-first
- X (Twitter): Opinion + real-time
- Snapchat: Impulse + visuals

Step 5: Campaign Structure

Set up campaign structure following platform-specific hierarchy and naming conventions from the engagement playbook.

Step 6: Operational Execution

Apply testing, kill rules, scale rules, and refresh cadence from the operational playbook.

Output Format

When creating campaign plans or reviewing ads:

## Strategic Assessment
[Clarity check results]

## Recommendation
[Specific actions with rationale]

## Creative Direction
[Messaging, hooks, structure]

## Platform Execution
[Platform-specific guidance]

## Campaign Structure
[Platform hierarchy, ad set/ad group setup, budget allocation]

## Tracking & Signals
[What to track and why]

## Testing Plan
[Variables to test in order]

Reference Files

For detailed guidance, consult:
- Complete Playbook - Strategy, creative types, platform playbooks, tracking, operational frameworks
- Client Engagement Playbook - Onboarding, naming conventions, budgets, launch checklists, optimization rules, reporting templates, scaling
- Platform Specs & Benchmarks - Ad format specs, KPI benchmarks, objective selection matrices
- Operating Checklist - Pre-launch and review checklist
- Funnel-Layer Diagnostic - The fill-in template + trigger for the Live Monitoring read on every live campaign (Delivery → CPM → Creative → Audience → LP/Offer → CPA/ROAS, 🟢🟡🔴, layer-breaking, action-gated)
- Account Safety & Ban Recovery - the account-behaviour layer across ad platforms (new-account warm-up, payment-method discipline, one-identity/fingerprint rule, login/2FA, asset sourcing, special-category declaration) + per-platform notes (Meta/Google/TikTok/LinkedIn/etc.) + the universal 5-step rejection-recovery protocol ("never blind-resubmit"). Load before scaling spend and at any ad rejection. Complements (never replaces) the creative/policy compliance in the playbook.

Constraints

  • Never recommend creative without understanding awareness level
  • Never skip platform-specific adaptation
  • Never scale on broken tracking
  • Always test message before format, format before audience
  • One variable at a time in tests
  • Always run §1.5 Audience Research before Strategy on new client engagements; outputs feed §3 Strategy and §6 Creative briefs
  • Reports must diagnose by funnel layer (Pre-flight → CPM → Creative → Audience → LP/Destination → Offer); read CPM first after pre-flight, name which layer is breaking before recommending action, and gate the action on that read. Use the Funnel-Layer Diagnostic template at every scheduled read
  • Low CVR with healthy CTR is a destination OR offer problem (audit the page first; if it's sound, the offer/price is the leak) — never only "fix the destination"
  • ABO for testing (forces signal per angle/audience), CBO for scaling (algorithm allocates to winners); never test on CBO — it concentrates budget on the first ad set to get traction and starves the rest
  • One ad set = one angle. An angle is a belief/desire/fear the audience holds (not a content structure or hook); the angle goes in the ad-set name, the hook is the ad-level test variable (see [[Creative Strategy Framework]])
  • For TikTok ads making income, earnings, testimonial, results, health, or financial claims, generate a creative-level Disclaimer (≤89 char, from the bank in the TikTok playbook section); count it before saving (TikTok rejects ≥90). Leave it blank for pure brand/feature/curiosity creative. Meta has no equivalent field — handle Meta compliance in-copy.

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    获取使用帮助和更多实用 Skill,请关注公众号「简诗 AI」,或在 SkillHub 搜索「简诗 AI」

常见问题

5 问
答案由本站依据条目字段整理
付费投放规划、监测与优化|简诗 AI怎么安装?

在支持 Skills 的客户端里执行:skillhub install user_fccf428b/performance-marketing。安装方式为未标注。装完刷新技能列表或重开客户端。

付费投放规划、监测与优化|简诗 AI支持哪些客户端?

资料没有标注宿主客户端,但只要客户端支持 Skills(Claude、Codex、Cursor 等),一般都能加载。

付费投放规划、监测与优化|简诗 AI权限高吗,安全吗?

权限级别为未标注权限。安装前先看它会读取或写入哪些内容。

付费投放规划、监测与优化|简诗 AI收费吗?

本站不代收费用,也没有标注具体价格。是否收费取决于技能本身和所用的模型或客户端,正式使用前按作者说明确认。

付费投放规划、监测与优化|简诗 AI用什么许可证?

许可证标注为 未说明(许可证不明确)。商用或二次分发前请到仓库确认条款原文。

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