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- 26 条
档案由构建时根据 SKILL.md 与安装命令自动衍生,可能与作者实际意图存在差异。
需要注意: 未限定 allowed-tools,默认拥有全部工具权限。
---
name: ads-meta
description: Meta Ads deep analysis covering Facebook, Instagram, and Threads advertising in the Andromeda +…
category: 通用
runtime: 无特殊运行时
---
# ads-meta 输出预览
## PART A: 任务判断
- 适用问题:通用任务拆解、检查和交付。
- 输入要求:目标材料、限制条件、期望输出和验收方式。
- 证据边界:围绕“Andromeda + GEM + Lattice (2026) / Creative-as-targeting scoring rubric / Entity-ID Clustering Predictor (pre-launch)”读取原文规则,不把推断写成作者承诺。
## PART B: 执行结果
- **01** 任务判断:确认你的需求是否属于通用任务拆解、检查和交付,并标出输入、限制和预期结果。
- **02** 执行计划:优先按“Andromeda + GEM + Lattice (2026) / Creative-as-targeting scoring rubric / Entity-ID Clustering Predictor (pre-launch)”拆成步骤,说明每一步会读取什么、修改什么、产出什么。
- **03** 交付结果:给出可复制的命令、文件改动、检查清单或内容草稿,并说明如何继续迭代。
- **04** 风险边界:结合 读取文件、写入/修改文件、主要在本地完成、通常不需要额外 API Key 给出执行前确认项。
## Running Rules
- 读取文件、写入/修改文件;主要在本地完成;通常不需要额外 API Key。
- 先小样例验证,再放大到真实任务。
- 交付时同时给结果、检查口径和下一步迭代建议。 原文没有稳定的斜杠命令要求。安装验证后通常全局生效,直接在对话里点名这个 Skill 并描述任务即可。
告诉 Agent 目标文件或材料、期望结果、不可改范围、是否允许联网或执行命令。本 Skill 的权限画像是:读取文件、写入/修改文件。
先用一个小任务确认它会围绕“Andromeda + GEM + Lattice (2026) / Creative-as-targeting scoring rubric / Entity-ID Clustering Predictor (pre-launch)”工作;涉及文件或命令时,先看 diff、日志、预览或测试结果。
检查最终产物是否包含明确结果、必要证据和下一步动作;如果输出泛泛而谈,就补充输入、边界和验收标准后重跑。
---
name: ads-meta
description: Meta Ads deep analysis covering Facebook, Instagram, and Threads advertising in the Andromeda +…
category: 通用
source: AgriciDaniel/claude-ads
---
# ads-meta
## 什么时候使用
- 把通用方向的常用动作沉淀成 Agent 可调用的技能 适合处理通用任务拆解、检查、交付和复盘,核心价值是把输入、判断、执行、验证和交付边界固定下来,避免 Agent 泛泛回答。 把任务拆成可执行、可检查、可继续迭代的步骤;通常不需要额外…
- 面向通用任务拆解、检查和交付,优先处理能明确输入、步骤和验收标准的工作。
## 需要提供什么
- 目标材料、目录范围、期望结果和不可改动内容。
- 是否允许联网、执行命令、读写文件或调用外部服务。
## 执行规则
- 围绕「Andromeda + GEM + Lattice (2026) / Creative-as-targeting scoring rubric / Entity-ID Clustering Predictor (pre-launch)」组织步骤,不把推断写成作者事实。
- 读取文件、写入/修改文件;主要在本地完成;通常不需要额外 API Key。
- 先跑小样例,确认结果可检查后再扩大任务范围。
## 输出要求
- 给出最终产物、关键证据、验证方式和下一步动作。
- 信息不足时标记 unknown,不编造命令、平台或依赖。 作者原文负责流程事实;仓库文件负责来源和命令;流狐只补充适用场景、限制和质量判断。
skill "ads-meta" {
输入层 -> 用户目标 + 目标文件 + 禁止范围 + 验收标准
上下文层 -> Andromeda + GEM + Lattice (2026) / Creative-as-targeting scoring rubric / Entity-ID Clustering Predictor (pre-launch)
规则层 -> SKILL.md 触发条件 / 执行顺序 / 输出格式
运行层 -> 无特殊运行时 | 读取文件、写入/修改文件 | 主要在本地完成
安全层 -> 通常不需要额外 API Key + 小任务验证 + diff / 日志复核
输出层 -> 可复制结果 + 检查清单 + 下一步迭代
} Meta Ads Deep Analysis
Andromeda + GEM + Lattice (2026)
Meta's delivery stack was rebuilt across three releases:
- Andromeda (Oct 2025) — ad-retrieval ranking model with 10,000× more model capacity than the previous funnel (Meta Engineering, Dec 2024). Filters the candidate creative set before the auction layer ever sees it.
- GEM (Generative Embedding Model, late 2025) — replaces the feature pipeline. Creative content embeds directly into the targeting space, which is why "creative is the new targeting" is now mechanical truth not slogan.
- Lattice (rolled out late 2025 / early 2026) — sequence-aware optimizer on top of GEM that uses user-action sequences to rank candidate ads.
Net effect: creative diversity is now the #1 performance lever. Ads with Similarity Score >60% (per Confect's measured threshold) get retrieval suppression — the algorithm clusters near-identical creatives and silently limits their delivery. 100 minor variations perform no better than 10 genuinely distinct ones. Prioritize concept / angle / format diversity over variant volume.
Creative-as-targeting scoring rubric
When auditing a creative library against Andromeda's retrieval logic, score across these 5 axes (each 0-2, total 0-10):
| Axis | 0 (Risk) | 1 (OK) | 2 (Strong) |
|---|---|---|---|
| Concept diversity | Single core message / value prop across all assets | 2 distinct messages | 3+ distinct angles (problem-led, social proof, comparison, …) |
| Format diversity | One format (e.g. all static image) | 2 formats | 3+ (image, video, carousel, collection) |
| Visual diversity | One palette / one model / one composition | 2 distinct visual treatments | 3+ visually distinct treatments |
| Hook diversity (video) | All hooks ≤3s look alike | 2 hook patterns | 3+ hook patterns (UGC POV, question, claim, demo, …) |
| Headline diversity | All headlines paraphrase the same line | 2 headline structures | 3+ structures (number-led, question, claim, comparison) |
Score 8-10 = LOW Entity-ID clustering risk. Score 4-7 = MEDIUM risk (some suppression likely). Score 0-3 = HIGH risk (significant retrieval ticket loss).
Entity-ID Clustering Predictor (pre-launch)
Before launch, predict which creatives Meta will cluster. Cluster-mates share retrieval tickets — only one wins per impression opportunity.
Predictor heuristics (apply to every pair of creatives in the launch set):
- Visual fingerprint — same product hero, same model, same backdrop, same lighting → likely cluster. Different products or different visual identities → likely not a cluster.
- Headline fingerprint — same first 4 tokens → likely cluster (e.g. "Save 30% on" + "Save 30% off" + "Save 30% — limited time").
- Body copy fingerprint — same opening sentence, same CTA verb → likely cluster regardless of middle-body differences.
- Video hook fingerprint — same 0-3s shot, same voiceover pattern → likely cluster even if the rest of the video diverges.
- Format mismatch wins — if pair is (static + video) AND visual fingerprint differs, they are not clustered. Crossing format AND visual is a strong diversity signal.
Output: produce a creative-cluster-risk.md deliverable that groups the
launch set into predicted clusters, recommends which creative in each cluster
should ship and which should be cut or rebuilt, and reports the final pre-
launch diversity score (target ≥8/10).
MAPI v25 ASC/AAC Deprecation Detector
Meta Marketing API v25 deprecates the explicit Advantage Shopping Campaigns (ASC) and Advantage App Campaigns (AAC) creation paths — those campaign types are folded into standard Sales / Leads / App objectives where ASC behavior becomes the default configuration. Detection:
- If the account uses MAPI v23 or earlier: ASC/AAC API endpoints will return deprecation warnings before the v25 cutover. Capture and flag them.
- If the account uses MAPI v25+: confirm that previously-ASC campaigns have been migrated to the new objective-default model with the equivalent catalog + budget + existing-customer cap settings preserved.
- If creating new campaigns: use the Sales / Leads / App objective + ASC defaults rather than the legacy ASC/AAC endpoints.
ASC defaults for Sales / Leads / App (2026 behavior)
When Sales / Leads / App objectives are selected, ASC behaviors are now the default. Audit confirms:
- Catalog connection (Sales): product catalog linked and feed health green
- Existing customer cap (Sales): set to 10-25% (default may be too high for high-LTV brands)
- Advantage+ Audience (all three objectives): on by default; only override with manual interest stacks for highly restricted categories
- Advantage+ Creative (all three): text / brightness / music enhancements on by default; if your brand-safety policy requires off, document the exception per ad set
Process
- Collect Meta Ads data (Ads Manager export, Events Manager screenshot, EMQ scores)
- Read
ads/references/meta-audit.mdfor full 50-check audit - Read
ads/references/benchmarks.mdfor Meta-specific benchmarks - Read
ads/references/scoring-system.mdfor weighted scoring - Evaluate all applicable checks as PASS, WARNING, or FAIL
- Calculate Meta Ads Health Score (0-100)
- Generate findings report with action plan
What to Analyze
Pixel / CAPI Health (30% weight)
- Meta Pixel installed and firing on all pages
- Conversions API (CAPI) active (30-40% data loss without it post-iOS 14.5)
- Event deduplication configured (event_id matching, ≥90% dedup rate)
- Event Match Quality (EMQ) ≥8.0 for Purchase event
- All standard events configured (ViewContent, AddToCart, Purchase, Lead)
- Custom conversions created for non-standard events
- Aggregated Event Measurement (AEM) configured for iOS
- Domain verification completed
- Server-side events include customer_information parameters
- Pixel fires with correct currency and value parameters
Creative (30% weight)
- ≥3 creative formats active (image, video, carousel, collection)
- ≥5 creatives per ad set (Meta recommendation)
- Creative fatigue detection: CTR drop >20% over 14 days = FAIL
- Video creative: 15s max for Stories/Reels, 30s max for Feed
- UGC/testimonial creative tested
- Dynamic Creative Optimization (DCO) tested
- Ad copy: headline under 40 chars, primary text under 125 chars
- Creative refresh cadence: every 2-4 weeks for high-spend
Account Structure (20% weight)
- Campaign Budget Optimization (CBO) vs Ad Set Budget (ABO) intentional
- Campaign consolidation: 1-3 campaigns total recommended
- Learning phase health: <30% ad sets in "Learning Limited" (FAIL >50%)
- Budget per ad set: ≥5x target CPA (minimum for learning phase exit)
- Ad set audience overlap <30% (Audience Overlap tool)
- Campaign naming conventions consistent and descriptive
- Advantage+ Sales Campaigns active for e-commerce
- Simplified campaign structure: 1-3 campaigns total (fewer, larger ad sets preferred)
Audience & Targeting (20% weight)
- Prospecting frequency (7-day): <3.0 (WARNING 3-5, FAIL >5)
- Retargeting frequency (7-day): <8.0 (WARNING 8-12, FAIL >12)
- Custom Audiences: website visitors, customer lists, engagement
- Lookalike Audiences: multiple seed sizes tested (1%, 3%, 5%)
- Advantage+ Audience tested vs manual targeting
- Interest targeting: broad enough for algorithm optimization
- Exclusions: purchasers excluded from prospecting, overlap managed
- Location targeting reviewed for relevance
Advantage+ Assessment
If Advantage+ features are in use:
- Advantage+ Sales Campaigns: catalog connected, existing customer cap set
- Advantage+ Audience: performance vs manual audience compared
- Advantage+ Creative: enhancements enabled (text, brightness, music)
- Advantage+ Placements: enabled (let Meta optimize placement mix)
- Budget allocation: Advantage+ campaigns getting fair test budget
Special Ad Categories
If ads are in restricted categories:
- Special Ad Category declared before campaign creation
- Targeting restrictions verified (no ZIP, age 18-65+ only, no Lookalike)
- Creative compliance with category-specific policies
- Read
ads/references/compliance.mdfor full requirements
EMQ Optimization Guide
| EMQ Score | Status | Action |
|---|---|---|
| 8.0-10.0 | Excellent | Maintain current setup |
| 6.0-7.9 | Good | Add more customer_information parameters |
| 4.0-5.9 | Fair | Implement CAPI, improve data quality |
| <4.0 | Poor | Critical: CAPI + Enhanced Matching required |
Key parameters to maximize EMQ:
em(email): highest match rate signalph(phone): second highest match signalfn,ln(first/last name): improves match accuracyct,st,zp(city, state, zip): geographic matchingexternal_id: CRM/user ID for cross-device matching
Key Thresholds
| Metric | Pass | Warning | Fail |
|---|---|---|---|
| EMQ (Purchase) | ≥8.0 | 6.0-7.9 | <6.0 |
| Dedup rate | ≥90% | 70-90% | <70% |
| CTR | ≥1.0% | 0.5-1.0% | <0.5% |
| Creative formats | ≥3 | 2 | 1 |
| Creatives per ad set | ≥5 | 3-4 | <3 |
| Learning Limited | <30% | 30-50% | >50% |
| Budget per ad set | ≥5x CPA | 2-5x CPA | <2x CPA |
Output
Meta Ads Health Score
Meta Ads Health Score: XX/100 (Grade: X)
Pixel / CAPI Health: XX/100 ████████░░ (30%)
Creative: XX/100 ██████████ (30%)
Account Structure: XX/100 ███████░░░ (20%)
Audience: XX/100 █████░░░░░ (20%)
Deliverables
META-ADS-REPORT.md: Full 50-check findings with pass/warning/fail- EMQ improvement roadmap
- Creative fatigue alerts (any creative with CTR declining >20%)
- Quick Wins sorted by impact
- Advantage+ adoption recommendations
Threads Placement
Threads placement GA Jan 2026, 400M+ MAU. Lower CPMs than Feed/Stories. Currently ~0.04% of total spend. Emerging channel. Evaluate:
- Is Threads placement enabled in Advantage+ Placements?
- Monitor CPM and engagement vs other placements
- Early-mover advantage for brands with active Threads presence
先判断是否适合
作者设计意图
作者的方法与取舍
边界和复核