sealeap-amazon-ad-architecture
Build and diagnose a profit-aware Amazon advertising architecture by working backward from stage-level sales and profit goals into inventory, keyword priorities, campaign roles, budgets, and measurable experiments across SP, SB, SBV, SD, keyword targeting, product targeting, and
Supply asset profile
Design and creative production
Design assets, images, video, audio, multimodal media, presentation, and creative production skills.
Scenario
Design and creative
I need my agent to produce design assets, UI directions, presentations, or creative media workflows.
Agent fit
Claude Code + CLI + Codex
Codex, Claude Code, Cursor, CLI, or custom agents.
Install
Ready
npx skills add xjli360/sealeap-amazon-ad-skills --skill sealeap-amazon-ad-architecture
Maintenance
fresh
Pushed today
Risk
Needs review
Financial research output is not financial advice; require human review before any live investment decision
GitHub quality
16
59/100 Quality · 72/100 Trust
Coverage tags
Review notes
Financial research output is not financial advice; require human review before any live investment decision · The SKILL.md references 'references/source-and-guardrails.md' but that file is not included in the provided excerpt; however, SKILL.md itself is sufficiently complete and self-contained.
Agent adoption scorecard
Trust, audit, and install readiness at a glance
These scores combine public repository metadata, OpenAgentSkill review signals, maintenance freshness, and install readiness. They are a shortlist signal, not a replacement for human review.
Quality
PromisingUseful candidate, but compare it with alternatives before adopting.
Trust
Sandbox onlyUseful candidate with missing or mixed trust signals. Keep it in an isolated workspace until the outcome loop proves task fit.
Audit
Needs reviewA machine-readable review of install readiness, security metadata, maintenance, and adoption risk.
OpenAgentSkill Trust Score v5
Human review before install
Run only in a sandbox and compare close alternatives before using it for real work.
Stars
16 GitHub stars
Repo activity
16 stars, 1 forks
Maintenance
Pushed today
License
MIT
Install
npx skills add xjli360/sealeap-amazon-ad-skills --skill sealeap-amazon-ad-architecture
Install safety
standard package or runtime install path
Permission surface
no high-risk permission surface in public metadata
Agent outcomes
No agent outcome data yet
Docs
Usable metadata, review docs
Risk summary
Review before production
- The SKILL.md references 'references/source-and-guardrails.md' but that file is not included in the provided excerpt; however, SKILL.md itself is sufficiently complete and self-contained.
- Financial research output is not financial advice; require human review before any live investment decision.
- Low GitHub adoption signal
- Quality score needs review
Install readiness
Install path available
- Install path is available
- Repository evidence is available
- License is declared
- No Agent Proven outcome evidence yet
Agent-readable metadata
Machine-readable decision data for this skill.
Use this block or the embedded JSON to decide whether an agent should install this skill, choose an alternative, or ask for human review first.
Suited tasks
- Research agents workflows
- Claude Code teams
- builders willing to evaluate younger projects
- Search sources
Suited agents
Install decision
- Command
- npx skills add xjli360/sealeap-amazon-ad-skills --skill sealeap-amazon-ad-architecture
- Policy
- review
- Human review
- yes
Trust and risk
- Trust
- 64/100
- Audit
- 76/100
- Risk level
- Needs review
Outcome loop
- Endpoint
- /api/agent/outcome
- Event ID
- resolve
- Outcomes
- 5
Install command
npx skills add xjli360/sealeap-amazon-ad-skills --skill sealeap-amazon-ad-architectureDo not use when
- teams that need a vendor-supported SLA
- production agents without a repository review
- Low GitHub adoption signal
- The SKILL.md references 'references/source-and-guardrails.md' but that file is not included in the provided excerpt; however, SKILL.md itself is sufficiently complete and self-contained.
- No OpenAgentSkill engagement data yet
Agent safety v2
60/100 · Review before install
Usable candidate, but the agent should surface permission and audit notes before installation.
Require human approval before installing into a real workspace.
medium
Network access
Skill likely fetches remote pages, APIs, repositories, or external services.
medium
Database access
Skill may inspect schemas, query databases, or work with persistent stores.
- Financial research output is not financial advice; require human review before any live investment decision
Install targets
Install this skill in your agent workflow
Use the public install endpoint to fetch the command, safety checklist, target prompts, and canonical links for this skill.
OpenAgentSkill CLI
Resolve policy, run the source installer safely, and report a verified install receipt.
$ npx --yes https://github.com/Leon-Drq/openagentskill/releases/download/cli-v0.2.1/openagentskill-0.2.1.tgz install xjli360-sealeap-amazon-ad-architectureAgent resolve plan
Let an agent verify fit before installing.
The Resolve API returns the selected skill, alternatives, safety policy, audit notes, install target, and copy-paste prompt an agent can follow without scraping this page.
Open JSON
/api/agent/resolve?task=Use%20sealeap-amazon-ad-architecture%20for%20an%20agent%20workflow&agent=codex&max_risk=medium
Resolve text
/api/agent/resolve?task=Use%20sealeap-amazon-ad-architecture%20for%20an%20agent%20workflow&agent=codex&max_risk=medium&format=text
Install handoff
/api/skills/xjli360-sealeap-amazon-ad-architecture/install
Agent should check
- Task fit and alternatives from Resolve API.
- Audit score, trust score, and safety policy warnings.
- Install target compatibility for Codex, Claude Code, Cursor, or CLI.
Copy prompt
Task: Use sealeap-amazon-ad-architecture in this workspace.
Resolve first: https://www.openagentskill.com/api/agent/resolve?task=Use%20sealeap-amazon-ad-architecture%20for%20an%20agent%20workflow&agent=codex&max_risk=medium
Review install handoff: https://www.openagentskill.com/api/skills/xjli360-sealeap-amazon-ad-architecture/install
Install command: npx skills add xjli360/sealeap-amazon-ad-skills --skill sealeap-amazon-ad-architecture
Before running it, summarize audit warnings, required permissions, and the fallback skill if install is risky.Agent handoff
Give an agent the install path, not another directory page.
Use the public install endpoint to fetch the command, safety checklist, target prompts, and canonical links for this skill.
Install handoff
/api/skills/xjli360-sealeap-amazon-ad-architecture/install
LLM text format
/api/skills/xjli360-sealeap-amazon-ad-architecture/install?format=text
Find alternatives
/api/skills/search?q=sealeap-amazon-ad-architecture&limit=3
Agent prompt
Use sealeap-amazon-ad-architecture for this task. Review https://www.openagentskill.com/api/skills/xjli360-sealeap-amazon-ad-architecture/install, then install with: npx skills add xjli360/sealeap-amazon-ad-skills --skill sealeap-amazon-ad-architectureRegistry metadata
Agent-readable profile for automatic skill selection.
This page exposes the same decision, trust, audit, use-case, and install signals through the Registry API, so agents can rank this skill without scraping the UI.
Manifest
/api/registry/manifest/xjli360-sealeap-amazon-ad-architecture
LLM text
/api/registry/manifest/xjli360-sealeap-amazon-ad-architecture?format=text
Install alias
/api/registry/install/xjli360-sealeap-amazon-ad-architecture
Recommend
/api/registry/recommend?task=Use%20sealeap-amazon-ad-architecture%20in%20an%20agent%20workflow&limit=3
Agent fit
Research agents
Use-case tags
Platforms
Claude Code
Audit report
Needs review · 76/100
A machine-readable review of install readiness, security metadata, maintenance, and adoption risk.
Agent decision cockpit
Fallback candidate for Research agents
Prototype with this skill first; keep a fallback candidate ready.
Role in stack
Fallback candidate
Primary fit
Research agents
Trust label
Prototype first
Install path
Command ready
Use when
- Research agents workflows
- Claude Code teams
- builders willing to evaluate younger projects
Evidence
- recent repository activity
- install command or GitHub repo available
- 59/100 quality profile
review first
- Low GitHub adoption signal
- The SKILL.md references 'references/source-and-guardrails.md' but that file is not included in the provided excerpt; however, SKILL.md itself is sufficiently complete and self-contained.
- No OpenAgentSkill engagement data yet
Implementation path
- 1Install it in a sandbox agent and run one Research agents task end to end.
- 2Compare output quality, latency, and failure behavior against at least one alternative.
- 3Promote it into production only after reviewing repository permissions, license, and maintenance signals.
Trust profile
Sandbox only
Useful candidate with missing or mixed trust signals. Keep it in an isolated workspace until the outcome loop proves task fit.
GitHub adoption
FIX16 GitHub stars
Stars/forks activity
FIX16 stars, 1 forks; issue activity unavailable in current metadata
Recent maintenance
PASSPushed today
License clarity
PASSMIT
Good signals
- AI review approved
- Install path is available
- Repository evidence is available
- Recently maintained repository
- Install command has no obvious high-risk pattern
- Outcome loop is ready but needs first real agent run
Review before install
- The SKILL.md references 'references/source-and-guardrails.md' but that file is not included in the provided excerpt; however, SKILL.md itself is sufficiently complete and self-contained.
- Financial research output is not financial advice; require human review before any live investment decision.
- Low GitHub adoption signal
- Quality score needs review
- GitHub adoption: 16 GitHub stars
- Stars/forks activity: 16 stars, 1 forks; issue activity unavailable in current metadata
- No real agent outcome reports yet
- Human review required before unattended installation
Recommended action
Run only in a sandbox and compare close alternatives before using it for real work.
Quality profile
Promising candidate for agent workflows
Useful candidate, but compare it with alternatives before adopting.
Workflow fit
Use this skill in these scenarios
Investigate faster
Research agents
I need my agent to research a topic, compare sources, and produce a concise report.
Operate web apps
Browser automation
I need my agent to control a browser, fill forms, and verify web app workflows.
Analyze markets
Finance and quant
I need my agent to analyze markets, financial data, filings, portfolios, and quant strategies.
Workflow fit
Add it to a complete workflow
Find, compare, and synthesize
Research report agent
A workflow for agents that gather sources, compare claims, summarize long material, and draft useful research briefs.
Operate and verify web apps
Browser QA agent
A workflow for agents that navigate products, fill forms, take screenshots, and verify real user flows across web applications.
Design, build, test, and ship interfaces
Frontend and UI
A practical workflow for agents that turn product briefs or Figma designs into polished frontend code, review the result, test it in a browser, and prepare a safe deployment.
Overview
--- name: sealeap-amazon-ad-architecture description: "Build and diagnose a profit-aware Amazon advertising architecture by working backward from stage-level sales and profit goals into inventory, keyword priorities, campaign roles, budgets, and measurable experiments across SP, SB, SBV, SD, keyword targeting, product targeting, and seasonal launch phases. Use for 精品广告架构, 亚马逊广告架构搭建, ASIN 推广计划, 季节性新品预算, 销量利润倒推, 关键词分层/竞争度/SPR/CPR, SP SB SBV SD 组合, 红海类目投放, 广告预算分配, 关键词首页计划, 周复盘, 或根据《如何搭建一个精品的广告架构》形成可审批方案. Default to analysis and draft; do not change live campaigns or claim organic-rank causality without verified account evidence and human approval." ---
# SeaLeap 亚马逊广告架构
围绕阶段销量和退货后利润构建广告组合,而不是按广告类型堆 Campaign。先算经营上限,再选择关键词和各广告活动的职责,最后用周复盘和单变量实验调整。
## 强制边界
- 把源 PPTX 中的日期、客单价、利润率、退货/仓储占比、搜索量区间、SPR/CPR、PPC、预算比例、订单和 ACOS 标记为 `TRAINING_CASE`,不得直接套入当前 ASIN。 - 不承诺“投广告即可把关键词推上首页”。自然排名受相关性、转化、销量、竞争和平台机制共同影响,只能把排名变化设为伴随指标。 - 使用当前账户的广告报告、业务报告、库存、退货、价格、费用和 Listing 证据;数据不足时输出 `HOLD / NEEDS_DATA`,不编数。 - 对不明确的缩写(如材料中的 SPM、SPA、KT、LW、MD、BP/BPE、CT)先建立数据字典,不猜测后执行。 - 广告可用性、归因、竞价策略、placement 和政策以当前站点/控制台为准。 - profile/store/ASIN/SKU 是业务对象,不是授权。生产写入必须绑定服务端已验证 scope,并逐项人工确认。 - 一张实验卡只改一个主变量;不要同时改 Listing、价格、Coupon、预算、竞价、匹配方式和创意后声称因果。
阅读 [references/source-and-guardrails.md](references/source-and-guardrails.md) 获取 PPTX 页码映射、案例口径与限制。
## 工作流
### 1. 固定对象和目标
记录 marketplace、profile、ASIN/SKU/父子体、品类、生命周期/季节、价格、销量目标、利润目标、旺季截止、库存、补货周期和负责人。
将目标按阶段拆开,每阶段只保留:日期、目标单位数、最低利润/最大可接受亏损、关键词/人群任务和停止条件。不要只写“提高销量”。
### 2. 倒推经济上限
用真实费用计算净收入、退货后贡献利润、盈亏平衡 ACOS/CPA 和最大广告花费。广告预算不得超过经营上限、库存上限或季节剩余机会中的最小值。
使用 [references/economics-and-stages.md](references/economics-and-stages.md) 的公式和三阶段模板。源材料的 $50 季节品案例只用于演示算法。
### 3. 建关键词/商品机会表
从搜索词、Search Query Performance/Brand Analytics、广告报告和当前可用的第三方研究取得证据。逐个验证相关性、意图、搜索量、CPC、CVR、竞争、自然/广告位置和利润容量。
按核心/中等/长尾/场景/竞品意图分层,不用固定 10 万/1 万搜索量阈值。使用 [references/keyword-plan.md](references/keyword-plan.md)。
### 4. 为每个阶段分配广告职责
按任务选择广告类型:
- SP 自动用于发现,SP 手动用于验证关键词/商品定向; - SB/SBV 用于品牌入口、视频卖点和额外搜索承接; - SD 用于当前可用的商品/受众再营销或扩展; - 只有具备资格、素材、落地页和可归因目标时才分配预算。
用 [references/campaign-portfolio.md](references/campaign-portfolio.md) 设计 Campaign/Ad Group、匹配与预算,不复制案例百分比。
### 5. 处理红海/高竞争场景
当核心大词的 SP 成本超过利润容量时,不用更高出价掩盖问题。先验证 Listing/价格/评论/库存,再比较 SB/SBV、商品定向、长尾和 SD 是否带来可盈利增量。
阅读 [references/red-ocean-playbook.md](references/red-ocean-playbook.md);材料中“SB 带来 210 单、占广告订单 40%”只属于一个 2023 年讲师案例。
### 6. 形成可审批架构
输出阶段目标、经济模型、关键词任务、Campaign map、预算、样本门槛、单变量动作卡与回退值。使用 [references/output-contract.md](references/output-contract.md)。
### 7. 周复盘与降档
- 同时看广告销售、自然销售、总销售、TACOS、退货后利润、库存和关键词位置;不要只看 ACOS。 - 标记价格、优惠、评论、断货、竞品、季节和归因延迟等干扰项。 - 依据预设样本/日期判断 `KEEP`、`ITERATE`、`ROLLBACK` 或 `STOP`。 - 旺季剩余时间短于学习/补货/回收窗口时停止扩量并执行降档。
## 必须交付
- 对象、授权、数据窗口、数据覆盖和口径; - 分阶段销量、利润、库存和季节截止; - 最大广告花费、盈亏平衡 ACOS/CPA 与计算假设; - 关键词/商品定向优先级及每个词的阶段任务; - SP/SB/SBV/SD 的职责、Campaign map、预算和资格; - `ACCOUNT_FACT`、`CURRENT_POLICY`、`TRAINING_CASE`、`HYPOTHESIS` 分离; - 单变量实验、逐项审批、停止条件、回退值和未解决风险。
信息不足时交付取数清单与 `HOLD`,不要为了填满架构而制造 Campaign。
Technical details
- Version
- 1.0.0
- License
- MIT
- Last updated
- Aug 23, 2026
- Published
- Aug 23, 2026
Decision snapshot
Fallback candidate
recent repository activity
Audit
Install review
Install and adoption review
- Security
- 81/100
- Maintenance
- 100/100
- Install
- 92/100
Agent-proven evidence
Agent-proven evidence
Outcome reports after resolve, review, install, and one narrow run.
- Success rate
- —
- Recent failure
- —
- Outcomes
- 0
- Output quality
- —
- Failed
- 0
- Not relevant
- 0
- Installs
- 0
- Risk blocked
- 0
- Setup needed
- 0
- Production
- 0
No agent outcome data yet. The first agent run can report success, setup needs, risk blocks, failure, or not-relevant through /api/agent/outcome.
Install
Add to agent workflow
Free and open source. Review the report before installing into production agents.
Growth loop
Share kit
Scenario-led draft for sealeap-amazon-ad-architecture, ready for a manual X post.
sealeap-amazon-ad-architecture: Build and diagnose a profit-aware Amazon advertising architecture by working backward from st... 16 stars https://www.openagentskill.com/skills/xjli360-sealeap-amazon-ad-architecture?ref=x
Optional reply with install command
Listing + install path for sealeap-amazon-ad-architecture: https://www.openagentskill.com/skills/xjli360-sealeap-amazon-ad-architecture?ref=x Install: npx skills add xjli360/sealeap-amazon-ad-skills --skill sealeap-amazon-ad-archite...
Listing source
Registry indexed
This listing was indexed from public sources and is not marked official until a maintainer claim is approved.
- Creator
- xjli360
- Indexed by
- OpenAgentSkill community index
Attribution links to the public repository or creator profile. Creators can claim the listing to update ownership signals.
Claim this skillOwner claim
Claim this skill listing
This Registry indexed listing is attributed to xjli360 but is not marked official yet. Claim it to add a verified owner signal and make future launch, install, and audit updates easier to trust.
Creator backlink kit
Add the evidence badges to your README
Show the canonical listing, current trust and audit signals, and real Agent-Proven evidence where developers evaluate the repository.
[](https://www.openagentskill.com/skills/xjli360-sealeap-amazon-ad-architecture)
[](https://www.openagentskill.com/skills/xjli360-sealeap-amazon-ad-architecture)
[](https://www.openagentskill.com/skills/xjli360-sealeap-amazon-ad-architecture/audit)
[](https://www.openagentskill.com/skills/xjli360-sealeap-amazon-ad-architecture)Author
xjli360
@xjli360
Tags
Platform fit
Health signals
- GitHub stars
- 16
- Quality score
- 32/100
- Last GitHub push
- Aug 23, 2026
- Framework hints
- Unknown
- OpenAgentSkill views
- 0
- Install copies
- 0
- Outbound clicks
- 0
Community signal
Share whether this skill looks useful for your agent workflow. Aggregated feedback improves rankings over time.
Trust & safety
Sandbox only
- GitHub adoption16 GitHub starsFIX
- Stars/forks activity16 stars, 1 forks; issue activity unavailable in current metadataFIX
- Recent maintenancePushed todayPASS
- License clarityMITPASS
- README/SKILL.md completenessPublic metadata needs stronger README/SKILL.md contextINFO
- Dependency/runtime riskno major dependency risk hints in public metadataPASS