sealeap-amazon-jp-apparel-ads
Diagnose and plan Amazon Japan apparel advertising with Japan-specific consumer behavior, seasonality, and ASIN lifecycle playbooks for long-lifecycle, short-lifecycle, and seasonal products. Use for 日本站服饰广告, JP apparel ads, 背包/内衣/泳装投放, ASIN 生命周期判断, 日本站新品冷启动, 品牌推广启动时机, Amazon Poi
Supply asset profile
Research and knowledge work
Deep research, source comparison, literature review, RAG, knowledge search, and reports.
Scenario
Research agents
I need my agent to research a topic, compare sources, and produce a concise report.
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-jp-apparel-ads
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 · 75/100 Trust
Coverage tags
Review notes
Financial research output is not financial advice; require human review before any live investment decision · Low GitHub adoption signal
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-jp-apparel-ads
Install safety
standard package or runtime install path
Permission surface
filesystem or document access
Agent outcomes
No agent outcome data yet
Docs
Usable metadata, review docs
Risk summary
Review before production
- 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
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-jp-apparel-ads
- Policy
- review
- Human review
- yes
Trust and risk
- Trust
- 67/100
- Audit
- 78/100
- 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-jp-apparel-adsDo not use when
- teams that need a vendor-supported SLA
- production agents without a repository review
- Low GitHub adoption signal
- No OpenAgentSkill engagement data yet
- Financial research output is not financial advice; require human review before any live investment decision
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Agent safety v2
58/100 · 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
Filesystem access
Skill may read or write project files, documents, generated artifacts, or local workspace state.
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-jp-apparel-adsAgent 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-jp-apparel-ads%20for%20an%20agent%20workflow&agent=codex&max_risk=medium
Resolve text
/api/agent/resolve?task=Use%20sealeap-amazon-jp-apparel-ads%20for%20an%20agent%20workflow&agent=codex&max_risk=medium&format=text
Install handoff
/api/skills/xjli360-sealeap-amazon-jp-apparel-ads/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-jp-apparel-ads in this workspace.
Resolve first: https://www.openagentskill.com/api/agent/resolve?task=Use%20sealeap-amazon-jp-apparel-ads%20for%20an%20agent%20workflow&agent=codex&max_risk=medium
Review install handoff: https://www.openagentskill.com/api/skills/xjli360-sealeap-amazon-jp-apparel-ads/install
Install command: npx skills add xjli360/sealeap-amazon-ad-skills --skill sealeap-amazon-jp-apparel-ads
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-jp-apparel-ads/install
LLM text format
/api/skills/xjli360-sealeap-amazon-jp-apparel-ads/install?format=text
Find alternatives
/api/skills/search?q=sealeap-amazon-jp-apparel-ads&limit=3
Agent prompt
Use sealeap-amazon-jp-apparel-ads for this task. Review https://www.openagentskill.com/api/skills/xjli360-sealeap-amazon-jp-apparel-ads/install, then install with: npx skills add xjli360/sealeap-amazon-ad-skills --skill sealeap-amazon-jp-apparel-adsRegistry 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-jp-apparel-ads
LLM text
/api/registry/manifest/xjli360-sealeap-amazon-jp-apparel-ads?format=text
Install alias
/api/registry/install/xjli360-sealeap-amazon-jp-apparel-ads
Recommend
/api/registry/recommend?task=Use%20sealeap-amazon-jp-apparel-ads%20in%20an%20agent%20workflow&limit=3
Agent fit
Research agents
Use-case tags
Platforms
Claude Code
Audit report
Needs review · 78/100
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
- 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
- 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.
Search private knowledge
RAG and knowledge
I need my agent to build a RAG workflow over documents and retrieve reliable context.
Manage repositories
GitHub automation
I need my agent to triage GitHub issues, review pull requests, and summarize repository changes.
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.
Ingest, retrieve, and cite
RAG knowledge base
A workflow for document-heavy agents that ingest files, create searchable knowledge, retrieve relevant context, and answer with grounded sources.
Inspect, patch, and verify code
Coding review agent
A workflow for software agents that inspect repositories, review pull requests, generate tests, and turn findings into shippable patches.
Alternative shortlist
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Overview
--- name: sealeap-amazon-jp-apparel-ads description: "Diagnose and plan Amazon Japan apparel advertising with Japan-specific consumer behavior, seasonality, and ASIN lifecycle playbooks for long-lifecycle, short-lifecycle, and seasonal products. Use for 日本站服饰广告, JP apparel ads, 背包/内衣/泳装投放, ASIN 生命周期判断, 日本站新品冷启动, 品牌推广启动时机, Amazon Points, 日文功能词, 季节性备货与预热, 广告预算结构, ACOS/ROAS 诊断, 复购再营销, 或根据《亚马逊日本站服饰品类广告运营手册》输出可审批的投放方案. Default to analysis and draft; do not mutate live campaigns without explicit human approval." ---
# SeaLeap 亚马逊日本站服饰广告运营
把日本站服饰 ASIN 的产品类型、生命周期阶段、季节节点、消费者意图和账户真实数据合并成可审核的广告计划。先诊断,再选择日本站打法;不要把美国站或英国站的节奏直接套入日本站。
## 强制边界
- 只将本 Skill 用于 Amazon.co.jp 服饰及与服饰紧密相关的配件。跨站点需求必须重新验证关键词、季节和消费者意图。 - 把手册中的百分比、倍数、预算结构和竞价建议标记为 `MANUAL_BASELINE`,不当作当前账户的事实或必达 KPI。 - 优先使用当前账户一方数据:Campaign/Search Term/Targeting/Placement 报告、广告销售、总销售、利润、库存、退货和 Listing 证据。缺数据时输出 `DRAFT / HOLD`,不编数。 - 把 `store_id`、seller ID、profile ID 或 ASIN 当作业务对象,不当作授权。任何真实读写都要绑定服务端已验证的店铺与广告 profile scope。 - 默认只产出草案。调整预算、竞价、placement、target、否定词、状态或广告结构前,逐项展示旧值、新值、证据、影响范围和回退值,并等待人工确认。 - 每张实验卡只改一个主变量。不要同时改 Listing、价格、优惠、库存、竞价和定向后声称因果。
查看 [references/source-and-guardrails.md](references/source-and-guardrails.md) 获取原 PDF 页码映射、数据口径和不可直接执行的阈值说明。
## 工作流
### 1. 锁定投放对象
取得并固定:
- 广告 profile、seller、marketplace=`JP`、ASIN、SKU、父子体和产品类型; - 上架日、当前销售曲线、历史峰值、季节节点、在途/可售库存和补货周期; - 价格、优惠、Amazon Points 当前设置、星级、评论量、退货原因和单件贡献利润; - 近30/14/7天广告数据,至少按 query/target、match type、placement、ASIN/SKU 拆分; - 当前 Listing 的主图、标题、五点、尺码表、A+、日文本地化和功能性声明证据。
信息不完时明确列出 `NEEDS_DATA`,继续做有边界的诊断,不用想象补齐。
### 2. 判定生命周期类型与阶段
先根据真实销售曲线判定,再用手册案例类比:
| 类型 | 判断信号 | 日本站手册案例 | 主要任务 | |---|---|---|---| | 长生命周期 | 全年需求相对稳定,靠评论与品牌长期累积 | 背包 | 新品建信任,成长期放大规模,成熟期守阵地与再营销 | | 短生命周期 | 快速起量后进入不可逆衰退,产品迭代快 | 内裤 | 新品用功能精准词起量,成长期建品牌,成熟期激活复购并让新款接力 | | 季节性 | 需求集中在明确月份,错过窗口难以补救 | 泳装 | 旺季前抢排名和视觉信任,爬坡期放量,高峰期收割并累积品牌 |
阅读 [references/market-and-lifecycle.md](references/market-and-lifecycle.md) 判定日本站消费者特征、全年节奏和生命周期边界。不要仅按上架月数硬套阶段;销售趋势、需求节点和库存风险必须一起判断。
### 3. 做五层诊断
按“现状 → 证据 → 问题 → 动作 → 验证指标”输出:
1. **可售性**:库存、Buy Box、抑制、价格、配送、资格和季节备货是否支持放量。 2. **可发现性**:日文品类词、功能词、场景词和商品定向是否匹配真实产品。 3. **点击**:搜索结果中主图、标题前段、价格/积分、评分和视频首帧是否建立当地化信任。 4. **转化与退货**:尺码、材质、功能、做工、使用场景和限制是否在 Listing 中被如实说清。 5. **利润与增量**:把 CPC、CVR、ACOS、TACOS、广告/自然/总订单、退货后贡献利润和库存消耗合并判断,不以单一 ROAS 下结论。
### 4. 路由到站点专属打法
- 长生命周期或高信任门槛产品:阅读 [references/long-lifecycle.md](references/long-lifecycle.md)。 - 短生命周期、高频消耗或款式迭代产品:阅读 [references/short-lifecycle.md](references/short-lifecycle.md)。 - 需求高度集中在旺季的产品:阅读 [references/seasonal-lifecycle.md](references/seasonal-lifecycle.md)。
先借用最接近的案例生成“假设”,再用当前账户数据验证。不要因为产品也是服饰,就默认它与背包、内裤或泳装具有同一节奏。
### 5. 生成可审批的广告计划
为每个建议创建独立动作卡,包含:
- 目标 profile / marketplace / campaign / ad group / ASIN / SKU; - 唯一主动作; - 基线窗口、归因窗口、样本阈值和数据完整性; - 旧值、新值和 `MANUAL_BASELINE` 仅作参考的说明; - 主指标、护栏指标、成功/失败/停止/回退条件; - 预期费用与退货后利润上限; - 审批状态:`DRAFT`、`READY_FOR_REVIEW`、`APPROVED`或 `HOLD`。
使用 [references/output-contract.md](references/output-contract.md) 的结构交付。
### 6. 验证与回退
- 把当天的价格、优惠、积分、库存、评论变化、竞品事件和季节事件记为干扰项。 - 在达到预设样本或时间窗口后评估;不要用统一的7天或固定点击数替代品类和利润判断。 - 如果触发花费、利润、库存或转化护栏,按预先记录的回退值处理,并保留审计记录。
## 必须交付的结果
- 对象、数据时间、数据口径和完整性; - 生命周期类型、阶段和判定证据; - 日本站消费者意图与季节节点; - 五层诊断与问题优先级; - Campaign/Ad Group 结构、关键词/商品定向、placement、创意和再营销草案; - 手册参考值与账户实际值的明确分离; - 单变量实验卡、审批项、回退方案和未解决风险。
证据不足时明确输出 `HOLD`;不要把一份 2026 年培训手册写成已验证的当前账户结论。
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
- 86/100
- 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-jp-apparel-ads, ready for a manual X post.
sealeap-amazon-jp-apparel-ads: Diagnose and plan Amazon Japan apparel advertising with Japan-specific consumer behavior, sea... 16 stars https://www.openagentskill.com/skills/xjli360-sealeap-amazon-jp-apparel-ads?ref=x
Optional reply with install command
Listing + install path for sealeap-amazon-jp-apparel-ads: https://www.openagentskill.com/skills/xjli360-sealeap-amazon-jp-apparel-ads?ref=x Install: npx skills add xjli360/sealeap-amazon-ad-skills --skill sealeap-amazon-jp-apparel...
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-jp-apparel-ads)
[](https://www.openagentskill.com/skills/xjli360-sealeap-amazon-jp-apparel-ads)
[](https://www.openagentskill.com/skills/xjli360-sealeap-amazon-jp-apparel-ads/audit)
[](https://www.openagentskill.com/skills/xjli360-sealeap-amazon-jp-apparel-ads)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
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