sealeap-amazon-jp-apparel-ads

REVIEW · 67
Registry indexed

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

Verified installs0
Stars16
Version1.0.0
Quality59/100 · Promising
Trust67/100 · Sandbox only
Audit78/100 · Needs review

Supply asset profile

Research and knowledge work

Deep research, source comparison, literature review, RAG, knowledge search, and reports.

Browse track

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

ResearchResearch agentsagent-skill

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

Promising
59

Useful candidate, but compare it with alternatives before adopting.

Trust

Sandbox only
67

Useful candidate with missing or mixed trust signals. Keep it in an isolated workspace until the outcome loop proves task fit.

Audit

Needs review
78

A 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.

CodexClaude CodeCursorOpenAgentSkill CLI

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.

Open JSON

Suited tasks

  • Research agents workflows
  • Claude Code teams
  • builders willing to evaluate younger projects
  • Search sources

Suited agents

CodexClaude CodeCursorOpenAgentSkill CLICLI

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-ads

Do 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

Agent safety v2

58/100 · Review before install

Reviewed with permission notesreview

Usable candidate, but the agent should surface permission and audit notes before installation.

Require human approval before installing into a real workspace.

Resolve via API

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.

skill install

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-ads

Agent 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 text plan

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.

Open install API

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-ads

Registry 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.

Open manifest

Agent fit

58/100

Research agents

Platforms

Claude Code

Audit report

Needs review · 78/100

A machine-readable review of install readiness, security metadata, maintenance, and adoption risk.

View audit reportView eval report

Agent decision cockpit

Fallback candidate for Research agents

Prototype with this skill first; keep a fallback candidate ready.

58
Readiness
Prototype
Stage

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

  1. 1Install it in a sandbox agent and run one Research agents task end to end.
  2. 2Compare output quality, latency, and failure behavior against at least one alternative.
  3. 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.

67
OpenAgentSkill Trust Score

GitHub adoption

FIX

16 GitHub stars

Stars/forks activity

FIX

16 stars, 1 forks; issue activity unavailable in current metadata

Recent maintenance

PASS

Pushed today

License clarity

PASS

MIT

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.

59
GitHub stars
16
Freshness
Today
Install ready
Yes
License
MIT
Review before install: Low GitHub adoption signal

Workflow fit

Use this skill in these scenarios

Workflow fit

Add it to a complete workflow

Alternative shortlist

Compare before you install

Similar skills that may fit this task.

Compare all

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

58
Ready
Prototype
Stage

recent repository activity

Audit

Install review

Install and adoption review

78
Needs review
Security
86/100
Maintenance
100/100
Install
92/100
Open full auditView eval report

Agent-proven evidence

Agent-proven evidence

Outcome reports after resolve, review, install, and one narrow run.

0
Proven
Needs first agent runAuto-install: review firstLast: Unknown
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

X

Scenario-led draft for sealeap-amazon-jp-apparel-ads, ready for a manual X post.

Curator note
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
Open X draft
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

Claimable

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 skill

Owner 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

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[![Listed on OpenAgentSkill](https://www.openagentskill.com/api/badge/xjli360-sealeap-amazon-jp-apparel-ads?metric=listed&label=Listed)](https://www.openagentskill.com/skills/xjli360-sealeap-amazon-jp-apparel-ads)
[![OpenAgentSkill Trust](https://www.openagentskill.com/api/badge/xjli360-sealeap-amazon-jp-apparel-ads?metric=trust&label=Trust)](https://www.openagentskill.com/skills/xjli360-sealeap-amazon-jp-apparel-ads)
[![OpenAgentSkill Audit](https://www.openagentskill.com/api/badge/xjli360-sealeap-amazon-jp-apparel-ads?metric=audit&label=Audit)](https://www.openagentskill.com/skills/xjli360-sealeap-amazon-jp-apparel-ads/audit)
[![Agent Proven](https://www.openagentskill.com/api/badge/xjli360-sealeap-amazon-jp-apparel-ads?metric=proven&label=Agent%20Proven)](https://www.openagentskill.com/skills/xjli360-sealeap-amazon-jp-apparel-ads)

Author

X

xjli360

@xjli360

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

67
  • 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