sealeap-amazon-eu-amc-audience

REVIEW · 63
Registry indexed

Diagnose and plan Amazon Marketing Cloud (AMC) analytics and audience activation for European Amazon Ads accounts, including journey/path analysis, time to conversion, reach and frequency, ad-type overlap, new-to-brand, rule-based and lookalike audiences, seasonal off-peak audien

Verified installs0
Stars16
Version1.0.0
Quality59/100 · Promising
Trust63/100 · Sandbox only
Audit76/100 · Needs review

Supply asset profile

Data, BI, and analytics

CSV, SQL, notebooks, dashboards, data pipelines, BI, ETL, and spreadsheet analysis.

Browse track

Scenario

Database and SQL

I need my agent to inspect database schemas, write SQL, and explain query results.

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-eu-amc-audience

Maintenance

fresh

Pushed today

Risk

Needs review

No critical issues found. The skill enforces read-only analysis by default, prohibits user-level data exposure, and requires explicit human approval before any mutation.

GitHub quality

16

59/100 Quality · 71/100 Trust

Coverage tags

DataDatabase and SQLdata-analysisagent-skill

Review notes

No critical issues found. The skill enforces read-only analysis by default, prohibits user-level data exposure, and requires explicit human approval before any mutation. · 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
63

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

Audit

Needs review
76

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-eu-amc-audience

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

  • No critical issues found. The skill enforces read-only analysis by default, prohibits user-level data exposure, and requires explicit human approval before any mutation.
  • 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-eu-amc-audience
Policy
review
Human review
yes

Trust and risk

Trust
63/100
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-eu-amc-audience

Do not use when

  • teams that need a vendor-supported SLA
  • production agents without a repository review
  • Low GitHub adoption signal
  • No critical issues found. The skill enforces read-only analysis by default, prohibits user-level data exposure, and requires explicit human approval before any mutation.
  • No OpenAgentSkill engagement data yet

Agent safety v2

56/100 · Review before install

Experimentalreview

Sparse or mixed signals. Useful for discovery, but not for autonomous installation.

Test manually in an isolated workspace and compare against safer alternatives.

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.

  • No critical issues found. The skill enforces read-only analysis by default, prohibits user-level data exposure, and requires explicit human approval before any mutation.

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-eu-amc-audience

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-eu-amc-audience in this workspace.
Resolve first: https://www.openagentskill.com/api/agent/resolve?task=Use%20sealeap-amazon-eu-amc-audience%20for%20an%20agent%20workflow&agent=codex&max_risk=medium
Review install handoff: https://www.openagentskill.com/api/skills/xjli360-sealeap-amazon-eu-amc-audience/install
Install command: npx skills add xjli360/sealeap-amazon-ad-skills --skill sealeap-amazon-eu-amc-audience
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-eu-amc-audience for this task. Review https://www.openagentskill.com/api/skills/xjli360-sealeap-amazon-eu-amc-audience/install, then install with: npx skills add xjli360/sealeap-amazon-ad-skills --skill sealeap-amazon-eu-amc-audience

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 · 76/100

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 critical issues found. The skill enforces read-only analysis by default, prohibits user-level data exposure, and requires explicit human approval before any mutation.
  • 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.

63
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

  • No critical issues found. The skill enforces read-only analysis by default, prohibits user-level data exposure, and requires explicit human approval before any mutation.
  • 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 · No critical issues found. The skill enforces read-only analysis by default, prohibits user-level data exposure, and requires explicit human approval before any mutation.

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-eu-amc-audience description: "Diagnose and plan Amazon Marketing Cloud (AMC) analytics and audience activation for European Amazon Ads accounts, including journey/path analysis, time to conversion, reach and frequency, ad-type overlap, new-to-brand, rule-based and lookalike audiences, seasonal off-peak audiences, and SP/SB/SD/DSP activation. Use for 欧洲站 AMC, 亚马逊营销云, AMC 人群包, 潮汐人群, 转化路径, 广告叠加, DSP+AMC, 购买转化周期, 新客分析, 受众竞价加成, AMC query/use case selection, 或把《欧洲转化破局》材料转为可审批的数据与投放方案. Default to read-only analysis and draft actions; never expose user-level data or mutate campaigns/audiences without verified scope and explicit human approval." ---

# SeaLeap 欧洲站 AMC 受众与衡量

把欧洲站的增长问题转换为可审计的 AMC 分析、受众定义、激活草案和衡量方案。先确定业务问题和数据资格,再选择模型;不要先创建人群包,再寻找解释。

## 强制边界

- 把 AMC 定义为隐私安全的数据净室/分析与受众层,不把它说成普通广告报表、用户级 CDP 或直接投放系统。 - 只使用聚合、匿名化或假名化信号。不得尝试导出、重识别、拼接或推断个人身份;不得规避最小受众量、隐私阈值或查询抑制。 - 把源材料中的模型数量、受众窗口、触达频次、运行时长、案例成果和账户截图标为 `TRAINING_CASE`,不当作当前账户事实或官方通用门槛。 - 在使用前核对当前 AMC 实例、marketplace、广告主、可用表、lookback、受众资格、激活渠道、延迟和官方政策。欧洲各站不要无依据合并。 - 将 advertiser/profile/store/AMC instance ID 视为业务对象,不视为授权。只在服务端已验证的主体和站点范围内读取或写入。 - 默认只输出分析与草案。创建查询、保存受众、调整 audience bid、预算、竞价或状态前,逐项等待人工确认。 - 一张实验卡只改变一个主变量。路径、重叠和相关性不能单独证明增量或因果。

阅读 [references/source-and-guardrails.md](references/source-and-guardrails.md) 获取 PDF 页码映射、证据等级和内容限制。

## 工作流

### 1. 锁定问题、主体与站点

记录业务目标、国家站点、广告主、AMC instance、Ads profile、品牌/ASIN、广告类型、时间窗和负责人。把问题写成可回答句,例如:

- 哪些广告组合触达后更可能产生新客,而不是“哪个广告最好”; - 旺季曝光未购买人群是否值得淡季再营销; - 高客单产品从首次触达到购买需要多久、多少次触达; - SP/SB/SD/DSP 的路径和重叠是否支持预算或频次假设。

### 2. 通过就绪门

检查实例与权限、站点和时区、数据覆盖、广告活动映射、转化定义、归因/回看窗口、隐私阈值、受众可激活性、库存和退货后利润。使用 [references/readiness-and-europe.md](references/readiness-and-europe.md)。

缺少关键条件时输出 `HOLD / NEEDS_DATA`;不要把 `No results returned` 自动解释为零,也不要默认数据在其他页面必然存在。

### 3. 选择最小分析模型

按问题只选必要模型:

| 业务问题 | 首选分析 | 主要输出 | |---|---|---| | 决策周期 | Time to Conversion | 转化耗时分布与对比 | | 渠道先后关系 | Path to Conversion by Campaign Groups | 路径、触点顺序、辅助触达 | | 重复覆盖 | Ad-type overlap / reach-frequency | 独占、重叠、频次与浪费假设 | | 拉新 | New-to-brand | 新客购买/销售占比与路径 | | 旺季长尾 | Seasonal off-peak exposure | 旺季曝光未转化候选受众 | | 人群扩展 | Rule-based / lookalike | 精准规则或相似拓展草案 |

阅读 [references/analysis-models.md](references/analysis-models.md) 获取指标定义、对比原则和误读防护。

### 4. 定义受众而非复制案例

用“纳入条件 + 排除条件 + 时间窗 + marketplace + 预估规模 + 用途 + 到期日”定义受众。根据问题选择规则型或相似型;不要把拼图桌案例中的 30/60/90 天窗口套给所有产品。

阅读 [references/audience-playbooks.md](references/audience-playbooks.md) 获取潮汐人群、探索者、痛点/场景、竞品关注者和全漏斗分层方法。

### 5. 生成激活草案

明确激活位置是 SP、SB、SD 还是 DSP,以及 `include`、`exclude`、竞价加成、再营销或相似拓展中的哪一个。先确认当前控制台支持该受众与操作,再创建单变量动作卡。

使用 [references/activation-and-measurement.md](references/activation-and-measurement.md) 设计基线、对照、冷却期、延迟、主指标和停止条件。

### 6. 审批、执行与复盘

- 在动作卡中展示原值、新值、估算成本、利润/频次/库存护栏、受众定义和回退值。 - 只有 `APPROVED` 且 scope 已验证时才能写入;审批一个受众不等于批准修改所有关联 campaign。 - 保存查询版本、参数、运行时间、数据覆盖、受众状态、激活时间和干扰项。 - 到期后关闭或复核受众,避免历史窗口永久运行。

使用 [references/output-contract.md](references/output-contract.md) 交付。

## 必须交付

- 对象、站点、授权、时间/时区、数据覆盖和限制; - 业务问题与为何选择该 AMC 模型; - 查询/模板参数、指标字典和结果解释; - 受众纳入/排除、窗口、规模状态和隐私门槛; - 激活渠道、单变量动作卡、审批与回退; - 对照/增量设计、归因延迟、利润和库存护栏; - `ACCOUNT_FACT`、`CURRENT_POLICY`、`TRAINING_CASE` 与 `HYPOTHESIS` 的明确分离。

证据不足时给出下一步取数清单,不编造 audience size、ROAS、频次或增量结论。

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

76
Needs review
Security
80/100
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-eu-amc-audience, ready for a manual X post.

Curator note
sealeap-amazon-eu-amc-audience: Diagnose and plan Amazon Marketing Cloud (AMC) analytics and audience activation for European...

16 stars

https://www.openagentskill.com/skills/xjli360-sealeap-amazon-eu-amc-audience?ref=x
Open X draft
Optional reply with install command
Listing + install path for sealeap-amazon-eu-amc-audience:
https://www.openagentskill.com/skills/xjli360-sealeap-amazon-eu-amc-audience?ref=x

Install: npx skills add xjli360/sealeap-amazon-ad-skills --skill sealeap-amazon-eu-amc-aud...

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
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Owner claim

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[![Listed on OpenAgentSkill](https://www.openagentskill.com/api/badge/xjli360-sealeap-amazon-eu-amc-audience?metric=listed&label=Listed)](https://www.openagentskill.com/skills/xjli360-sealeap-amazon-eu-amc-audience)
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[![Agent Proven](https://www.openagentskill.com/api/badge/xjli360-sealeap-amazon-eu-amc-audience?metric=proven&label=Agent%20Proven)](https://www.openagentskill.com/skills/xjli360-sealeap-amazon-eu-amc-audience)

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

63
  • 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