Social Card Gen
BrianRWagner/ai-marketing-claude-code-skills
Generate platform-specific social post variants (Twitter/X, LinkedIn, Reddit) from one source input.
Diagnose and draft Amazon Canada apparel advertising plans with lifecycle and seasonal timing, English/French search coverage, account evidence, profitability guardrails, and approval-ready…
Install Sealeap Amazon Ca Apparel Ads
$ npx skills add xjli360/sealeap-amazon-skills --skill sealeap-amazon-ca-apparel-ads -a claude-codeProject install by default; add -g for ~/.claude/skills/.
$ gh skill install xjli360/sealeap-amazon-skills sealeap-amazon-ca-apparel-ads --agent claude-codeProject scope by default; add --scope user for a personal install. Needs GitHub CLI 2.90.0 or later (public preview).
$ git clone --depth 1 https://github.com/xjli360/sealeap-amazon-skills.git skills-src && mkdir -p .claude/skills && cp -r skills-src/amazon-skills/amazon-official/sealeap-amazon-ca-apparel-ads .claude/skills/sealeap-amazon-ca-apparel-ads && rm -rf skills-srcUse ~/.claude/skills/ instead of .claude/skills for a personal install. The folder must contain SKILL.md.
Claude Code skills documentation · loads skills from .claude/skills/
Install the "sealeap-amazon-ca-apparel-ads" agent skill from https://github.com/xjli360/sealeap-amazon-skills/tree/main/amazon-skills/amazon-official/sealeap-amazon-ca-apparel-ads into .claude/skills/sealeap-amazon-ca-apparel-ads/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "sealeap-amazon-ca-apparel-ads", then confirm the skill loads.Claude Code copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$skill-installer install https://github.com/xjli360/sealeap-amazon-skills/tree/main/amazon-skills/amazon-official/sealeap-amazon-ca-apparel-adsType this inside Codex. $skill-installer <name> installs a curated skill from openai/skills. The installer writes to $CODEX_HOME/skills (default ~/.codex/skills). Restart Codex if the skill does not show up.
$ npx skills add xjli360/sealeap-amazon-skills --skill sealeap-amazon-ca-apparel-ads -a codexProject install goes to .agents/skills/; add -g for ~/.codex/skills/.
$ gh skill install xjli360/sealeap-amazon-skills sealeap-amazon-ca-apparel-ads --agent codexProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/xjli360/sealeap-amazon-skills.git skills-src && mkdir -p .agents/skills && cp -r skills-src/amazon-skills/amazon-official/sealeap-amazon-ca-apparel-ads .agents/skills/sealeap-amazon-ca-apparel-ads && rm -rf skills-srcUse ~/.agents/skills/ instead of .agents/skills for a personal install.
Codex skills documentation · loads skills from .agents/skills/
Install the "sealeap-amazon-ca-apparel-ads" agent skill from https://github.com/xjli360/sealeap-amazon-skills/tree/main/amazon-skills/amazon-official/sealeap-amazon-ca-apparel-ads into .agents/skills/sealeap-amazon-ca-apparel-ads/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "sealeap-amazon-ca-apparel-ads", then confirm the skill loads.Codex copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ npx skills add xjli360/sealeap-amazon-skills --skill sealeap-amazon-ca-apparel-ads -a cursorProject install goes to .agents/skills/; add -g for ~/.cursor/skills/.
$ gh skill install xjli360/sealeap-amazon-skills sealeap-amazon-ca-apparel-ads --agent cursorProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/xjli360/sealeap-amazon-skills.git skills-src && mkdir -p .cursor/skills && cp -r skills-src/amazon-skills/amazon-official/sealeap-amazon-ca-apparel-ads .cursor/skills/sealeap-amazon-ca-apparel-ads && rm -rf skills-srcUse ~/.cursor/skills/ instead of .cursor/skills for a personal install.
Cursor skills documentation · loads skills from .cursor/skills/, .agents/skills/, .claude/skills/, .codex/skills/
Install the "sealeap-amazon-ca-apparel-ads" agent skill from https://github.com/xjli360/sealeap-amazon-skills/tree/main/amazon-skills/amazon-official/sealeap-amazon-ca-apparel-ads into .cursor/skills/sealeap-amazon-ca-apparel-ads/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "sealeap-amazon-ca-apparel-ads", then confirm the skill loads.Cursor copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ gemini skills install https://github.com/xjli360/sealeap-amazon-skills.git --path amazon-skills/amazon-official/sealeap-amazon-ca-apparel-ads--scope user (default) or --scope workspace; --path is the subfolder of the repo that holds the skill; --consent skips the security confirmation prompt.
$ npx skills add xjli360/sealeap-amazon-skills --skill sealeap-amazon-ca-apparel-ads -a gemini-cliProject install goes to .agents/skills/; add -g for ~/.gemini/skills/.
$ gh skill install xjli360/sealeap-amazon-skills sealeap-amazon-ca-apparel-ads --agent gemini-cliProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/xjli360/sealeap-amazon-skills.git skills-src && mkdir -p .gemini/skills && cp -r skills-src/amazon-skills/amazon-official/sealeap-amazon-ca-apparel-ads .gemini/skills/sealeap-amazon-ca-apparel-ads && rm -rf skills-srcUse ~/.gemini/skills/ instead of .gemini/skills for a personal install, then run /skills reload.
Gemini CLI skills documentation · loads skills from .gemini/skills/, .agents/skills/
Install the "sealeap-amazon-ca-apparel-ads" agent skill from https://github.com/xjli360/sealeap-amazon-skills/tree/main/amazon-skills/amazon-official/sealeap-amazon-ca-apparel-ads into .gemini/skills/sealeap-amazon-ca-apparel-ads/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "sealeap-amazon-ca-apparel-ads", then confirm the skill loads.Gemini CLI copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ gh skill install xjli360/sealeap-amazon-skills sealeap-amazon-ca-apparel-adsInstalls for Copilot at project scope by default; add --scope user for a personal install. Preview a skill first with gh skill preview. Needs GitHub CLI 2.90.0 or later (public preview).
$ npx skills add xjli360/sealeap-amazon-skills --skill sealeap-amazon-ca-apparel-ads -a github-copilotProject install goes to .agents/skills/; add -g for ~/.copilot/skills/.
$ git clone --depth 1 https://github.com/xjli360/sealeap-amazon-skills.git skills-src && mkdir -p .github/skills && cp -r skills-src/amazon-skills/amazon-official/sealeap-amazon-ca-apparel-ads .github/skills/sealeap-amazon-ca-apparel-ads && rm -rf skills-srcUse ~/.copilot/skills/ instead of .github/skills for a personal install. Commit .github/skills so cloud agent and code review can use it.
GitHub Copilot skills documentation · loads skills from .github/skills/, .claude/skills/, .agents/skills/
Install the "sealeap-amazon-ca-apparel-ads" agent skill from https://github.com/xjli360/sealeap-amazon-skills/tree/main/amazon-skills/amazon-official/sealeap-amazon-ca-apparel-ads into .github/skills/sealeap-amazon-ca-apparel-ads/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "sealeap-amazon-ca-apparel-ads", then confirm the skill loads.GitHub Copilot copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ npx skills add xjli360/sealeap-amazon-skills --skill sealeap-amazon-ca-apparel-ads -a opencodeOpenCode documents no install command of its own. Project install goes to .agents/skills/; add -g for ~/.config/opencode/skills/.
$ gh skill install xjli360/sealeap-amazon-skills sealeap-amazon-ca-apparel-ads --agent opencodeProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/xjli360/sealeap-amazon-skills.git skills-src && mkdir -p .opencode/skills && cp -r skills-src/amazon-skills/amazon-official/sealeap-amazon-ca-apparel-ads .opencode/skills/sealeap-amazon-ca-apparel-ads && rm -rf skills-srcUse ~/.config/opencode/skills/ instead of .opencode/skills for a personal install.
OpenCode skills documentation · loads skills from .opencode/skills/, .claude/skills/, .agents/skills/
Install the "sealeap-amazon-ca-apparel-ads" agent skill from https://github.com/xjli360/sealeap-amazon-skills/tree/main/amazon-skills/amazon-official/sealeap-amazon-ca-apparel-ads into .opencode/skills/sealeap-amazon-ca-apparel-ads/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "sealeap-amazon-ca-apparel-ads", then confirm the skill loads.OpenCode copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
Facts
- Skill name
sealeap-amazon-ca-apparel-ads- GitHub stars
- 251
- Token cost
- ~1.2k tokens
- SKILL.md length
- 239 words
- Files
- 7 (incl. scripts, references)
- Skills in repo
- 179
- Repo updated
- First seen
- Licence
- MIT
At a glance
Diagnose and draft Amazon Canada apparel advertising plans with lifecycle and seasonal timing, English/French search coverage, account evidence, profitability guardrails, and approval-ready…
- Works in 9 steps: 锁定对象、目标和双时间轴 → 判断课程适配范围 → 建立消费者顾虑与页面就绪度 → …
- Amazon.ca Coat 外套夹克
- SKILL.md covers 目标, 不可妥协的边界, 先声明模式 and 核心工作流, plus 1 more section
- Runs Python scripts from its folder; calls python3
What it does
Sealeap Amazon Ca Apparel Ads is an agent skill from xjli360/sealeap-amazon-skills. Diagnose and draft Amazon Canada apparel advertising plans with lifecycle and seasonal timing, English/French search coverage, account evidence, profitability guardrails, and approval-ready experiments. Use for 加拿大站服饰广告, Amazon.ca Coat 外套夹克, Underpants 内衣文胸, 季节性长生命周期, 长生命周期, 新品期成长期成熟期, 广告预算配比, SP/SB/SBV/SD/商品投放, 法语关键词, 旺季预热, 复购再营销, CPC/ROAS/ACOS 异常, or when converting the authorized course material into an account-specific plan. Default to diagnosis and draft; never write live advertising changes without explicit…
Its SKILL.md is about 1.2k tokens, which your agent loads only when the skill is triggered. The skill folder holds 9 other files, including scripts and reference files (for example `agents/openai.yaml`, `references/canada-market-and-consumer.md` and `references/lifecycle-playbooks.md`).
It sits in AI & LLM Engineering, covering Paid advertising and LLM guardrails. The repository describes itself as: Reusable Agent Skills for Amazon product research, listings, advertising, inventory, and operations. The licence is MIT.
When your agent uses it
- Amazon.ca Coat 外套夹克
- Underpants 内衣文胸
- SP/SB/SBV/SD/商品投放
- CPC/ROAS/ACOS 异常
Example prompts
- “/sealeap-amazon-ca-apparel-ads”
Requirements
- Python 3
Workflow steps
9 steps, taken from the step headings in SKILL.md.
What it can do on your machine
Read from SKILL.md and the folder at commit 497d4b8. It shows what the files ask for, not the result of running them.
Tool permissions
Pre-approves nothing: there is no allowed-tools line, so your agent's usual permission prompts apply.
From allowed-tools in the SKILL.md frontmatter.
Runs code
Ships 1 file in scripts/ (Python), which the agent can run.
Shell commands in SKILL.md call:
python3
From the folder's file list and the shell code blocks in SKILL.md.
Network
No URLs in SKILL.md.
From URLs in SKILL.md, links to its own repository left out.
Credentials
Names no API keys, tokens, secrets or passwords.
From names ending in _API_KEY, _TOKEN, _SECRET, _KEY or _PASSWORD in SKILL.md.
Context cost
Sealeap Amazon Ca Apparel Ads loads about 1.2k tokens when it runs, and up to ~4.1k if it reads all its reference files. Until then it costs about 141 tokens; SKILL.md has 239 words of instructions outside code blocks.
Estimates: characters ÷ 4, the usual rule of thumb; real counts depend on the model's tokenizer. Scripts and assets cost tokens only if the agent reads them.
Safety
Auto-check passed
The automated check found no risky patterns in SKILL.md.
Automated static check — not a guarantee. Review scripts before installing. It scans the text of SKILL.md for risky patterns (piping downloads into a shell, reading credential files, hidden Unicode, destructive commands); the scripts in this folder are not scanned.
SKILL.md
The full file from xjli360/sealeap-amazon-skills at commit 497d4b8, republished under its MIT licence (© xjli360). 239 words, ~1,207 tokens.
Download SKILL.mdSave it as
.claude/skills/sealeap-amazon-ca-apparel-ads/SKILL.md (or your agent's skills folder). This skill also uses 6 other files; get the full folder from GitHub.- name
- sealeap-amazon-ca-apparel-ads
- description
- Diagnose and draft Amazon Canada apparel advertising plans with lifecycle and seasonal timing, English/French search coverage, account evidence, profitability guardrails, and approval-ready experiments. Use for 加拿大站服饰广告, Amazon.ca Coat 外套夹克, Underpants 内衣文胸, 季节性长生命周期, 长生命周期, 新品期成长期成熟期, 广告预算配比, SP/SB/SBV/SD/商品投放, 法语关键词, 旺季预热, 复购再营销, CPC/ROAS/ACOS 异常, or when converting the authorized course material into an account-specific plan. Default to diagnosis and draft; never write live advertising changes without explicit human approval.
亚马逊加拿大站服饰广告 · 生命周期与季节节奏
目标
把加拿大站服饰广告从“照搬美国站”改成一条可复核的决策链：先同时判断 ASIN 生命周期与当年季节窗口，再核对消费者顾虑、英法语流量、利润和库存，最后生成分阶段广告结构与单变量实验草案。
本 Skill 的课程证据只详细覆盖两类产品：
Coat：季节性长生命周期，课程核心是提前布局、旺季加码、旺季后释放积累；Underpants：长生命周期，课程核心是先建立合身/舒适/材质信任，再用品牌与再营销形成规模复利。
先读 references/source-and-guardrails.md。需要预算表和课程对比数据时读 references/lifecycle-playbooks.md；需要消费者与英法语流量背景时读 references/canada-market-and-consumer.md。
不可妥协的边界
- 把课程比例、头尾 ASIN 倍数和消费者研究标为
COURSE_BASELINE；把当前 Campaign、Search Term、Placement、销量、利润、库存、评价与 Listing 数据标为ACCOUNT_ACTUAL。 - 课程中的倍数是加拿大站服饰类目头部 25% ASIN 相对尾部 25% ASIN 的描述性对比，不是目标值、因果证明或执行阈值。
- 不把“更早投入”自动等同于“必然获得排名、复购或更高 ROAS”。先验证产品、可售性、相关性、转化和利润是否支撑。
- 不把法语查询示例直接扩写或翻译后投放。先验证当前 Amazon.ca 搜索相关性、商品事实、页面语言和账户数据。
- 不用无证据的“抑菌、保暖温度、透气提升、舒适度提升”等声明制作广告或 Listing。
store_id、profile ID、ASIN 或 marketplace 只是业务标识，不是授权。所有读取和写入都必须绑定当前验证过的服务端账户范围。- 默认只生成草案。预算、竞价、placement、target、否定词、状态和广告结构均属于外部写操作，必须逐项人工确认。
- 每轮实验只改变一个可归因主变量；不要同时改 Listing、价格、优惠、竞价、预算和定向后声称因果。
先声明模式
在结果顶部选择一种模式：
DIAGNOSE：只读诊断，不生成可执行变更；DRAFT：生成结构、预算重心和实验草案；默认；RELEASE_PREP：生成逐对象新旧值、护栏、回退和审批卡；APPROVED_WRITE：仅执行用户本轮明确批准的对象和单一动作，写后复读。
核心工作流
1. 锁定对象、目标和双时间轴
记录：
- 已验证的 Amazon.ca 广告 profile、seller、ASIN/SKU、父子体、品类和品牌资格；
- 上架日、首次销售日、历史销售峰值、近 36 个月销售曲线和当前生命周期阶段；
- 当前月份、目标旺季起止、距第一波需求的周数、补货周期和库存覆盖；
- 主目标只能选一个：
验证相关性 / 抢旺季流量 / 建立品牌认知 / 守位 / 利润 / 复购； - 贡献毛利率、盈亏平衡 ACOS、目标 TACOS、预算上限和停止条件。
必须分别输出：
ASIN_LIFECYCLE = NEW | GROWTH | MATURE | DECLINE | NEEDS_DATA
SEASON_WINDOW = OFF_SEASON | PREHEAT | PEAK | POST_PEAK | NON_SEASONAL | NEEDS_DATACoat 老品每年仍会重新进入 PREHEAT → PEAK → POST_PEAK。生命周期成熟不等于全年只降价；两轴冲突时，以当前需求、库存、利润和账户数据决定动作。
2. 判断课程适配范围
用真实销售曲线判断：
| 轨迹 | 课程代表 | 本 Skill 的处理 |
|---|---|---|
| 季节性长生命周期 | Coat | 使用完整分阶段打法 |
| 长生命周期 | Underpants | 使用完整分阶段打法 |
| 季节性短生命周期 | Shirt | 仅可识别，不得套用 Coat 预算 |
| 短生命周期 | Backpack / Swimwear | 仅可识别，不得套用 Underpants 预算 |
若商品不落在前两类，输出 NEEDS_DATA 并说明最接近的类比及差异；不要伪造课程未给出的阶段比例。
3. 建立消费者顾虑与页面就绪度
Coat 至少核对：保暖相关商品事实、材质/填充、适用温度证据、尺码、使用场景、配送承诺、品牌可信度、英文与法语页面信息。
Underpants 至少核对：尺码实测、版型差异、材质参数、弹性、缩水、刺激/舒适反馈、肩带或做工问题、退货原因和复购窗口。
输出“购买问题 → 账户/商品证据 → 页面是否已回答 → 广告能否承接”。页面和商品事实不足时，广告放量只能是 HOLD 或小规模验证。
4. 获取同口径账户证据
至少收集：
- Campaign / Ad Group / Targeting / Search Term / Placement 报告；
- advertised product 与 purchased product 维度；
- 近 7/14/30 天及去年同期的曝光、点击、花费、订单、广告销售额；
- 自然与广告总销售、库存、价格/优惠、Featured Offer、评分/评论和退货；
- 英文、法语、品牌、类目、属性、场景、竞品和不相关查询的分组表现；
- 变更日志、归因窗口、币种、时区和数据更新时间。
不要跨归因窗口、广告类型、币种或父子 ASIN 直接相加。样本不足时输出区间和缺口，不用固定点击数下结论。
5. 选择课程基线并重算账户预算
打开 references/lifecycle-playbooks.md，只把对应类型与阶段的比例作为起点。可运行：
python3 scripts/budget_mix_check.py --product coat --stage growth
python3 scripts/budget_mix_check.py --product underpants --stage mature --allocation plan.json重算时依次应用：
- 删除账户当前不可用或无资格的广告产品；
- 按目标、贡献毛利和库存限制总预算；
- 按已验证查询、ASIN 和 placement 表现分配；
- 保留探索预算但设单独活动与停止条件；
- 明确课程基线与账户草案的差异及原因。
课程比例相加为 100% 也不代表账户计划合理。
6. 设计分层结构
将不同意图和证据强度拆开：
- 英文与法语查询分开观察；品牌、类目、属性/场景和竞品词分开；
- 探索与收割分开；自动、关键词、商品定向分开；
- 进攻竞品与防御自家 ASIN 分开；
- Coat 的预热、旺季与旺季后活动保留独立预算和日期护栏；
- Underpants 的首次获客与历史购买/浏览再营销分开衡量。
不要让多个目的共享同一预算后再推断哪个动作有效。
7. 形成诊断与动作梯度
按顺序判断：
可售/库存/Featured Offer
→ 流量相关性与语言
→ CTR 与创意/价格/位置
→ CVR 与页面/评价/配送/查询
→ CPC 与竞价/竞争/placement
→ ACOS、TACOS、增量和贡献利润先解决上游断点，再考虑加预算。Coat 旺季前的加码必须有库存、相关性和页面承接；Underpants 的品牌与再营销扩张必须有可信商品事实、评价基础和可定义的受众窗口。
8. 生成单变量实验卡
每张卡只包含一个 store + campaign + unique ad group + main variable，并写明：
- 当前观察、证据 ID、基线窗口和课程假设；
- 唯一动作及对象、新旧值、预算上限；
- 冻结变量；
- 最小观察要求、归因等待、成功/停止/回退条件；
- 库存、利润、花费、品牌和合规护栏；
- 负责人和人工确认状态。
9. 审批与写后验证
进入 RELEASE_PREP 时展示 profile、campaign、ad group、target/placement、旧值、新值、最大影响、回退值和证据。仅在用户本轮明确批准后执行。
写后复读实际状态并保存 request/operation ID 与时间。仅看到请求成功时写“已提交”；只有复读确认才写“已生效”。
必须交付
按 references/output-contract.md 输出，至少包含：
- 授权范围、数据窗口、双时间轴和证据等级；
- 课程适配类型、消费者顾虑与页面就绪度；
COURSE_BASELINE与ACCOUNT_ACTUAL分开的阶段预算表；- 英法语查询、关键词、商品定向、品牌与展示型推广结构；
- 利润/库存护栏和单变量实验卡；
DRAFT、READY_FOR_REVIEW、APPROVED或HOLD。
READY_FOR_REVIEW 不等于已批准执行；没有当前账户数据时最终状态只能是 DRAFT 或 HOLD。
© xjli360, MIT. Rendered from Markdown: HTML in the file is shown as text, images as links, and headings moved down two levels. Raw file
Files
SKILL.md and 6 other files (scripts, references) in amazon-skills/amazon-official/sealeap-amazon-ca-apparel-ads of xjli360/sealeap-amazon-skills.
- SKILL.md
- agents/openai.yaml
- references/canada-market-and-consumer.md
- references/lifecycle-playbooks.md
- references/output-contract.md
- references/source-and-guardrails.md
- scripts/budget_mix_check.py
Open the folder on GitHubat commit 497d4b8
Compare with similar skills
Sealeap Amazon Ca Apparel Ads next to the 5 skills that share the most tags, products or categories with it. Stars are the repository's; “used in” counts other GitHub owners with a copy.
| Skill | Stars | Used in | Tokens | Auto-check | Licence | Repo updated |
|---|---|---|---|---|---|---|
| Sealeap Amazon Ca Apparel Ads this skillxjli360/sealeap-amazon-skills | 251 | — | ~1.2k | Automated safety check: Pass | MIT | |
| Social Card GenBrianRWagner/ai-marketing-claude-code-skills | 441 | — | ~1.9k | Automated safety check: Pass | None | |
| Paid Acquisition Planmohitagw15856/pm-claude-skills | 1.4k | — | ~952 | Automated safety check: Pass | MIT | |
| Blog GoogleAgriciDaniel/claude-blog | 2.3k | 1 repos | ~3.3k | Automated safety check: Notes | MIT | |
| Aisafetyhotwuyoscar/AISafetyHot-Hub | 827 | — | ~1.4k | Automated safety check: Pass | Custom licence | |
| Meridian Budget Optimizationgoogle/meridian | 1.6k | — | ~1.1k | Automated safety check: Pass | Apache-2.0 |
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Questions about Sealeap Amazon Ca Apparel Ads
What does Sealeap Amazon Ca Apparel Ads do?
Diagnose and draft Amazon Canada apparel advertising plans with lifecycle and seasonal timing, English/French search coverage, account evidence, profitability guardrails, and approval-ready…. Sealeap Amazon Ca Apparel Ads is an agent skill from xjli360/sealeap-amazon-skills. Diagnose and draft Amazon Canada apparel advertising plans with lifecycle and seasonal timing, English/French search coverage, account evidence, profitability guardrails, and approval-ready experiments.
When should I use Sealeap Amazon Ca Apparel Ads?
Sealeap Amazon Ca Apparel Ads fits situations like: amazon.ca Coat 外套夹克; underpants 内衣文胸; SP/SB/SBV/SD/商品投放; CPC/ROAS/ACOS 异常.
How do I install Sealeap Amazon Ca Apparel Ads in Claude Code?
Run `npx skills add xjli360/sealeap-amazon-skills --skill sealeap-amazon-ca-apparel-ads -a claude-code`. Or copy the skill folder (amazon-skills/amazon-official/sealeap-amazon-ca-apparel-ads in xjli360/sealeap-amazon-skills) into .claude/skills/sealeap-amazon-ca-apparel-ads in your project. Claude Code loads it when a task matches its description.
How do I install Sealeap Amazon Ca Apparel Ads in Codex?
Run `npx skills add xjli360/sealeap-amazon-skills --skill sealeap-amazon-ca-apparel-ads -a codex`. Or copy the skill folder (amazon-skills/amazon-official/sealeap-amazon-ca-apparel-ads in xjli360/sealeap-amazon-skills) into .agents/skills/sealeap-amazon-ca-apparel-ads in your project. Codex loads it when a task matches its description.
Can I use Sealeap Amazon Ca Apparel Ads in Cursor, Gemini CLI or GitHub Copilot?
Cursor, Gemini CLI, GitHub Copilot and OpenCode also load SKILL.md folders. With the skills CLI, run `npx skills add xjli360/sealeap-amazon-skills --skill sealeap-amazon-ca-apparel-ads -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/sealeap-amazon-ca-apparel-ads, .gemini/skills/sealeap-amazon-ca-apparel-ads, .github/skills/sealeap-amazon-ca-apparel-ads and .opencode/skills/sealeap-amazon-ca-apparel-ads in your project.
What does Sealeap Amazon Ca Apparel Ads need to run?
Going by SKILL.md and its folder, Sealeap Amazon Ca Apparel Ads needs Python for the scripts in its folder and the command-line tools its instructions call (python3). Our summary lists: Python 3.
Does Sealeap Amazon Ca Apparel Ads access the network?
SKILL.md contains no URLs. Any network use would come from the scripts or tools the agent runs. This is read from the text; nothing was executed.
Is Sealeap Amazon Ca Apparel Ads safe to install?
Our automated static check of SKILL.md found no risky patterns, such as piping downloads into a shell, reading credential files or hidden Unicode. It is not a guarantee. The check reads SKILL.md only: the scripts in the folder are not scanned, so read them before running anything.
What licence does Sealeap Amazon Ca Apparel Ads use?
Sealeap Amazon Ca Apparel Ads is published under the MIT licence (the repository's licence). It allows redistribution, so the full SKILL.md is shown on this page.
How many tokens does Sealeap Amazon Ca Apparel Ads use?
About 1.2k tokens (SKILL.md is roughly 4.8k characters). Agents keep only the skill's name and description in context until a task matches; then they load SKILL.md in full. Its references folder adds about 2.9k tokens, read only when the agent opens those files.
What are the alternatives to Sealeap Amazon Ca Apparel Ads?
Skills that share tags, products or a category with Sealeap Amazon Ca Apparel Ads: Social Card Gen (BrianRWagner/ai-marketing-claude-code-skills, 441 stars), Paid Acquisition Plan (mohitagw15856/pm-claude-skills, 1.4k stars), Blog Google (AgriciDaniel/claude-blog, 2.3k stars) and Aisafetyhot (wuyoscar/AISafetyHot-Hub, 827 stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.
Who maintains Sealeap Amazon Ca Apparel Ads?
xjli360 (a GitHub user) maintains it in xjli360/sealeap-amazon-skills, which has 251 GitHub stars. The repository holds 179 skills in this directory. The repository was last updated on September 28, 2026.
Source: xjli360/sealeap-amazon-skills on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.