Amazon Ads Audit
AgriciDaniel/claude-ads
Audits an Amazon Ads account across Sponsored Products, Brands, Display and DSP, producing evidence-based findings, prioritized recommendations and draft-only changes.
Research, diagnose, and draft Amazon Ads ASIN and category product-targeting plans that complement keyword targeting, including audience expansion, competitor and category traffic, cross-sell…
MITAuto-check passed
Install Sealeap Amazon Product Targeting
$ npx skills add xjli360/sealeap-amazon-skills --skill sealeap-amazon-product-targeting -a claude-codeProject install by default; add -g for ~/.claude/skills/.
$ gh skill install xjli360/sealeap-amazon-skills sealeap-amazon-product-targeting --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-product-targeting .claude/skills/sealeap-amazon-product-targeting && 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-product-targeting" agent skill from https://github.com/xjli360/sealeap-amazon-skills/tree/main/amazon-skills/amazon-official/sealeap-amazon-product-targeting into .claude/skills/sealeap-amazon-product-targeting/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "sealeap-amazon-product-targeting", 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-product-targetingType 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-product-targeting -a codexProject install goes to .agents/skills/; add -g for ~/.codex/skills/.
$ gh skill install xjli360/sealeap-amazon-skills sealeap-amazon-product-targeting --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-product-targeting .agents/skills/sealeap-amazon-product-targeting && 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-product-targeting" agent skill from https://github.com/xjli360/sealeap-amazon-skills/tree/main/amazon-skills/amazon-official/sealeap-amazon-product-targeting into .agents/skills/sealeap-amazon-product-targeting/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "sealeap-amazon-product-targeting", 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-product-targeting -a cursorProject install goes to .agents/skills/; add -g for ~/.cursor/skills/.
$ gh skill install xjli360/sealeap-amazon-skills sealeap-amazon-product-targeting --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-product-targeting .cursor/skills/sealeap-amazon-product-targeting && 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-product-targeting" agent skill from https://github.com/xjli360/sealeap-amazon-skills/tree/main/amazon-skills/amazon-official/sealeap-amazon-product-targeting into .cursor/skills/sealeap-amazon-product-targeting/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "sealeap-amazon-product-targeting", 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-product-targeting--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-product-targeting -a gemini-cliProject install goes to .agents/skills/; add -g for ~/.gemini/skills/.
$ gh skill install xjli360/sealeap-amazon-skills sealeap-amazon-product-targeting --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-product-targeting .gemini/skills/sealeap-amazon-product-targeting && 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-product-targeting" agent skill from https://github.com/xjli360/sealeap-amazon-skills/tree/main/amazon-skills/amazon-official/sealeap-amazon-product-targeting into .gemini/skills/sealeap-amazon-product-targeting/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "sealeap-amazon-product-targeting", 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-product-targetingInstalls 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-product-targeting -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-product-targeting .github/skills/sealeap-amazon-product-targeting && 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-product-targeting" agent skill from https://github.com/xjli360/sealeap-amazon-skills/tree/main/amazon-skills/amazon-official/sealeap-amazon-product-targeting into .github/skills/sealeap-amazon-product-targeting/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "sealeap-amazon-product-targeting", 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-product-targeting -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-product-targeting --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-product-targeting .opencode/skills/sealeap-amazon-product-targeting && 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-product-targeting" agent skill from https://github.com/xjli360/sealeap-amazon-skills/tree/main/amazon-skills/amazon-official/sealeap-amazon-product-targeting into .opencode/skills/sealeap-amazon-product-targeting/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "sealeap-amazon-product-targeting", 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-product-targeting- GitHub stars
- 251
- Token cost
- ~1.2k tokens
- SKILL.md length
- 254 words
- Files
- 8 (incl. scripts, references)
- Skills in repo
- 179
- Repo updated
- First seen
- Licence
- MIT
At a glance
Research, diagnose, and draft Amazon Ads ASIN and category product-targeting plans that complement keyword targeting, including audience expansion, competitor and category traffic, cross-sell…
- Works in 10 steps: 锁定对象、目标和基线 → 建立商品事实与 3WCS 假设表 → 还原当前流量结构 → …
- Product Targeting
- 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 Product Targeting is an agent skill from xjli360/sealeap-amazon-skills. Research, diagnose, and draft Amazon Ads ASIN and category product-targeting plans that complement keyword targeting, including audience expansion, competitor and category traffic, cross-sell, upsell, self-defense, negative targeting, placement analysis, and single-variable experiments. Use for 商品投放, ASIN 定向, 品类定向, Product Targeting, 关键词引流遇到瓶颈, 关联流量, 互补品/替代品, 竞品详情页抢流量, 自家 ASIN 防御, Best Sellers/New Releases 候选, 自动与手动广告联动, or the local file named 如何提升关键词引流效率. Default to research and draft; verify current…
Its SKILL.md is about 1.2k tokens, which your agent loads only when the skill is triggered. The skill folder holds 10 other files, including scripts and reference files (for example `agents/openai.yaml`, `references/keyword-product-linkage.md` and `references/output-contract.md`).
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
- Product Targeting
- Best Sellers/New Releases 候选
- The local file named 如何提升关键词引流效率
Example prompts
- “/sealeap-amazon-product-targeting”
Requirements
- Python 3
Workflow steps
10 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 Product Targeting loads about 1.2k tokens when it runs, and up to ~4k if it reads all its reference files. Until then it costs about 158 tokens; SKILL.md has 254 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). 254 words, ~1,236 tokens.
Download SKILL.mdSave it as
.claude/skills/sealeap-amazon-product-targeting/SKILL.md (or your agent's skills folder). This skill also uses 7 other files; get the full folder from GitHub.- name
- sealeap-amazon-product-targeting
- description
- Research, diagnose, and draft Amazon Ads ASIN and category product-targeting plans that complement keyword targeting, including audience expansion, competitor and category traffic, cross-sell, upsell, self-defense, negative targeting, placement analysis, and single-variable experiments. Use for 商品投放, ASIN 定向, 品类定向, Product Targeting, 关键词引流遇到瓶颈, 关联流量, 互补品/替代品, 竞品详情页抢流量, 自家 ASIN 防御, Best Sellers/New Releases 候选, 自动与手动广告联动, or the local file named 如何提升关键词引流效率. Default to research and draft; verify current marketplace capabilities and never mutate live campaigns without explicit human approval.
Amazon Ads 商品投放 · ASIN/品类定向与关键词联动
目标
把商品投放从“找一批竞品 ASIN 去打”升级为一条可复核的流量设计链：先还原商品与消费者任务，再识别关键词覆盖不到的商品页、类目节点、互补/替代和自家详情页流量，形成候选池，最后用独立 Campaign/Ad Group 做单变量验证。
源文件名与实际内容不一致：文件名是《如何提升关键词引流效率？》，但 39 页课件实际标题和正文均为《商品投放实用案例分享》。本 Skill 以实际内容为准，并保留关键词与商品投放联动部分。先读 references/source-and-guardrails.md。
不可妥协的边界
- 商品投放包括课程中的品类定向和 ASIN 定向；“扩展商品投放”、细化条件、否定能力、广告位和支持广告产品均以当前 marketplace 控制台/API 为准。
- 课件中标为“第三方卖家意见”的 3WCS、榜单分级、欧洲站贴标签、日本站反查词和阻力带案例只能作为
SELLER_HYPOTHESIS，不能写成 Amazon 官方机制。 - 不声称商品投放会让系统“收录关键词”、增加自然排名或给 ASIN 贴上确定标签。只观察可测的曝光、点击、订单、流量位置和利润变化。
- 不因为竞品是 FBM、自家是 FBA 就认定一定更有竞争力；必须比较当前价格、配送承诺、评分、评价量、变体、优惠和商品匹配。
- 不复制竞品文案、素材、商标表达或虚构比较优势；只使用公开商品事实与合法定向能力。
store_id、profile、ASIN 或 marketplace 不等于授权。读取与写入都必须绑定当前验证的服务端账户范围。- 不使用固定“点击 N 次无单”否定阈值。按利润、流量、归因窗口和统计证据定义停止规则。
- 默认只读和草案。任何 target、negative target、bid、budget、placement、status 或结构变更必须逐项人工确认。
先声明模式
RESEARCH：只读构建流量地图与候选池；默认；DIAGNOSE：诊断现有商品投放；DRAFT：生成分层结构与单变量实验；RELEASE_PREP：生成审批卡、旧值/新值、护栏和回退；APPROVED_WRITE：只执行用户本轮明确批准的一个动作，写后复读。
核心工作流
1. 锁定对象、目标和基线
记录：
- 已验证 seller、marketplace、广告 profile、广告产品、ASIN/SKU 与父子体；
- 目标只能选一个：
扩大覆盖 / 突破关键词瓶颈 / 类目节点 / 细分人群 / 交叉销售 / 升级销售 / 自家防御 / 竞品进攻； - 当前关键词、自动和商品投放结构及近 7/14/30 天表现；
- 贡献毛利、盈亏线、库存、Featured Offer、价格/优惠、评价与配送；
- 基线窗口、归因窗口、当前变更和季节事件。
缺少明确目标时先输出 NEEDS_DATA，不要把七种场景全部混在一个 Campaign。
2. 建立商品事实与 3WCS 假设表
用 references/use-cases-and-selection.md 建立：
What: 商品身份、功能、特性、材质、颜色、尺寸、售卖方式
Who: 真实购买对象与购买任务
Where: 使用场景
Competitor: 同需求、同价格带、可替代的竞品
Substitute: 关联、互补或替代商品3WCS 来自第三方卖家观点。每一项都要绑定商品事实、账户查询或市场观察证据；不能凭想象填人群与场景。
3. 还原当前流量结构
至少获取：
- Campaign / Ad Group / Targeting / Search Term / Placement 报告；
- advertised product 与 purchased product 维度；
- 当前自动投放、手动关键词、手动商品投放及 negative targeting；
- 搜索结果与详情页的当前可见广告/自然位置观察；
- Brand Analytics、Search Query Performance 或账户可用的一方查询证据；
- 当前 Best Sellers / New Releases、类目节点与候选 ASIN 前台事实。
按 搜索流量 / 商品详情页 / 类目节点 / 互补 / 替代 / 自家 / 竞品 聚合曝光、点击、花费、订单、销售和贡献利润。不要把单个低样本 ASIN 当成稳定规律。
4. 选择一个应用场景
课件给出七种商品投放场景：扩大覆盖、绕开关键词瓶颈、类目节点、细分人群、交叉/升级销售、自家防御、竞品进攻。具体选择器见 references/use-cases-and-selection.md。
一轮只选择一个主场景。若同时存在防御和进攻需求，拆成不同 Campaign、预算和实验卡。
5. 建立候选 ASIN/品类池
候选来源可以包括：
- 已有自动或商品投放中真实出单/高质量点击的 ASIN；
- purchased product 与 search term 关联出的商品；
- 当前类目、榜单和新品榜中的相关 ASIN；
- 自家变体、配件、升级款与互补商品；
- 高自然排名目标的公开观察；
- 关键词流量研究中的互补/替代主题。
每个候选记录：
candidate / source / relationship / customer_task / relevance /
price_delivery_rating_gap / observed_traffic / account_performance /
profit_ceiling / risk / evidence_ids / freshness候选分为：
TIER_1_TESTABLE：相关、可竞争、有账户或市场证据；TIER_2_EXPLORE：相关但数据不足，只能小预算探索；EXCLUDE：不相关、明显不可竞争、无流量或合规风险。
6. 设计品类与 ASIN 定向
品类定向
- 只使用当前控制台实际提供的品牌、价格、评分、配送或其它细化条件；
- 记录细化前后覆盖范围，避免“精准”到没有曝光；
- 类目节点必须与商品任务相关，不能只因流量大就投。
ASIN 定向
- 自家防御、竞品进攻、互补、替代与升级分别建组；
- 拆开强竞品、可竞争竞品与探索候选；
- “扩展商品投放”若当前可用，单独建组并标明系统可能扩展到替代/互补商品；
- 搜索结果页曝光位置是竞价与系统匹配结果，不作展示保证。
7. 与关键词和自动投放联动
读取 references/keyword-product-linkage.md，采用三轨结构：
自动投放：发现查询与 ASIN，验证基础关联
手动关键词：精细控制搜索意图、排名与品牌防御
手动商品投放：覆盖详情页、类目、互补/替代、进攻与防御迁移规则：
- 从自动/历史报告发现候选；
- 验证商品与消费者任务相关性；
- 候选 ASIN 单独进入手动商品投放；
- 对候选 ASIN 反查到的词仍需一方查询/账户数据验证后才进入手动关键词；
- 不在原活动立即否定，除非存在明确重复竞价问题且有证据；
- 保留源、目的、日期与去重策略。
8. 否定与清理
先按当前广告产品确认支持的否定类型。候选否定必须有：
- 不相关商品事实；或
- 可复核的长期低质量流量与足够样本；或
- 明显不可竞争且不符合实验目的；或
- 品牌/商品合规风险。
将“否定整个品牌”和“否定单个 ASIN”分开评估。若同品牌仍有相关、可竞争的商品，不做整品牌否定。
9. 生成单变量实验卡
一张卡只允许一个 store + campaign + unique ad group + main variable，并写：
- 主场景、候选与关系类型；
- 来源和证据 ID；
- 当前基线与唯一动作的新旧值；
- 预算上限、bid/placement 护栏；
- 冻结的关键词、Listing、价格、优惠和其它 target；
- 成功、停止、回退和归因等待；
- 人工确认状态。
可以运行：
python3 scripts/targeting_plan_check.py --input references/targeting-plan.example.json脚本只做静态结构校验，不验证 ASIN 存在性、实时资格或经济性。
10. 审批与写后验证
进入 RELEASE_PREP 后展示 profile、campaign、ad group、target/negative target、旧值、新值、最大花费、证据和回退。只有用户本轮明确批准后执行。
写后复读目标状态与控制台结果；请求接受不等于已经开始稳定投放。
必须交付
按 references/output-contract.md 输出：
- 授权、口径、商品事实和当前三轨流量地图；
- 单一应用场景和候选池证据；
- ASIN/品类/细化/否定草案；
- 自动、关键词与商品投放的迁移/去重关系；
- 单变量实验、花费护栏、回退和审批对象；
DRAFT、READY_FOR_REVIEW、APPROVED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 7 other files (scripts, references) in amazon-skills/amazon-official/sealeap-amazon-product-targeting of xjli360/sealeap-amazon-skills.
- SKILL.md
- agents/openai.yaml
- references/keyword-product-linkage.md
- references/output-contract.md
- references/source-and-guardrails.md
- references/targeting-plan.example.json
- references/use-cases-and-selection.md
- scripts/targeting_plan_check.py
Open the folder on GitHubat commit 497d4b8
Compare with similar skills
Sealeap Amazon Product Targeting 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 Product Targeting this skillxjli360/sealeap-amazon-skills | 251 | — | ~1.2k | Automated safety check: Pass | MIT | |
| Amazon Ads AuditAgriciDaniel/claude-ads | 9.9k | — | ~531 | Automated safety check: Pass | MIT | |
| Adscoreyhaines31/marketingskills | 54k | 1 repos | ~7k | Automated safety check: Pass | MIT | |
| Paid Ads Amazonnowork-studio/notfair-plugin | 3.9k | — | ~246 | Automated safety check: Pass | MIT | |
| Amazon ASIN Lookupbrowser-act/skills | 6.1k | 1 repos | ~1.5k | Automated safety check: Pass | MIT | |
| Ad Creativecoreyhaines31/marketingskills | 54k | — | ~6.3k | Automated safety check: Pass | MIT |
Similar skills
Ads
coreyhaines31/marketingskills
When the user wants help with paid advertising campaigns on Google Ads, Meta (Facebook/Instagram), LinkedIn, Twitter/X, or other ad platforms.
Paid Ads Amazon
nowork-studio/notfair-plugin
Plan and review Amazon Ads with margin-aware ACoS, product, and search-term guardrails.
Amazon ASIN Lookup
browser-act/skills
Fetches structured Amazon product details such as title, price, ratings and availability for a given ASIN through BrowserAct's lookup API template.
Ad Creative
coreyhaines31/marketingskills
When the user wants to generate, iterate, or scale ad creative — headlines, descriptions, primary text, or full ad variations — for any paid advertising platform.
Ad Creative
nexu-io/open-design
Generate and iterate ad creative including headlines, descriptions, and primary text.
More from xjli360/sealeap-amazon-skills
All 179 skills in this repoSealeap Amazon Acos Diagnostics
xjli360/sealeap-amazon-skills
Diagnose Amazon Ads ACOS with reconciled CTR, CPC, CVR, AOV, ROAS, TACOS, placement, search-term, benchmark, attribution, and contribution-margin evidence, then produce a single-variable…
Sealeap Amazon Ca Apparel Ads
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…
Sealeap Amazon Listing Optimizer
xjli360/sealeap-amazon-skills
Audit, diagnose, rewrite, creatively brief, test, and safely prepare updates for Amazon product detail pages using live marketplace and product-type requirements, verified product facts, Brand…
Sealeap Amazon Prime Day Planning
xjli360/sealeap-amazon-skills
Filter, interpret, and turn the authorized 2025 Amazon Prime Day advertising insight records into a qualified event plan without averaging incompatible slices or treating historical benchmarks as…
Sealeap Amazon Acos Conversion Diagnostics
xjli360/sealeap-amazon-skills
Diagnose high Amazon Ads ACoS by decomposing CPC, conversion rate, price, query mix, placement mix, and sample sufficiency.
Sealeap Amazon Ad Profit Turnaround
xjli360/sealeap-amazon-skills
Rebuild an unprofitable Amazon ad account by replacing head-term dependence with a verified keyword universe, root-based broad tests, pre-emptive negatives, exact harvesting, and portfolio-level…
Questions about Sealeap Amazon Product Targeting
What does Sealeap Amazon Product Targeting do?
Research, diagnose, and draft Amazon Ads ASIN and category product-targeting plans that complement keyword targeting, including audience expansion, competitor and category traffic, cross-sell…. Sealeap Amazon Product Targeting is an agent skill from xjli360/sealeap-amazon-skills. Research, diagnose, and draft Amazon Ads ASIN and category product-targeting plans that complement keyword targeting, including audience expansion, competitor and category traffic, cross-sell, upsell, self-defense, negative targeting, placement analysis, and single-variable experiments.
When should I use Sealeap Amazon Product Targeting?
Sealeap Amazon Product Targeting fits situations like: product Targeting; best Sellers/New Releases 候选; the local file named 如何提升关键词引流效率.
How do I install Sealeap Amazon Product Targeting in Claude Code?
Run `npx skills add xjli360/sealeap-amazon-skills --skill sealeap-amazon-product-targeting -a claude-code`. Or copy the skill folder (amazon-skills/amazon-official/sealeap-amazon-product-targeting in xjli360/sealeap-amazon-skills) into .claude/skills/sealeap-amazon-product-targeting in your project. Claude Code loads it when a task matches its description.
How do I install Sealeap Amazon Product Targeting in Codex?
Run `npx skills add xjli360/sealeap-amazon-skills --skill sealeap-amazon-product-targeting -a codex`. Or copy the skill folder (amazon-skills/amazon-official/sealeap-amazon-product-targeting in xjli360/sealeap-amazon-skills) into .agents/skills/sealeap-amazon-product-targeting in your project. Codex loads it when a task matches its description.
Can I use Sealeap Amazon Product Targeting 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-product-targeting -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-product-targeting, .gemini/skills/sealeap-amazon-product-targeting, .github/skills/sealeap-amazon-product-targeting and .opencode/skills/sealeap-amazon-product-targeting in your project.
What does Sealeap Amazon Product Targeting need to run?
Going by SKILL.md and its folder, Sealeap Amazon Product Targeting 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 Product Targeting 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 Product Targeting 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 Product Targeting use?
Sealeap Amazon Product Targeting 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 Product Targeting use?
About 1.2k tokens (SKILL.md is roughly 4.9k 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 2.8k tokens, read only when the agent opens those files.
What are the alternatives to Sealeap Amazon Product Targeting?
Skills that share tags, products or a category with Sealeap Amazon Product Targeting: Amazon Ads Audit (AgriciDaniel/claude-ads, 9.9k stars), Ads (coreyhaines31/marketingskills, 54k stars), Paid Ads Amazon (nowork-studio/notfair-plugin, 3.9k stars) and Amazon ASIN Lookup (browser-act/skills, 6.1k stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.
Who maintains Sealeap Amazon Product Targeting?
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.