Ad Creative
LeoYeAI/openclaw-marketing-skills
When the user wants to generate, iterate, or scale ad creative — headlines, descriptions, primary text, or full ad variations — for any paid advertising platform.
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…
Install Sealeap Amazon Acos Diagnostics
$ npx skills add xjli360/sealeap-amazon-skills --skill sealeap-amazon-acos-diagnostics -a claude-codeProject install by default; add -g for ~/.claude/skills/.
$ gh skill install xjli360/sealeap-amazon-skills sealeap-amazon-acos-diagnostics --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-acos-diagnostics .claude/skills/sealeap-amazon-acos-diagnostics && 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-acos-diagnostics" agent skill from https://github.com/xjli360/sealeap-amazon-skills/tree/main/amazon-skills/amazon-official/sealeap-amazon-acos-diagnostics into .claude/skills/sealeap-amazon-acos-diagnostics/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "sealeap-amazon-acos-diagnostics", 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-acos-diagnosticsType 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-acos-diagnostics -a codexProject install goes to .agents/skills/; add -g for ~/.codex/skills/.
$ gh skill install xjli360/sealeap-amazon-skills sealeap-amazon-acos-diagnostics --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-acos-diagnostics .agents/skills/sealeap-amazon-acos-diagnostics && 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-acos-diagnostics" agent skill from https://github.com/xjli360/sealeap-amazon-skills/tree/main/amazon-skills/amazon-official/sealeap-amazon-acos-diagnostics into .agents/skills/sealeap-amazon-acos-diagnostics/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "sealeap-amazon-acos-diagnostics", 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-acos-diagnostics -a cursorProject install goes to .agents/skills/; add -g for ~/.cursor/skills/.
$ gh skill install xjli360/sealeap-amazon-skills sealeap-amazon-acos-diagnostics --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-acos-diagnostics .cursor/skills/sealeap-amazon-acos-diagnostics && 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-acos-diagnostics" agent skill from https://github.com/xjli360/sealeap-amazon-skills/tree/main/amazon-skills/amazon-official/sealeap-amazon-acos-diagnostics into .cursor/skills/sealeap-amazon-acos-diagnostics/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "sealeap-amazon-acos-diagnostics", 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-acos-diagnostics--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-acos-diagnostics -a gemini-cliProject install goes to .agents/skills/; add -g for ~/.gemini/skills/.
$ gh skill install xjli360/sealeap-amazon-skills sealeap-amazon-acos-diagnostics --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-acos-diagnostics .gemini/skills/sealeap-amazon-acos-diagnostics && 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-acos-diagnostics" agent skill from https://github.com/xjli360/sealeap-amazon-skills/tree/main/amazon-skills/amazon-official/sealeap-amazon-acos-diagnostics into .gemini/skills/sealeap-amazon-acos-diagnostics/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "sealeap-amazon-acos-diagnostics", 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-acos-diagnosticsInstalls 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-acos-diagnostics -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-acos-diagnostics .github/skills/sealeap-amazon-acos-diagnostics && 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-acos-diagnostics" agent skill from https://github.com/xjli360/sealeap-amazon-skills/tree/main/amazon-skills/amazon-official/sealeap-amazon-acos-diagnostics into .github/skills/sealeap-amazon-acos-diagnostics/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "sealeap-amazon-acos-diagnostics", 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-acos-diagnostics -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-acos-diagnostics --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-acos-diagnostics .opencode/skills/sealeap-amazon-acos-diagnostics && 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-acos-diagnostics" agent skill from https://github.com/xjli360/sealeap-amazon-skills/tree/main/amazon-skills/amazon-official/sealeap-amazon-acos-diagnostics into .opencode/skills/sealeap-amazon-acos-diagnostics/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "sealeap-amazon-acos-diagnostics", 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-acos-diagnostics- GitHub stars
- 251
- Token cost
- ~1.2k tokens
- SKILL.md length
- 284 words
- Files
- 10 (incl. scripts, references)
- Skills in repo
- 179
- Repo updated
- First seen
- Licence
- MIT
At a glance
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…
- Works in 9 steps: 先问“这轮广告要完成什么” → 锁定分析作用域 → 先重算，不信任表格中的派生值 → …
- Converting the authorized Amazon Ads metrics course into an account-specific plan
- SKILL.md covers 目标, 核心原则, 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 Acos Diagnostics is an agent skill from 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 optimization experiment. Use for ACOS 高低判断, 广告亏损, CTR/CVR/CPC 异常, 盈亏平衡 ACOS, 广告报告诊断, Benchmark 基准, placement 浪费, 搜索词不精准, Listing 转化问题, 广告利润优化, or converting the authorized Amazon Ads metrics course into an account-specific plan. Default to read-only diagnosis and draft; never change live campaigns without explicit human approval.
Its SKILL.md is about 1.2k tokens, which your agent loads only when the skill is triggered. The skill folder holds 12 other files, including scripts and reference files (for example `agents/openai.yaml`, `references/acos-input.example.json` and `references/benchmark-methodology.md`).
It sits in Marketing & SEO, covering Paid advertising. 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
- Converting the authorized Amazon Ads metrics course into an account-specific plan
- Tasks that involve Paid advertising
Example prompts
- “/sealeap-amazon-acos-diagnostics”
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 Acos Diagnostics loads about 1.2k tokens when it runs, and up to ~4.8k if it reads all its reference files. Until then it costs about 138 tokens; SKILL.md has 284 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). 284 words, ~1,215 tokens.
Download SKILL.mdSave it as
.claude/skills/sealeap-amazon-acos-diagnostics/SKILL.md (or your agent's skills folder). This skill also uses 9 other files; get the full folder from GitHub.- name
- sealeap-amazon-acos-diagnostics
- description
- 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 optimization experiment. Use for ACOS 高低判断, 广告亏损, CTR/CVR/CPC 异常, 盈亏平衡 ACOS, 广告报告诊断, Benchmark 基准, placement 浪费, 搜索词不精准, Listing 转化问题, 广告利润优化, or converting the authorized Amazon Ads metrics course into an account-specific plan. Default to read-only diagnosis and draft; never change live campaigns without explicit human approval.
Amazon Ads ACOS 核心指标诊断
目标
把“ACOS 高不高”改写成一条可复核的问题链：先确认策略目标和经济性，再统一数据口径，重算 ACOS 及其驱动项，定位 CPC、CVR、客单价或流量结构断点，最后只提出一个可归因的实验。
先读 references/source-and-guardrails.md。需要公式与指标口径时读 references/metric-system.md，需要完整诊断树时读 references/diagnostic-tree.md。课程案例只能结合 references/case-study-and-caveats.md 使用；需要 Benchmark 算法与误读防护时读 references/benchmark-methodology.md。
核心原则
ACOS = 广告花费 ÷ 广告归因销售额 × 100%，也可在同一口径下拆为CPC ÷ (CVR × 广告订单客单价) × 100%。- ACOS 是结果指标，不是所有广告目标的唯一评价标准。测试、守位、品牌获客、推排名和成熟品利润的主目标不同。
- 盈亏判断使用“扣除商品成本、平台费用、履约、折扣、退货等广告外可变成本后的贡献毛利率”。缺少完整成本时不得把普通毛利率写成精确盈亏线。
- 广告归因销售额与总销售额不得混用；ACOS、TACOS、ROAS 必须分别命名。
- 不跨 marketplace、profile、币种、广告类型、归因窗口、日期或层级直接拼接。
- Benchmark 是同业参照，不是目标或因果解释。当前可用性、同业组、分位数与指标定义必须在控制台/API 重新确认。
- 默认只读。任何 bid、budget、placement、target、否定词、状态或结构变更均需逐对象人工批准。
先声明模式
DIAGNOSE：重算和定位，不生成变更；默认；DRAFT：生成单变量实验草案；RELEASE_PREP：生成审批卡、旧值/新值、停止线和回退；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. 先问“这轮广告要完成什么”
只选一个主目标：
| 目标 | 首要判断 | ACOS 的位置 |
|---|---|---|
| 测试商品/查询 | 相关性与有效样本 | 护栏，不是首要结果 |
| 防守 | 关键流量是否守住且经济可承受 | 与覆盖、份额、利润并看 |
| 品牌获客 | 品牌新客与后续价值 | 与新客成本、店铺行为并看 |
| 推排名 | 排名/自然贡献是否改善 | 与总利润、TACOS、库存并看 |
| 成熟品利润 | 贡献利润和现金效率 | 关键结果之一 |
若用户只说“把 ACOS 降低”，先确认降低 ACOS 是否会伤害本轮主目标。证据不足时仍可继续只读诊断，但把目标标为 NEEDS_DATA。
2. 锁定分析作用域
记录：
- 已验证的 seller、marketplace、广告 profile 和授权范围；
- 日期、时区、币种、广告类型、归因窗口、数据更新时间；
- 分析层级：portfolio / campaign / ad group / target / search term / placement / advertised ASIN；
- 当前价格、优惠、库存、Featured Offer、评分、配送和 Listing 变更；
- 单位经济：售价、折扣、COGS、FBA/佣金/履约、退货/退款、其它可变成本。
不要用账户汇总 ACOS 直接解释某个词，也不要用某个词的 CTR 替代 campaign 目标表现。
3. 先重算，不信任表格中的派生值
准备 JSON 后运行：
python3 scripts/acos_diagnose.py --input references/acos-input.example.json至少提供 impressions / clicks / spend / orders / ad_sales。脚本会计算 CTR、CPC、CPM、CVR、AOV、CPA、ACOS、ROAS，以及可选 TACOS，并对上报指标做一致性检查。
遇到以下情况先 HOLD 或降级结论：
- 广告销售额为 0：ACOS 未定义，不写成 0%；
- 点击为 0：CPC/CVR 未定义；
- 数据为负、订单大于点击、点击大于曝光等明显口径问题；
spend ≠ CPC × clicks、ad_sales ≠ AOV × orders超出舍入误差；- 归因未成熟、退款未回写或多个币种混合。
4. 与经济性对齐
优先计算：
break_even_acos = contribution_margin_before_ads / revenue
ad_contribution_profit = ad_sales × contribution_margin_rate - ad_spend
tacos = ad_spend / total_sales分别报告“广告归因贡献利润”和“全店/ASIN 总贡献”。ACOS 低于盈亏线不自动证明广告增量盈利；仍需考虑自然替代、品牌词截流、退货、库存和边际效果。
5. 拆解 ACOS 驱动项
依次回答：
- ACOS 是否真的影响当前主目标？
- CPC 是否上升，来自 bid、placement、竞争、匹配结构还是流量迁移？
- CVR 是否下降，来自搜索词不相关、Listing、价格/优惠、评价、配送、库存还是变体？
- 广告订单客单价是否变化，来自 SKU 组合、折扣、捆绑或归因结构？
- 各层汇总是否被少数 placement、target、search term 或 ASIN 淹没？
用 references/diagnostic-tree.md 输出“观察 → 重算 → 可能解释 → 排除证据 → 根因置信度 → 下一步”。不要把同时发生当成因果。
6. 使用 Benchmark 只做参照
课程 2026 快照描述了品牌维度 Benchmark，可比较 CTR、CPC、CPM、新客购买占比/购买率/单次购买成本和视频指标，并提到 25/50/75 分位及同行组隐私门槛。
使用前：
- 在当前 marketplace、广告类型与账户确认可见性；
- 保存同业组、分位数、日期、指标定义和样本覆盖；
- 只比较同层级、同时间窗、同广告产品；
- Benchmark 异常只定位“值得查的指标”，不直接给动作。
课程对“平均值”和“中位数”表述不完全一致；未拿到当前字段定义时标 NEEDS_DATA。
7. 深挖断点
CPC 偏高
- 分 placement、target/search term、match type、日期和设备/素材能力可见维度；
- 检查当前 bid、动态竞价、placement 加价、预算抢量和竞争期；
- 同时看 CVR 与点击价值。高 CPC 但高贡献利润不必机械降低。
CTR 偏低
- 先区分流量不匹配与创意/商品卡问题；
- 检查主图、标题前段、价格、优惠、评分、配送、广告位置和竞品差异；
- 不在同一实验同时改主图、标题和竞价。
CVR 偏低
- 先看 search term/ASIN 相关性，再看详情页；
- 检查商品事实、图片/视频/A+、价格、评价、配送、变体、退货和库存；
- 不因单个低转化词的少量点击立即否定；按账户利润和归因窗口定义证据要求。
客单价偏低
- 区分促销、低价子体、交叉销售和归因组合变化；
- “提高客单价/捆绑”只是候选策略，必须重算 CVR、利润、库存和合规影响。
8. 生成一个单变量实验
一张实验卡只允许一个 store + campaign + unique ad group + main variable。必须包含：
- 主目标和战略理由；
- 基线窗口、当前值、数据量、归因成熟度；
- 唯一动作、旧值、新值、最大花费；
- 冻结变量；
- 成功、停止、回退和风险护栏；
- 预期观察指标与不应受损指标；
- 人工确认状态。
若根因在 Listing，广告侧先保持不变，另建 Listing 实验；若根因在竞价，不同时加否词。
9. 审批与复读
进入 RELEASE_PREP 后逐项展示 profile、campaign、ad group、target/placement、旧值、新值、证据、影响范围、花费上限和回退。只有用户本轮明确确认后才能写。
写后复读 Amazon 返回和控制台/报告状态。请求接受只写“已提交”，复读确认后才写“已生效”。
必须交付
按 references/output-contract.md 输出：
- 目标、授权、口径、归因成熟度和数据质量；
- 重算指标、经济性和派生值一致性；
- ACOS → CPC/CVR/AOV → placement/target/search term/Listing 的诊断链；
- Benchmark 的适用范围与局限；
- 一个单变量实验卡、审批对象与回退；
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 9 other files (scripts, references) in amazon-skills/amazon-official/sealeap-amazon-acos-diagnostics of xjli360/sealeap-amazon-skills.
- SKILL.md
- agents/openai.yaml
- references/acos-input.example.json
- references/benchmark-methodology.md
- references/case-study-and-caveats.md
- references/diagnostic-tree.md
- references/metric-system.md
- references/output-contract.md
- references/source-and-guardrails.md
- scripts/acos_diagnose.py
Open the folder on GitHubat commit 497d4b8
Compare with similar skills
Sealeap Amazon Acos Diagnostics 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 Acos Diagnostics this skillxjli360/sealeap-amazon-skills | 251 | — | ~1.2k | Automated safety check: Pass | MIT | |
| Ad CreativeLeoYeAI/openclaw-marketing-skills | 1k | 8 repos | ~3.4k | Automated safety check: Pass | Custom licence | |
| Blog GoogleAgriciDaniel/claude-blog | 2.3k | 1 repos | ~3.3k | Automated safety check: Notes | MIT | |
| Ad Account Auditoraaron-he-zhu/aaron-marketing-skills | 2.9k | 2 repos | ~2.2k | Automated safety check: Pass | Apache-2.0 | |
| Ad Creative Builderaaron-he-zhu/aaron-marketing-skills | 2.9k | 2 repos | ~2.2k | Automated safety check: Pass | Apache-2.0 | |
| Ad Test Designeraaron-he-zhu/aaron-marketing-skills | 2.9k | 2 repos | ~2.8k | Automated safety check: Pass | Apache-2.0 |
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Questions about Sealeap Amazon Acos Diagnostics
What does Sealeap Amazon Acos Diagnostics do?
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 Acos Diagnostics is an agent skill from 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 optimization experiment.
When should I use Sealeap Amazon Acos Diagnostics?
Sealeap Amazon Acos Diagnostics fits situations like: converting the authorized Amazon Ads metrics course into an account-specific plan; tasks that involve Paid advertising.
How do I install Sealeap Amazon Acos Diagnostics in Claude Code?
Run `npx skills add xjli360/sealeap-amazon-skills --skill sealeap-amazon-acos-diagnostics -a claude-code`. Or copy the skill folder (amazon-skills/amazon-official/sealeap-amazon-acos-diagnostics in xjli360/sealeap-amazon-skills) into .claude/skills/sealeap-amazon-acos-diagnostics in your project. Claude Code loads it when a task matches its description.
How do I install Sealeap Amazon Acos Diagnostics in Codex?
Run `npx skills add xjli360/sealeap-amazon-skills --skill sealeap-amazon-acos-diagnostics -a codex`. Or copy the skill folder (amazon-skills/amazon-official/sealeap-amazon-acos-diagnostics in xjli360/sealeap-amazon-skills) into .agents/skills/sealeap-amazon-acos-diagnostics in your project. Codex loads it when a task matches its description.
Can I use Sealeap Amazon Acos Diagnostics 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-acos-diagnostics -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-acos-diagnostics, .gemini/skills/sealeap-amazon-acos-diagnostics, .github/skills/sealeap-amazon-acos-diagnostics and .opencode/skills/sealeap-amazon-acos-diagnostics in your project.
What does Sealeap Amazon Acos Diagnostics need to run?
Going by SKILL.md and its folder, Sealeap Amazon Acos Diagnostics 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 Acos Diagnostics 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 Acos Diagnostics 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 Acos Diagnostics use?
Sealeap Amazon Acos Diagnostics 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 Acos Diagnostics 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 3.6k tokens, read only when the agent opens those files.
What are the alternatives to Sealeap Amazon Acos Diagnostics?
Skills that share tags, products or a category with Sealeap Amazon Acos Diagnostics: Ad Creative (LeoYeAI/openclaw-marketing-skills, 1k stars), Blog Google (AgriciDaniel/claude-blog, 2.3k stars), Ad Account Auditor (aaron-he-zhu/aaron-marketing-skills, 2.9k stars) and Ad Creative Builder (aaron-he-zhu/aaron-marketing-skills, 2.9k stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.
Who maintains Sealeap Amazon Acos Diagnostics?
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.