MCP Server Builder
anthropics/skills
Guides the design and implementation of Model Context Protocol servers in TypeScript or Python, from tool naming and error messages to evaluation.
Diagnose why an Amazon keyword converts poorly at top of search but better elsewhere by analyzing placement reports, effective bids, competitor context, and controlled experiments.
MITAuto-check passed
Install Sealeap Amazon Placement Conversion Gap
$ npx skills add xjli360/sealeap-amazon-skills --skill sealeap-amazon-placement-conversion-gap -a claude-codeProject install by default; add -g for ~/.claude/skills/.
$ gh skill install xjli360/sealeap-amazon-skills sealeap-amazon-placement-conversion-gap --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/douyin/qilin/sealeap-amazon-placement-conversion-gap .claude/skills/sealeap-amazon-placement-conversion-gap && 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-placement-conversion-gap" agent skill from https://github.com/xjli360/sealeap-amazon-skills/tree/main/amazon-skills/douyin/qilin/sealeap-amazon-placement-conversion-gap into .claude/skills/sealeap-amazon-placement-conversion-gap/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "sealeap-amazon-placement-conversion-gap", 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/douyin/qilin/sealeap-amazon-placement-conversion-gapType 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-placement-conversion-gap -a codexProject install goes to .agents/skills/; add -g for ~/.codex/skills/.
$ gh skill install xjli360/sealeap-amazon-skills sealeap-amazon-placement-conversion-gap --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/douyin/qilin/sealeap-amazon-placement-conversion-gap .agents/skills/sealeap-amazon-placement-conversion-gap && 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-placement-conversion-gap" agent skill from https://github.com/xjli360/sealeap-amazon-skills/tree/main/amazon-skills/douyin/qilin/sealeap-amazon-placement-conversion-gap into .agents/skills/sealeap-amazon-placement-conversion-gap/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "sealeap-amazon-placement-conversion-gap", 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-placement-conversion-gap -a cursorProject install goes to .agents/skills/; add -g for ~/.cursor/skills/.
$ gh skill install xjli360/sealeap-amazon-skills sealeap-amazon-placement-conversion-gap --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/douyin/qilin/sealeap-amazon-placement-conversion-gap .cursor/skills/sealeap-amazon-placement-conversion-gap && 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-placement-conversion-gap" agent skill from https://github.com/xjli360/sealeap-amazon-skills/tree/main/amazon-skills/douyin/qilin/sealeap-amazon-placement-conversion-gap into .cursor/skills/sealeap-amazon-placement-conversion-gap/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "sealeap-amazon-placement-conversion-gap", 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/douyin/qilin/sealeap-amazon-placement-conversion-gap--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-placement-conversion-gap -a gemini-cliProject install goes to .agents/skills/; add -g for ~/.gemini/skills/.
$ gh skill install xjli360/sealeap-amazon-skills sealeap-amazon-placement-conversion-gap --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/douyin/qilin/sealeap-amazon-placement-conversion-gap .gemini/skills/sealeap-amazon-placement-conversion-gap && 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-placement-conversion-gap" agent skill from https://github.com/xjli360/sealeap-amazon-skills/tree/main/amazon-skills/douyin/qilin/sealeap-amazon-placement-conversion-gap into .gemini/skills/sealeap-amazon-placement-conversion-gap/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "sealeap-amazon-placement-conversion-gap", 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-placement-conversion-gapInstalls 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-placement-conversion-gap -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/douyin/qilin/sealeap-amazon-placement-conversion-gap .github/skills/sealeap-amazon-placement-conversion-gap && 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-placement-conversion-gap" agent skill from https://github.com/xjli360/sealeap-amazon-skills/tree/main/amazon-skills/douyin/qilin/sealeap-amazon-placement-conversion-gap into .github/skills/sealeap-amazon-placement-conversion-gap/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "sealeap-amazon-placement-conversion-gap", 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-placement-conversion-gap -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-placement-conversion-gap --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/douyin/qilin/sealeap-amazon-placement-conversion-gap .opencode/skills/sealeap-amazon-placement-conversion-gap && 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-placement-conversion-gap" agent skill from https://github.com/xjli360/sealeap-amazon-skills/tree/main/amazon-skills/douyin/qilin/sealeap-amazon-placement-conversion-gap into .opencode/skills/sealeap-amazon-placement-conversion-gap/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "sealeap-amazon-placement-conversion-gap", 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-placement-conversion-gap- GitHub stars
- 247
- Token cost
- ~509 tokens
- SKILL.md length
- 86 words
- Files
- 4 (incl. scripts, references)
- Skills in repo
- 179
- Repo updated
- First seen
- Licence
- MIT
At a glance
Diagnose why an Amazon keyword converts poorly at top of search but better elsewhere by analyzing placement reports, effective bids, competitor context, and controlled experiments.
- Works in 6 steps: 还原有效竞价 → 比较广告位经济性 → 审视竞争环境 → …
- An exact keyword gains premium placement yet underperforms
- SKILL.md covers 目标, 适用任务, 开始前要拿到 and 不可妥协的边界, plus 4 more sections
- Runs Python scripts from its folder
What it does
Sealeap Amazon Placement Conversion Gap is an agent skill from xjli360/sealeap-amazon-skills. Diagnose why an Amazon keyword converts poorly at top of search but better elsewhere by analyzing placement reports, effective bids, competitor context, and controlled experiments. Use when an exact keyword gains premium placement yet underperforms, when raising bids shifts spend to the wrong placement, or when the user wants a placement test. Never claim exact page-position control.
Its SKILL.md is about 510 tokens, which your agent loads only when the skill is triggered. The skill folder holds 6 other files, including scripts and reference files (for example `agents/openai.yaml`, `references/mcp-data-plan.md` and `scripts/mcp_research.py`).
It works with Model Context Protocol. 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
- An exact keyword gains premium placement yet underperforms
- Raising bids shifts spend to the wrong placement
- The user wants a placement test
Example prompts
- “/sealeap-amazon-placement-conversion-gap”
Requirements
- Python 3
Workflow steps
6 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.
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 Placement Conversion Gap loads about 509 tokens when it runs, and up to ~2k if it reads all its reference files. Until then it costs about 107 tokens; SKILL.md has 86 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). 86 words, ~509 tokens.
Download SKILL.mdSave it as
.claude/skills/sealeap-amazon-placement-conversion-gap/SKILL.md (or your agent's skills folder). This skill also uses 3 other files; get the full folder from GitHub.- name
- sealeap-amazon-placement-conversion-gap
- description
- Diagnose why an Amazon keyword converts poorly at top of search but better elsewhere by analyzing placement reports, effective bids, competitor context, and controlled experiments. Use when an exact keyword gains premium placement yet underperforms, when raising bids shifts spend to the wrong placement, or when the user wants a placement test. Never claim exact page-position control.
Amazon 广告位转化差异诊断
目标
识别同一查询在不同广告位的转化差异，用有效竞价和单变量实验找到利润更好的流量环境。
适用任务
- 首页顶部高消耗但低转化。
- 降低竞价后订单反而改善。
- 调整基础竞价后预算跑向非目标广告位。
开始前要拿到
- 按广告位拆分的曝光、点击、花费、订单、销售额和新客数据。
- 基础竞价、动态竞价策略、广告位调整和历史修改时间。
- 商品价格、评分、配送、内容与查询环境的可见竞品快照。
缺失的数据要明确列为缺口，并把结论标成事实、估算或假设；不要补造数字。
不可妥协的边界
- 广告位分类不等于固定自然页码；不能保证卡在具体位置。
- 前台竞争环境是样本，不应据单次截图下结论。
- 竞价与位置系数的改动必须计算最坏有效竞价。
- 当前 Amazon 官方政策、帮助页、账户资格和后台实际字段优先于本 Skill 中的经验框架；规则可能变化时先核验。
- 默认提供诊断或草案。写入前展示对象、旧值、新值、影响、停止线与回退，核对用户已有授权是否覆盖对象、动作与预算；范围已明确授权时继续执行并回读核验，只有未覆盖或扩大的范围才请求批准。
- 不输出原素材的创作者身份、账号、链接、视频编号或可反查线索；当前业务证据的官方来源、采集时间和口径仍需保留。
第三方 MCP 数据
只有在本任务确实需要外部市场、竞品、关键词或公开网页证据时，才读取 references/mcp-data-plan.md，并使用 scripts/mcp_research.py。
- 先动态执行 tools/list、search-tools 和 describe，依据实时 inputSchema 构造参数，不照搬历史工具名。
- 凭证只从环境变量读取，不放进命令参数、URL、Skill、结果文件或 Git。
- tools/call 可能计费。调用前展示 Provider、工具名、无密钥参数、预计成本与输出位置，核对已有授权覆盖后才加 --allow-cost；该标志不是费用上限。
- 第三方数据标为估算或代理证据，记录 Provider、工具、无密钥参数、查询时间和原始结果位置；失败一次后记录缺口，不反复消耗额度。
- 脱敏结果用 --output 写到 Skill 包之外的任务私有目录；不假设安装位置受仓库 .gitignore 保护，不把运行结果写入 Skill 包。
工作流
1. 还原有效竞价
汇总基础竞价、动态策略和各位置系数，计算可能的有效出价范围。
2. 比较广告位经济性
对各位置计算 CTR、CVR、CPC、CPA、ACoS 和贡献利润，并标记样本强度。
3. 审视竞争环境
在标准化条件下抽样观察价格、评分、配送与卖点差异，把它作为解释线索。
4. 设计隔离实验
固定关键词、商品页和预算，只改变基础竞价或一个位置系数；设最小窗口和累计止损。
5. 调整流量组合
增加利润成立的位置权重，压低持续亏损位置；若所有位置转化差，回到 Listing 或关键词相关性。
6. 验证持续性
跨多个周期检查结果，防止促销、库存或竞品变化造成假胜利。
判断标准
- 有效竞价计算无遗漏。
- 位置对比使用相同或明确可比窗口。
- 结论区分数据事实、竞争环境推断和待验证假设。
必须交付的结果
- 广告位绩效和有效竞价表。
- 竞争环境假设。
- 单变量实验设计。
- 待批准位置调整与回滚条件。
结尾列出数据窗口、关键假设、证据缺口、风险和下一步；如包含待执行动作，单独放在“待批准变更”中。
© 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 3 other files (scripts, references) in amazon-skills/douyin/qilin/sealeap-amazon-placement-conversion-gap of xjli360/sealeap-amazon-skills.
- SKILL.md
- agents/openai.yaml
- references/mcp-data-plan.md
- scripts/mcp_research.py
Open the folder on GitHubat commit 497d4b8
Compare with similar skills
Sealeap Amazon Placement Conversion Gap 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 Placement Conversion Gap this skillxjli360/sealeap-amazon-skills | 247 | — | ~509 | Automated safety check: Pass | MIT | |
| MCP Server Builderanthropics/skills | 180k | 63 repos | ~2.3k | Automated safety check: Pass | Apache-2.0 | |
| MCP Server BuildershareAI-lab/learn-claude-code | 78k | 5 repos | ~1.2k | Automated safety check: Pass | MIT | |
| MCP Integration for Pluginsanthropics/claude-plugins-official | 38k | 11 repos | ~3.1k | Automated safety check: Pass | Apache-2.0 | |
| Figma use_figma Plugin API Ruleswarpdotdev/warp | 65k | 4 repos | ~4.4k | Automated safety check: Pass | AGPL-3.0 | |
| Stitch to Remotion Walkthrough Videosgoogle-labs-code/stitch-skills | 8.4k | 6 repos | ~3.2k | Automated safety check: Notes | Apache-2.0 |
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Questions about Sealeap Amazon Placement Conversion Gap
What does Sealeap Amazon Placement Conversion Gap do?
Diagnose why an Amazon keyword converts poorly at top of search but better elsewhere by analyzing placement reports, effective bids, competitor context, and controlled experiments. Sealeap Amazon Placement Conversion Gap is an agent skill from xjli360/sealeap-amazon-skills. Diagnose why an Amazon keyword converts poorly at top of search but better elsewhere by analyzing placement reports, effective bids, competitor context, and controlled experiments.
When should I use Sealeap Amazon Placement Conversion Gap?
Sealeap Amazon Placement Conversion Gap fits situations like: an exact keyword gains premium placement yet underperforms; raising bids shifts spend to the wrong placement; the user wants a placement test.
How do I install Sealeap Amazon Placement Conversion Gap in Claude Code?
Run `npx skills add xjli360/sealeap-amazon-skills --skill sealeap-amazon-placement-conversion-gap -a claude-code`. Or copy the skill folder (amazon-skills/douyin/qilin/sealeap-amazon-placement-conversion-gap in xjli360/sealeap-amazon-skills) into .claude/skills/sealeap-amazon-placement-conversion-gap in your project. Claude Code loads it when a task matches its description.
How do I install Sealeap Amazon Placement Conversion Gap in Codex?
Run `npx skills add xjli360/sealeap-amazon-skills --skill sealeap-amazon-placement-conversion-gap -a codex`. Or copy the skill folder (amazon-skills/douyin/qilin/sealeap-amazon-placement-conversion-gap in xjli360/sealeap-amazon-skills) into .agents/skills/sealeap-amazon-placement-conversion-gap in your project. Codex loads it when a task matches its description.
Can I use Sealeap Amazon Placement Conversion Gap 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-placement-conversion-gap -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-placement-conversion-gap, .gemini/skills/sealeap-amazon-placement-conversion-gap, .github/skills/sealeap-amazon-placement-conversion-gap and .opencode/skills/sealeap-amazon-placement-conversion-gap in your project.
What does Sealeap Amazon Placement Conversion Gap need to run?
Going by SKILL.md and its folder, Sealeap Amazon Placement Conversion Gap needs Python for the scripts in its folder. Our summary lists: Python 3.
Does Sealeap Amazon Placement Conversion Gap 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 Placement Conversion Gap 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 Placement Conversion Gap use?
Sealeap Amazon Placement Conversion Gap 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 Placement Conversion Gap use?
About 509 tokens (SKILL.md is roughly 2k 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 1.5k tokens, read only when the agent opens those files.
What are the alternatives to Sealeap Amazon Placement Conversion Gap?
Skills that share tags, products or a category with Sealeap Amazon Placement Conversion Gap: MCP Server Builder (anthropics/skills, 180k stars), MCP Server Builder (shareAI-lab/learn-claude-code, 78k stars), MCP Integration for Plugins (anthropics/claude-plugins-official, 38k stars) and Figma use_figma Plugin API Rules (warpdotdev/warp, 65k stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.
Who maintains Sealeap Amazon Placement Conversion Gap?
xjli360 (a GitHub user) maintains it in xjli360/sealeap-amazon-skills, which has 247 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.