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.
Agent skill
Sealeap Amazon Conversational Shopping Discoverability
Map verified product facts to customer shopping missions, structured attributes and localized Amazon listing content, then design observable conversational-shopping tests.
MITAuto-check passed
Install Sealeap Amazon Conversational Shopping Discoverability
$ npx skills add xjli360/sealeap-amazon-skills --skill sealeap-amazon-conversational-shopping-discoverability -a claude-codeProject install by default; add -g for ~/.claude/skills/.
$ gh skill install xjli360/sealeap-amazon-skills sealeap-amazon-conversational-shopping-discoverability --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-conversational-shopping-discoverability .claude/skills/sealeap-amazon-conversational-shopping-discoverability && 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-conversational-shopping-discoverability" agent skill from https://github.com/xjli360/sealeap-amazon-skills/tree/main/amazon-skills/douyin/qilin/sealeap-amazon-conversational-shopping-discoverability into .claude/skills/sealeap-amazon-conversational-shopping-discoverability/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "sealeap-amazon-conversational-shopping-discoverability", 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-conversational-shopping-discoverabilityType 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-conversational-shopping-discoverability -a codexProject install goes to .agents/skills/; add -g for ~/.codex/skills/.
$ gh skill install xjli360/sealeap-amazon-skills sealeap-amazon-conversational-shopping-discoverability --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-conversational-shopping-discoverability .agents/skills/sealeap-amazon-conversational-shopping-discoverability && 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-conversational-shopping-discoverability" agent skill from https://github.com/xjli360/sealeap-amazon-skills/tree/main/amazon-skills/douyin/qilin/sealeap-amazon-conversational-shopping-discoverability into .agents/skills/sealeap-amazon-conversational-shopping-discoverability/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "sealeap-amazon-conversational-shopping-discoverability", 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-conversational-shopping-discoverability -a cursorProject install goes to .agents/skills/; add -g for ~/.cursor/skills/.
$ gh skill install xjli360/sealeap-amazon-skills sealeap-amazon-conversational-shopping-discoverability --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-conversational-shopping-discoverability .cursor/skills/sealeap-amazon-conversational-shopping-discoverability && 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-conversational-shopping-discoverability" agent skill from https://github.com/xjli360/sealeap-amazon-skills/tree/main/amazon-skills/douyin/qilin/sealeap-amazon-conversational-shopping-discoverability into .cursor/skills/sealeap-amazon-conversational-shopping-discoverability/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "sealeap-amazon-conversational-shopping-discoverability", 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-conversational-shopping-discoverability--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-conversational-shopping-discoverability -a gemini-cliProject install goes to .agents/skills/; add -g for ~/.gemini/skills/.
$ gh skill install xjli360/sealeap-amazon-skills sealeap-amazon-conversational-shopping-discoverability --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-conversational-shopping-discoverability .gemini/skills/sealeap-amazon-conversational-shopping-discoverability && 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-conversational-shopping-discoverability" agent skill from https://github.com/xjli360/sealeap-amazon-skills/tree/main/amazon-skills/douyin/qilin/sealeap-amazon-conversational-shopping-discoverability into .gemini/skills/sealeap-amazon-conversational-shopping-discoverability/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "sealeap-amazon-conversational-shopping-discoverability", 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-conversational-shopping-discoverabilityInstalls 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-conversational-shopping-discoverability -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-conversational-shopping-discoverability .github/skills/sealeap-amazon-conversational-shopping-discoverability && 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-conversational-shopping-discoverability" agent skill from https://github.com/xjli360/sealeap-amazon-skills/tree/main/amazon-skills/douyin/qilin/sealeap-amazon-conversational-shopping-discoverability into .github/skills/sealeap-amazon-conversational-shopping-discoverability/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "sealeap-amazon-conversational-shopping-discoverability", 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-conversational-shopping-discoverability -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-conversational-shopping-discoverability --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-conversational-shopping-discoverability .opencode/skills/sealeap-amazon-conversational-shopping-discoverability && 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-conversational-shopping-discoverability" agent skill from https://github.com/xjli360/sealeap-amazon-skills/tree/main/amazon-skills/douyin/qilin/sealeap-amazon-conversational-shopping-discoverability into .opencode/skills/sealeap-amazon-conversational-shopping-discoverability/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "sealeap-amazon-conversational-shopping-discoverability", 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-conversational-shopping-discoverability- GitHub stars
- 251
- Token cost
- ~541 tokens
- SKILL.md length
- 95 words
- Files
- 5 (incl. scripts, references)
- Skills in repo
- 179
- Repo updated
- First seen
- Licence
- MIT
At a glance
Map verified product facts to customer shopping missions, structured attributes and localized Amazon listing content, then design observable conversational-shopping tests.
- Works in 6 steps: 建立事实底稿 → 补全属性 → 映射真实场景 → …
- Shopping Mission、场景化Listing、Alexa for Shopping、Rufus and AI购物可见性
- 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 Conversational Shopping Discoverability is an agent skill from xjli360/sealeap-amazon-skills. Map verified product facts to customer shopping missions, structured attributes and localized Amazon listing content, then design observable conversational-shopping tests. Use for Shopping Mission、场景化Listing、Alexa for Shopping、Rufus and AI购物可见性. Never seed reviews or Q&A, fabricate scenarios, or guarantee recommendation placement.
Its SKILL.md is about 540 tokens, which your agent loads only when the skill is triggered. The skill folder holds 7 other files, including scripts and reference files (for example `agents/openai.yaml`, `references/mcp-data-plan.md` and `references/shopping-mission.md`).
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
- Shopping Mission、场景化Listing、Alexa for Shopping、Rufus and AI购物可见性
Example prompts
- “/sealeap-amazon-conversational-shopping-discoverability”
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 Conversational Shopping Discoverability loads about 541 tokens when it runs, and up to ~2.7k if it reads all its reference files. Until then it costs about 97 tokens; SKILL.md has 95 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). 95 words, ~541 tokens.
Download SKILL.mdSave it as
.claude/skills/sealeap-amazon-conversational-shopping-discoverability/SKILL.md (or your agent's skills folder). This skill also uses 4 other files; get the full folder from GitHub.- name
- sealeap-amazon-conversational-shopping-discoverability
- description
- Map verified product facts to customer shopping missions, structured attributes and localized Amazon listing content, then design observable conversational-shopping tests. Use for Shopping Mission、场景化Listing、Alexa for Shopping、Rufus and AI购物可见性. Never seed reviews or Q&A, fabricate scenarios, or guarantee recommendation placement.
Amazon 对话式购物可发现性
目标
让商品事实和真实使用场景更完整、结构化、可验证，使搜索与购物助手更容易理解商品适用性。
适用任务
- Listing 属性不完整或场景表达薄弱。
- 准备适配 Rufus、Alexa 或其他对话式购物入口。
- 需要从真实客户问题和反馈中提炼场景内容。
开始前要拿到
- 产品规格、说明书、认证、兼容性、限制条件和真实场景证据。
- Listing 当前标题、五点、属性、图片、A+、视频和本地化版本。
- 真实客户搜索词、客服问题、退货原因和评论主题聚合。
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
- 不得安排、购买或撰写买家评论与 Q&A，也不得把营销话术伪装成客户内容。
- 所有场景、性能和兼容性声明必须有产品事实或证据支持。
- 不承诺被任何购物助手推荐；推荐机制和展示会变化，需核对当前官方信息。
- 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. 建立事实底稿
整理结构化规格、兼容性、使用限制、认证和证据来源，先解决内部矛盾。
2. 补全属性
填写当前类目允许且适用的属性，不用关键词堆砌替代字段含义。
3. 映射真实场景
读取 购物任务与证据映射，建立支持、条件支持、不支持和未知的任务卡，并按用户指定字段交付。
从搜索词、客服、退货和评论主题聚合出高频任务，用产品事实判断支持、不支持或需条件支持。
4. 改造内容
在标题、五点、图片、A+ 和视频中自然表达关键场景、限制和证明，保持可读性并做本地化。
5. 处理客户内容边界
只观察真实客户评论和问题的主题；品牌回答保持事实中立，不诱导评价或虚构提问。
6. 验证效果
用真实对话式查询做发现性检查，并跟踪会话、转化和退货变化；把结果标为相关观察。
判断标准
- 每条卖点和场景能回到事实证据。
- 属性、图片和文案之间一致。
- 不包含任何评论或 Q&A 植入动作。
必须交付的结果
- 产品事实与场景矩阵，含任务条件、证据 ID 和字段分配。
- 属性缺口清单。
- Listing 内容改写草稿。
- 对话式查询测试与监控方案。
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 4 other files (scripts, references) in amazon-skills/douyin/qilin/sealeap-amazon-conversational-shopping-discoverability of xjli360/sealeap-amazon-skills.
- SKILL.md
- agents/openai.yaml
- references/mcp-data-plan.md
- references/shopping-mission.md
- scripts/mcp_research.py
Open the folder on GitHubat commit 497d4b8
Compare with similar skills
Sealeap Amazon Conversational Shopping Discoverability 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 Conversational Shopping Discoverability this skillxjli360/sealeap-amazon-skills | 251 | — | ~541 | 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 | 4 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 | 8.5k | 6 repos | ~3.2k | Automated safety check: Notes | Apache-2.0 |
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Questions about Sealeap Amazon Conversational Shopping Discoverability
What does Sealeap Amazon Conversational Shopping Discoverability do?
Map verified product facts to customer shopping missions, structured attributes and localized Amazon listing content, then design observable conversational-shopping tests. Sealeap Amazon Conversational Shopping Discoverability is an agent skill from xjli360/sealeap-amazon-skills. Map verified product facts to customer shopping missions, structured attributes and localized Amazon listing content, then design observable conversational-shopping tests.
When should I use Sealeap Amazon Conversational Shopping Discoverability?
Sealeap Amazon Conversational Shopping Discoverability fits situations like: shopping Mission、场景化Listing、Alexa for Shopping、Rufus and AI购物可见性.
How do I install Sealeap Amazon Conversational Shopping Discoverability in Claude Code?
Run `npx skills add xjli360/sealeap-amazon-skills --skill sealeap-amazon-conversational-shopping-discoverability -a claude-code`. Or copy the skill folder (amazon-skills/douyin/qilin/sealeap-amazon-conversational-shopping-discoverability in xjli360/sealeap-amazon-skills) into .claude/skills/sealeap-amazon-conversational-shopping-discoverability in your project. Claude Code loads it when a task matches its description.
How do I install Sealeap Amazon Conversational Shopping Discoverability in Codex?
Run `npx skills add xjli360/sealeap-amazon-skills --skill sealeap-amazon-conversational-shopping-discoverability -a codex`. Or copy the skill folder (amazon-skills/douyin/qilin/sealeap-amazon-conversational-shopping-discoverability in xjli360/sealeap-amazon-skills) into .agents/skills/sealeap-amazon-conversational-shopping-discoverability in your project. Codex loads it when a task matches its description.
Can I use Sealeap Amazon Conversational Shopping Discoverability 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-conversational-shopping-discoverability -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-conversational-shopping-discoverability, .gemini/skills/sealeap-amazon-conversational-shopping-discoverability, .github/skills/sealeap-amazon-conversational-shopping-discoverability and .opencode/skills/sealeap-amazon-conversational-shopping-discoverability in your project.
What does Sealeap Amazon Conversational Shopping Discoverability need to run?
Going by SKILL.md and its folder, Sealeap Amazon Conversational Shopping Discoverability needs Python for the scripts in its folder. Our summary lists: Python 3.
Does Sealeap Amazon Conversational Shopping Discoverability 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 Conversational Shopping Discoverability 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 Conversational Shopping Discoverability use?
Sealeap Amazon Conversational Shopping Discoverability 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 Conversational Shopping Discoverability use?
About 541 tokens (SKILL.md is roughly 2.2k 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 2.2k tokens, read only when the agent opens those files.
What are the alternatives to Sealeap Amazon Conversational Shopping Discoverability?
Skills that share tags, products or a category with Sealeap Amazon Conversational Shopping Discoverability: 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 Conversational Shopping Discoverability?
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.