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 New Product Conversion Readiness
Diagnose why an Amazon new product cannot gain traction by separating retail-readiness, traffic relevance, click-through, conversion, economics, and feedback quality.
MITAuto-check passed
Install Sealeap Amazon New Product Conversion Readiness
$ npx skills add xjli360/sealeap-amazon-skills --skill sealeap-amazon-new-product-conversion-readiness -a claude-codeProject install by default; add -g for ~/.claude/skills/.
$ gh skill install xjli360/sealeap-amazon-skills sealeap-amazon-new-product-conversion-readiness --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-new-product-conversion-readiness .claude/skills/sealeap-amazon-new-product-conversion-readiness && 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-new-product-conversion-readiness" agent skill from https://github.com/xjli360/sealeap-amazon-skills/tree/main/amazon-skills/douyin/qilin/sealeap-amazon-new-product-conversion-readiness into .claude/skills/sealeap-amazon-new-product-conversion-readiness/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "sealeap-amazon-new-product-conversion-readiness", 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-new-product-conversion-readinessType 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-new-product-conversion-readiness -a codexProject install goes to .agents/skills/; add -g for ~/.codex/skills/.
$ gh skill install xjli360/sealeap-amazon-skills sealeap-amazon-new-product-conversion-readiness --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-new-product-conversion-readiness .agents/skills/sealeap-amazon-new-product-conversion-readiness && 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-new-product-conversion-readiness" agent skill from https://github.com/xjli360/sealeap-amazon-skills/tree/main/amazon-skills/douyin/qilin/sealeap-amazon-new-product-conversion-readiness into .agents/skills/sealeap-amazon-new-product-conversion-readiness/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "sealeap-amazon-new-product-conversion-readiness", 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-new-product-conversion-readiness -a cursorProject install goes to .agents/skills/; add -g for ~/.cursor/skills/.
$ gh skill install xjli360/sealeap-amazon-skills sealeap-amazon-new-product-conversion-readiness --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-new-product-conversion-readiness .cursor/skills/sealeap-amazon-new-product-conversion-readiness && 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-new-product-conversion-readiness" agent skill from https://github.com/xjli360/sealeap-amazon-skills/tree/main/amazon-skills/douyin/qilin/sealeap-amazon-new-product-conversion-readiness into .cursor/skills/sealeap-amazon-new-product-conversion-readiness/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "sealeap-amazon-new-product-conversion-readiness", 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-new-product-conversion-readiness--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-new-product-conversion-readiness -a gemini-cliProject install goes to .agents/skills/; add -g for ~/.gemini/skills/.
$ gh skill install xjli360/sealeap-amazon-skills sealeap-amazon-new-product-conversion-readiness --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-new-product-conversion-readiness .gemini/skills/sealeap-amazon-new-product-conversion-readiness && 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-new-product-conversion-readiness" agent skill from https://github.com/xjli360/sealeap-amazon-skills/tree/main/amazon-skills/douyin/qilin/sealeap-amazon-new-product-conversion-readiness into .gemini/skills/sealeap-amazon-new-product-conversion-readiness/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "sealeap-amazon-new-product-conversion-readiness", 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-new-product-conversion-readinessInstalls 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-new-product-conversion-readiness -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-new-product-conversion-readiness .github/skills/sealeap-amazon-new-product-conversion-readiness && 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-new-product-conversion-readiness" agent skill from https://github.com/xjli360/sealeap-amazon-skills/tree/main/amazon-skills/douyin/qilin/sealeap-amazon-new-product-conversion-readiness into .github/skills/sealeap-amazon-new-product-conversion-readiness/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "sealeap-amazon-new-product-conversion-readiness", 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-new-product-conversion-readiness -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-new-product-conversion-readiness --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-new-product-conversion-readiness .opencode/skills/sealeap-amazon-new-product-conversion-readiness && 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-new-product-conversion-readiness" agent skill from https://github.com/xjli360/sealeap-amazon-skills/tree/main/amazon-skills/douyin/qilin/sealeap-amazon-new-product-conversion-readiness into .opencode/skills/sealeap-amazon-new-product-conversion-readiness/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "sealeap-amazon-new-product-conversion-readiness", 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-new-product-conversion-readiness- GitHub stars
- 251
- Token cost
- ~524 tokens
- SKILL.md length
- 92 words
- Files
- 4 (incl. scripts, references)
- Skills in repo
- 179
- Repo updated
- First seen
- Licence
- MIT
At a glance
Diagnose why an Amazon new product cannot gain traction by separating retail-readiness, traffic relevance, click-through, conversion, economics, and feedback quality.
- Works in 6 steps: 检查可售漏斗 → 诊断点击 → 诊断转化 → …
- A new ASIN is not launching
- 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 New Product Conversion Readiness is an agent skill from xjli360/sealeap-amazon-skills. Diagnose why an Amazon new product cannot gain traction by separating retail-readiness, traffic relevance, click-through, conversion, economics, and feedback quality. Use when a new ASIN is not launching, ads are not converting, or the team is tempted to use fake reviews, inflated reference prices, or artificial orders. Replace unsafe tactics with compliant conversion and advertising work.
Its SKILL.md is about 520 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
- A new ASIN is not launching
- Ads are not converting
- The team is tempted to use fake reviews
- Inflated reference prices
Example prompts
- “/sealeap-amazon-new-product-conversion-readiness”
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 New Product Conversion Readiness loads about 524 tokens when it runs, and up to ~2.1k if it reads all its reference files. Until then it costs about 110 tokens; SKILL.md has 92 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). 92 words, ~524 tokens.
Download SKILL.mdSave it as
.claude/skills/sealeap-amazon-new-product-conversion-readiness/SKILL.md (or your agent's skills folder). This skill also uses 3 other files; get the full folder from GitHub.- name
- sealeap-amazon-new-product-conversion-readiness
- description
- Diagnose why an Amazon new product cannot gain traction by separating retail-readiness, traffic relevance, click-through, conversion, economics, and feedback quality. Use when a new ASIN is not launching, ads are not converting, or the team is tempted to use fake reviews, inflated reference prices, or artificial orders. Replace unsafe tactics with compliant conversion and advertising work.
Amazon 新品转化就绪诊断
目标
找出新品推不动是可售、点击、转化、流量还是经济性问题，并先修承接短板再扩大流量。
适用任务
- 新品有曝光或点击但没有订单。
- 团队把评论数量当作唯一启动条件。
- 需要建立商品页与广告的联合排查顺序。
开始前要拿到
- 可售状态、库存、Buy Box、价格、优惠和配送承诺。
- 主图、标题、五点、A+、视频、属性、合规评价和退货反馈。
- 查询级曝光、CTR、CVR、CPA 与竞品可比数据。
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
- 拒绝虚假订单、免评单、测评、付费好评、评论合并和人为操纵参考价。
- 评论数量少不等于必须暂停推广；用真实转化障碍判断。
- 不得把广告带来的短期变化宣称为平台认可或排名因果。
- 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. 检查可售漏斗
从抑制、库存、配送、Featured Offer 和价格开始，先排除根本无法顺畅下单的问题。
2. 诊断点击
对比同一查询环境下的主图、价格、优惠、评分和标题相关性，找出 CTR 短板。
3. 诊断转化
检查内容证据、功能表达、变体选择、风险消除、真实评价主题和售后信息。
4. 审查流量
确认广告查询与商品事实匹配，集中预算到高意图主题，否定明确无关流量。
5. 建立合规反馈基础
使用符合资格的 Vine、Request a Review 和中立售后；把差评主题转为产品或说明改进。
6. 设置验证门槛
每个改动设前后窗口、目标指标和止损，承接仍弱时回到产品决策而不是继续烧钱。
判断标准
- 漏斗各层使用对应指标，不用评论数解释所有问题。
- 商品页改动有事实依据，不制造虚假稀缺、折扣或证明。
- 广告预算只在承接达标后扩大。
必须交付的结果
- 新品漏斗诊断。
- 商品页优先修复清单。
- 合规评价与售后计划。
- 精准流量验证方案和停止条件。
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-new-product-conversion-readiness 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 New Product Conversion Readiness 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 New Product Conversion Readiness this skillxjli360/sealeap-amazon-skills | 251 | — | ~524 | 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 New Product Conversion Readiness
What does Sealeap Amazon New Product Conversion Readiness do?
Diagnose why an Amazon new product cannot gain traction by separating retail-readiness, traffic relevance, click-through, conversion, economics, and feedback quality. Sealeap Amazon New Product Conversion Readiness is an agent skill from xjli360/sealeap-amazon-skills. Diagnose why an Amazon new product cannot gain traction by separating retail-readiness, traffic relevance, click-through, conversion, economics, and feedback quality.
When should I use Sealeap Amazon New Product Conversion Readiness?
Sealeap Amazon New Product Conversion Readiness fits situations like: A new ASIN is not launching; ads are not converting; the team is tempted to use fake reviews; inflated reference prices.
How do I install Sealeap Amazon New Product Conversion Readiness in Claude Code?
Run `npx skills add xjli360/sealeap-amazon-skills --skill sealeap-amazon-new-product-conversion-readiness -a claude-code`. Or copy the skill folder (amazon-skills/douyin/qilin/sealeap-amazon-new-product-conversion-readiness in xjli360/sealeap-amazon-skills) into .claude/skills/sealeap-amazon-new-product-conversion-readiness in your project. Claude Code loads it when a task matches its description.
How do I install Sealeap Amazon New Product Conversion Readiness in Codex?
Run `npx skills add xjli360/sealeap-amazon-skills --skill sealeap-amazon-new-product-conversion-readiness -a codex`. Or copy the skill folder (amazon-skills/douyin/qilin/sealeap-amazon-new-product-conversion-readiness in xjli360/sealeap-amazon-skills) into .agents/skills/sealeap-amazon-new-product-conversion-readiness in your project. Codex loads it when a task matches its description.
Can I use Sealeap Amazon New Product Conversion Readiness 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-new-product-conversion-readiness -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-new-product-conversion-readiness, .gemini/skills/sealeap-amazon-new-product-conversion-readiness, .github/skills/sealeap-amazon-new-product-conversion-readiness and .opencode/skills/sealeap-amazon-new-product-conversion-readiness in your project.
What does Sealeap Amazon New Product Conversion Readiness need to run?
Going by SKILL.md and its folder, Sealeap Amazon New Product Conversion Readiness needs Python for the scripts in its folder. Our summary lists: Python 3.
Does Sealeap Amazon New Product Conversion Readiness 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 New Product Conversion Readiness 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 New Product Conversion Readiness use?
Sealeap Amazon New Product Conversion Readiness 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 New Product Conversion Readiness use?
About 524 tokens (SKILL.md is roughly 2.1k 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 New Product Conversion Readiness?
Skills that share tags, products or a category with Sealeap Amazon New Product Conversion Readiness: 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 New Product Conversion Readiness?
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.