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 Xiezhi Amazon Product Test Decision Tree
Choose a compliant Amazon validation method based on whether the uncertainty is concept acceptance, marketplace conversion, or paid-traffic economics.
MITAuto-check passed
Install Sealeap Xiezhi Amazon Product Test Decision Tree
$ npx skills add xjli360/sealeap-amazon-skills --skill sealeap-xiezhi-amazon-product-test-decision-tree -a claude-codeProject install by default; add -g for ~/.claude/skills/.
$ gh skill install xjli360/sealeap-amazon-skills sealeap-xiezhi-amazon-product-test-decision-tree --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/xiezhi/sealeap-xiezhi-amazon-product-test-decision-tree .claude/skills/sealeap-xiezhi-amazon-product-test-decision-tree && 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-xiezhi-amazon-product-test-decision-tree" agent skill from https://github.com/xjli360/sealeap-amazon-skills/tree/main/amazon-skills/douyin/xiezhi/sealeap-xiezhi-amazon-product-test-decision-tree into .claude/skills/sealeap-xiezhi-amazon-product-test-decision-tree/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "sealeap-xiezhi-amazon-product-test-decision-tree", 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/xiezhi/sealeap-xiezhi-amazon-product-test-decision-treeType 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-xiezhi-amazon-product-test-decision-tree -a codexProject install goes to .agents/skills/; add -g for ~/.codex/skills/.
$ gh skill install xjli360/sealeap-amazon-skills sealeap-xiezhi-amazon-product-test-decision-tree --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/xiezhi/sealeap-xiezhi-amazon-product-test-decision-tree .agents/skills/sealeap-xiezhi-amazon-product-test-decision-tree && 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-xiezhi-amazon-product-test-decision-tree" agent skill from https://github.com/xjli360/sealeap-amazon-skills/tree/main/amazon-skills/douyin/xiezhi/sealeap-xiezhi-amazon-product-test-decision-tree into .agents/skills/sealeap-xiezhi-amazon-product-test-decision-tree/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "sealeap-xiezhi-amazon-product-test-decision-tree", 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-xiezhi-amazon-product-test-decision-tree -a cursorProject install goes to .agents/skills/; add -g for ~/.cursor/skills/.
$ gh skill install xjli360/sealeap-amazon-skills sealeap-xiezhi-amazon-product-test-decision-tree --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/xiezhi/sealeap-xiezhi-amazon-product-test-decision-tree .cursor/skills/sealeap-xiezhi-amazon-product-test-decision-tree && 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-xiezhi-amazon-product-test-decision-tree" agent skill from https://github.com/xjli360/sealeap-amazon-skills/tree/main/amazon-skills/douyin/xiezhi/sealeap-xiezhi-amazon-product-test-decision-tree into .cursor/skills/sealeap-xiezhi-amazon-product-test-decision-tree/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "sealeap-xiezhi-amazon-product-test-decision-tree", 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/xiezhi/sealeap-xiezhi-amazon-product-test-decision-tree--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-xiezhi-amazon-product-test-decision-tree -a gemini-cliProject install goes to .agents/skills/; add -g for ~/.gemini/skills/.
$ gh skill install xjli360/sealeap-amazon-skills sealeap-xiezhi-amazon-product-test-decision-tree --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/xiezhi/sealeap-xiezhi-amazon-product-test-decision-tree .gemini/skills/sealeap-xiezhi-amazon-product-test-decision-tree && 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-xiezhi-amazon-product-test-decision-tree" agent skill from https://github.com/xjli360/sealeap-amazon-skills/tree/main/amazon-skills/douyin/xiezhi/sealeap-xiezhi-amazon-product-test-decision-tree into .gemini/skills/sealeap-xiezhi-amazon-product-test-decision-tree/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "sealeap-xiezhi-amazon-product-test-decision-tree", 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-xiezhi-amazon-product-test-decision-treeInstalls 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-xiezhi-amazon-product-test-decision-tree -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/xiezhi/sealeap-xiezhi-amazon-product-test-decision-tree .github/skills/sealeap-xiezhi-amazon-product-test-decision-tree && 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-xiezhi-amazon-product-test-decision-tree" agent skill from https://github.com/xjli360/sealeap-amazon-skills/tree/main/amazon-skills/douyin/xiezhi/sealeap-xiezhi-amazon-product-test-decision-tree into .github/skills/sealeap-xiezhi-amazon-product-test-decision-tree/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "sealeap-xiezhi-amazon-product-test-decision-tree", 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-xiezhi-amazon-product-test-decision-tree -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-xiezhi-amazon-product-test-decision-tree --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/xiezhi/sealeap-xiezhi-amazon-product-test-decision-tree .opencode/skills/sealeap-xiezhi-amazon-product-test-decision-tree && 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-xiezhi-amazon-product-test-decision-tree" agent skill from https://github.com/xjli360/sealeap-amazon-skills/tree/main/amazon-skills/douyin/xiezhi/sealeap-xiezhi-amazon-product-test-decision-tree into .opencode/skills/sealeap-xiezhi-amazon-product-test-decision-tree/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "sealeap-xiezhi-amazon-product-test-decision-tree", 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-xiezhi-amazon-product-test-decision-tree- GitHub stars
- 251
- Token cost
- ~517 tokens
- SKILL.md length
- 100 words
- Files
- 5 (incl. scripts, references)
- Skills in repo
- 179
- Repo updated
- First seen
- Licence
- MIT
At a glance
Choose a compliant Amazon validation method based on whether the uncertainty is concept acceptance, marketplace conversion, or paid-traffic economics.
- Works in 5 steps: 识别未知项 → 选择方法 → 定义成功 → …
- Deciding whether to test an original design
- 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 Xiezhi Amazon Product Test Decision Tree is an agent skill from xjli360/sealeap-amazon-skills. Choose a compliant Amazon validation method based on whether the uncertainty is concept acceptance, marketplace conversion, or paid-traffic economics. Use when deciding whether to test an original design, a differentiated mature product, or a proven-market candidate.
Its SKILL.md is about 520 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/playbook.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
- Deciding whether to test an original design
- A differentiated mature product
- A proven-market candidate
Example prompts
- “/sealeap-xiezhi-amazon-product-test-decision-tree”
Requirements
- Python 3
Workflow steps
5 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 Xiezhi Amazon Product Test Decision Tree loads about 517 tokens when it runs, and up to ~2.8k if it reads all its reference files. Until then it costs about 79 tokens; SKILL.md has 100 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). 100 words, ~517 tokens.
Download SKILL.mdSave it as
.claude/skills/sealeap-xiezhi-amazon-product-test-decision-tree/SKILL.md (or your agent's skills folder). This skill also uses 4 other files; get the full folder from GitHub.- name
- sealeap-xiezhi-amazon-product-test-decision-tree
- description
- Choose a compliant Amazon validation method based on whether the uncertainty is concept acceptance, marketplace conversion, or paid-traffic economics. Use when deciding whether to test an original design, a differentiated mature product, or a proven-market candidate.
Amazon 产品测款决策树
目标
只验证尚未被证据回答的最大不确定性，并用真实可履约库存、最小样本和明确止损控制测试成本。
适用任务
- 判断产品是否需要测款。
- 选择概念测试、FBM 或小批 FBA 验证。
- 定义测试指标、样本和退出条件。
开始前要拿到
- 产品创新程度及可比商品集合。
- 需要验证的具体假设。
- 真实可履约库存、配送时效和售后能力。
- CPC、CVR、毛利、首批量、测试预算与时间窗口。
缺少字段时列出证据缺口，并把相关结论标为 FACT、ESTIMATE、ASSUMPTION 或 UNKNOWN；不要补造数据。
不可妥协的边界
- 第三方数据均为估算或代理证据；Amazon 一方报告、后台实时字段和产品事实优先。
- 经验阈值只能作为可调起点，必须展示敏感性分析，不能写成 Amazon 官方规则。
- 不得捏造销量、搜索量、CPC、CVR、成本、认证、产品属性或消费者需求。
- 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。
- 不输出或保存素材来源身份、账号、链接、作品编号、互动数据、原始话术或其他可反查来源的线索。
- 禁止创建无库存、不可履约或计划取消订单的虚假 FBM Listing。
- 不得通过虚假订单、评价或变体操纵测试结果。
工作流
1. 识别未知项
区分需求是否存在、设计是否被接受、FBA 条件下的真实转化、CPC 和市场份额上限。
2. 选择方法
纯概念先做访谈/落地页/样品研究；有真实 FBM 库存时可测购买意向；成熟市场微创新用小批 FBA 测真实履约条件。
3. 定义成功
在测试前写明 CTR、CVR、CPC、订单、退款、评价和库存周转的目标区间与最低样本。
4. 限制暴露
只投入足以回答假设的真实库存和广告预算，并预先设累计亏损、时长和清货条件。
5. 决策复盘
将结果与先验区间比较，选择扩大、迭代、延长或停止；记录无法归因的混杂因素。
判断标准
- 已有可比市场和历史证据时，优先用单位经济与小批实销验证，不重复验证已知需求。
- FBM 与 FBA 的配送承诺不同，结果不能直接等同；方法必须匹配待验证问题。
- 测试不是追求几单，而是用最小成本降低最大不确定性。
第三方 MCP 数据
需要外部关键词、竞品、评论或公开网页证据时，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。 - 凭证只从环境变量读取，不进入参数、URL、Skill、终端输出或 Git。
- 可能计费的
tools/call先展示 Provider、工具、无密钥参数、预计成本与输出位置，核对已有授权；仅在授权覆盖本次范围时使用--allow-cost，该标志不是费用上限。 - 脱敏结果用
--output写入 Skill 包之外的任务私有目录；不假设安装位置受仓库.gitignore保护。第三方数据标为估算或代理证据。 - 失败一次后记录缺口，不以重复付费重试掩盖不可用状态。
必须交付的结果
- 不确定性清单
- 方法选择树
- 测试方案与样本门槛
- 预算/库存止损
- 扩大或停止结论
结尾列出站点、数据窗口、证据来源、关键假设、缺口、风险、下一步和所有待批准动作。证据不足时写 HOLD，不得包装成可直接执行。
执行细节、证据字段和质量检查见 references/playbook.md。
© 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/xiezhi/sealeap-xiezhi-amazon-product-test-decision-tree of xjli360/sealeap-amazon-skills.
- SKILL.md
- agents/openai.yaml
- references/mcp-data-plan.md
- references/playbook.md
- scripts/mcp_research.py
Open the folder on GitHubat commit 497d4b8
Compare with similar skills
Sealeap Xiezhi Amazon Product Test Decision Tree 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 Xiezhi Amazon Product Test Decision Tree this skillxjli360/sealeap-amazon-skills | 251 | — | ~517 | 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 Xiezhi Amazon Product Test Decision Tree
What does Sealeap Xiezhi Amazon Product Test Decision Tree do?
Choose a compliant Amazon validation method based on whether the uncertainty is concept acceptance, marketplace conversion, or paid-traffic economics. Sealeap Xiezhi Amazon Product Test Decision Tree is an agent skill from xjli360/sealeap-amazon-skills. Choose a compliant Amazon validation method based on whether the uncertainty is concept acceptance, marketplace conversion, or paid-traffic economics.
When should I use Sealeap Xiezhi Amazon Product Test Decision Tree?
Sealeap Xiezhi Amazon Product Test Decision Tree fits situations like: deciding whether to test an original design; A differentiated mature product; A proven-market candidate.
How do I install Sealeap Xiezhi Amazon Product Test Decision Tree in Claude Code?
Run `npx skills add xjli360/sealeap-amazon-skills --skill sealeap-xiezhi-amazon-product-test-decision-tree -a claude-code`. Or copy the skill folder (amazon-skills/douyin/xiezhi/sealeap-xiezhi-amazon-product-test-decision-tree in xjli360/sealeap-amazon-skills) into .claude/skills/sealeap-xiezhi-amazon-product-test-decision-tree in your project. Claude Code loads it when a task matches its description.
How do I install Sealeap Xiezhi Amazon Product Test Decision Tree in Codex?
Run `npx skills add xjli360/sealeap-amazon-skills --skill sealeap-xiezhi-amazon-product-test-decision-tree -a codex`. Or copy the skill folder (amazon-skills/douyin/xiezhi/sealeap-xiezhi-amazon-product-test-decision-tree in xjli360/sealeap-amazon-skills) into .agents/skills/sealeap-xiezhi-amazon-product-test-decision-tree in your project. Codex loads it when a task matches its description.
Can I use Sealeap Xiezhi Amazon Product Test Decision Tree 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-xiezhi-amazon-product-test-decision-tree -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-xiezhi-amazon-product-test-decision-tree, .gemini/skills/sealeap-xiezhi-amazon-product-test-decision-tree, .github/skills/sealeap-xiezhi-amazon-product-test-decision-tree and .opencode/skills/sealeap-xiezhi-amazon-product-test-decision-tree in your project.
What does Sealeap Xiezhi Amazon Product Test Decision Tree need to run?
Going by SKILL.md and its folder, Sealeap Xiezhi Amazon Product Test Decision Tree needs Python for the scripts in its folder. Our summary lists: Python 3.
Does Sealeap Xiezhi Amazon Product Test Decision Tree 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 Xiezhi Amazon Product Test Decision Tree 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 Xiezhi Amazon Product Test Decision Tree use?
Sealeap Xiezhi Amazon Product Test Decision Tree 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 Xiezhi Amazon Product Test Decision Tree use?
About 517 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 2.3k tokens, read only when the agent opens those files.
What are the alternatives to Sealeap Xiezhi Amazon Product Test Decision Tree?
Skills that share tags, products or a category with Sealeap Xiezhi Amazon Product Test Decision Tree: 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 Xiezhi Amazon Product Test Decision Tree?
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.