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.
Triage negative Amazon reviews into policy violations, suspected abuse, and genuine product feedback, then prepare factual official reports and product-remediation actions.
MITAuto-check passed
Install Sealeap Amazon Negative Review Response
$ npx skills add xjli360/sealeap-amazon-skills --skill sealeap-amazon-negative-review-response -a claude-codeProject install by default; add -g for ~/.claude/skills/.
$ gh skill install xjli360/sealeap-amazon-skills sealeap-amazon-negative-review-response --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-negative-review-response .claude/skills/sealeap-amazon-negative-review-response && 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-negative-review-response" agent skill from https://github.com/xjli360/sealeap-amazon-skills/tree/main/amazon-skills/douyin/qilin/sealeap-amazon-negative-review-response into .claude/skills/sealeap-amazon-negative-review-response/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "sealeap-amazon-negative-review-response", 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-negative-review-responseType 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-negative-review-response -a codexProject install goes to .agents/skills/; add -g for ~/.codex/skills/.
$ gh skill install xjli360/sealeap-amazon-skills sealeap-amazon-negative-review-response --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-negative-review-response .agents/skills/sealeap-amazon-negative-review-response && 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-negative-review-response" agent skill from https://github.com/xjli360/sealeap-amazon-skills/tree/main/amazon-skills/douyin/qilin/sealeap-amazon-negative-review-response into .agents/skills/sealeap-amazon-negative-review-response/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "sealeap-amazon-negative-review-response", 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-negative-review-response -a cursorProject install goes to .agents/skills/; add -g for ~/.cursor/skills/.
$ gh skill install xjli360/sealeap-amazon-skills sealeap-amazon-negative-review-response --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-negative-review-response .cursor/skills/sealeap-amazon-negative-review-response && 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-negative-review-response" agent skill from https://github.com/xjli360/sealeap-amazon-skills/tree/main/amazon-skills/douyin/qilin/sealeap-amazon-negative-review-response into .cursor/skills/sealeap-amazon-negative-review-response/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "sealeap-amazon-negative-review-response", 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-negative-review-response--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-negative-review-response -a gemini-cliProject install goes to .agents/skills/; add -g for ~/.gemini/skills/.
$ gh skill install xjli360/sealeap-amazon-skills sealeap-amazon-negative-review-response --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-negative-review-response .gemini/skills/sealeap-amazon-negative-review-response && 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-negative-review-response" agent skill from https://github.com/xjli360/sealeap-amazon-skills/tree/main/amazon-skills/douyin/qilin/sealeap-amazon-negative-review-response into .gemini/skills/sealeap-amazon-negative-review-response/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "sealeap-amazon-negative-review-response", 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-negative-review-responseInstalls 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-negative-review-response -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-negative-review-response .github/skills/sealeap-amazon-negative-review-response && 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-negative-review-response" agent skill from https://github.com/xjli360/sealeap-amazon-skills/tree/main/amazon-skills/douyin/qilin/sealeap-amazon-negative-review-response into .github/skills/sealeap-amazon-negative-review-response/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "sealeap-amazon-negative-review-response", 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-negative-review-response -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-negative-review-response --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-negative-review-response .opencode/skills/sealeap-amazon-negative-review-response && 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-negative-review-response" agent skill from https://github.com/xjli360/sealeap-amazon-skills/tree/main/amazon-skills/douyin/qilin/sealeap-amazon-negative-review-response into .opencode/skills/sealeap-amazon-negative-review-response/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "sealeap-amazon-negative-review-response", 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-negative-review-response- GitHub stars
- 251
- Token cost
- ~515 tokens
- SKILL.md length
- 89 words
- Files
- 4 (incl. scripts, references)
- Skills in repo
- 179
- Repo updated
- First seen
- Licence
- MIT
At a glance
Triage negative Amazon reviews into policy violations, suspected abuse, and genuine product feedback, then prepare factual official reports and product-remediation actions.
- Works in 6 steps: 保存原始证据 → 按准则分类 → 评估异常模式 → …
- The user asks whether a review can be removed
- 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 Negative Review Response is an agent skill from xjli360/sealeap-amazon-skills. Triage negative Amazon reviews into policy violations, suspected abuse, and genuine product feedback, then prepare factual official reports and product-remediation actions. Use when the user asks whether a review can be removed, how to report abusive content, or how to respond to a rating decline. Never fabricate evidence, contact reviewers off-platform, or incentivize review changes.
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
- The user asks whether a review can be removed
- How to report abusive content
- How to respond to a rating decline
Example prompts
- “/sealeap-amazon-negative-review-response”
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 Negative Review Response loads about 515 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 89 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). 89 words, ~515 tokens.
Download SKILL.mdSave it as
.claude/skills/sealeap-amazon-negative-review-response/SKILL.md (or your agent's skills folder). This skill also uses 3 other files; get the full folder from GitHub.- name
- sealeap-amazon-negative-review-response
- description
- Triage negative Amazon reviews into policy violations, suspected abuse, and genuine product feedback, then prepare factual official reports and product-remediation actions. Use when the user asks whether a review can be removed, how to report abusive content, or how to respond to a rating decline. Never fabricate evidence, contact reviewers off-platform, or incentivize review changes.
Amazon 差评合规处置
目标
只对明确违反社区准则的内容走官方报告，对真实差评回到产品和售后修复，并保留完整证据链。
适用任务
- 判断某条差评是否符合删除或报告条件。
- 怀疑恶意攻击但证据不足。
- 建立差评预警、分流和产品闭环。
开始前要拿到
- 评论原文、公开页面、时间、关联 ASIN 和可见上下文。
- 当前 Amazon Community Guidelines 与官方报告入口。
- 退货原因、客服工单、批次和质量记录。
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
- 不得捏造职业差评师、竞争对手攻击或买家身份；相似表达只算线索。
- 不得站外联系评论者、施压、补偿换改评或委托服务商磨掉差评。
- 真实且合规的负面体验不能因影响评分而要求删除。
- 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. 保存原始证据
记录完整评论、页面、时间和 ASIN，不截取会改变语义的片段，也不扩散个人信息。
2. 按准则分类
逐条比对辱骂、个人信息、促销内容、非商品反馈等当前规则，列出匹配条款和不确定点。
3. 评估异常模式
查看公开可验证的重复、集中时间或跨商品模式，但把它标为风险信号而非主体归因。
4. 选择官方路径
违规内容通过官方报告或支持渠道提交；用事实、链接和条款写简洁材料，不夸大。
5. 处理真实差评
把问题映射到设计、包装、说明、质检、变体或售后，确定负责人和验证指标。
6. 建立闭环
按主题跟踪差评率、退货率和修复后变化，重复问题升级为批次或产品决策。
判断标准
- 每条删除请求都有具体政策依据。
- 报告材料区分事实、推断和未知。
- 真实问题有产品或服务纠正措施。
必须交付的结果
- 评论合规分类表。
- 官方报告草稿与证据附件清单。
- 不可删除评论的产品修复计划。
- 差评主题预警看板字段。
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-negative-review-response 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 Negative Review Response 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 Negative Review Response this skillxjli360/sealeap-amazon-skills | 251 | — | ~515 | 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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Related
Works with
Questions about Sealeap Amazon Negative Review Response
What does Sealeap Amazon Negative Review Response do?
Triage negative Amazon reviews into policy violations, suspected abuse, and genuine product feedback, then prepare factual official reports and product-remediation actions. Sealeap Amazon Negative Review Response is an agent skill from xjli360/sealeap-amazon-skills. Triage negative Amazon reviews into policy violations, suspected abuse, and genuine product feedback, then prepare factual official reports and product-remediation actions.
When should I use Sealeap Amazon Negative Review Response?
Sealeap Amazon Negative Review Response fits situations like: the user asks whether a review can be removed; how to report abusive content; how to respond to a rating decline.
How do I install Sealeap Amazon Negative Review Response in Claude Code?
Run `npx skills add xjli360/sealeap-amazon-skills --skill sealeap-amazon-negative-review-response -a claude-code`. Or copy the skill folder (amazon-skills/douyin/qilin/sealeap-amazon-negative-review-response in xjli360/sealeap-amazon-skills) into .claude/skills/sealeap-amazon-negative-review-response in your project. Claude Code loads it when a task matches its description.
How do I install Sealeap Amazon Negative Review Response in Codex?
Run `npx skills add xjli360/sealeap-amazon-skills --skill sealeap-amazon-negative-review-response -a codex`. Or copy the skill folder (amazon-skills/douyin/qilin/sealeap-amazon-negative-review-response in xjli360/sealeap-amazon-skills) into .agents/skills/sealeap-amazon-negative-review-response in your project. Codex loads it when a task matches its description.
Can I use Sealeap Amazon Negative Review Response 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-negative-review-response -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-negative-review-response, .gemini/skills/sealeap-amazon-negative-review-response, .github/skills/sealeap-amazon-negative-review-response and .opencode/skills/sealeap-amazon-negative-review-response in your project.
What does Sealeap Amazon Negative Review Response need to run?
Going by SKILL.md and its folder, Sealeap Amazon Negative Review Response needs Python for the scripts in its folder. Our summary lists: Python 3.
Does Sealeap Amazon Negative Review Response 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 Negative Review Response 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 Negative Review Response use?
Sealeap Amazon Negative Review Response 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 Negative Review Response use?
About 515 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 Negative Review Response?
Skills that share tags, products or a category with Sealeap Amazon Negative Review Response: 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 Negative Review Response?
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.