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.
Turn verified product facts and third-party keyword exports into an auditable AI workflow for filtering queries, selecting ad candidates, drafting listing fields, and preserving evidence for every…
MITAuto-check passed
Install Sealeap Baize Amazon AI Listing Pipeline
$ npx skills add xjli360/sealeap-amazon-skills --skill sealeap-baize-amazon-ai-listing-pipeline -a claude-codeProject install by default; add -g for ~/.claude/skills/.
$ gh skill install xjli360/sealeap-amazon-skills sealeap-baize-amazon-ai-listing-pipeline --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/baize/sealeap-baize-amazon-ai-listing-pipeline .claude/skills/sealeap-baize-amazon-ai-listing-pipeline && 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-baize-amazon-ai-listing-pipeline" agent skill from https://github.com/xjli360/sealeap-amazon-skills/tree/main/amazon-skills/douyin/baize/sealeap-baize-amazon-ai-listing-pipeline into .claude/skills/sealeap-baize-amazon-ai-listing-pipeline/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "sealeap-baize-amazon-ai-listing-pipeline", 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/baize/sealeap-baize-amazon-ai-listing-pipelineType 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-baize-amazon-ai-listing-pipeline -a codexProject install goes to .agents/skills/; add -g for ~/.codex/skills/.
$ gh skill install xjli360/sealeap-amazon-skills sealeap-baize-amazon-ai-listing-pipeline --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/baize/sealeap-baize-amazon-ai-listing-pipeline .agents/skills/sealeap-baize-amazon-ai-listing-pipeline && 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-baize-amazon-ai-listing-pipeline" agent skill from https://github.com/xjli360/sealeap-amazon-skills/tree/main/amazon-skills/douyin/baize/sealeap-baize-amazon-ai-listing-pipeline into .agents/skills/sealeap-baize-amazon-ai-listing-pipeline/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "sealeap-baize-amazon-ai-listing-pipeline", 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-baize-amazon-ai-listing-pipeline -a cursorProject install goes to .agents/skills/; add -g for ~/.cursor/skills/.
$ gh skill install xjli360/sealeap-amazon-skills sealeap-baize-amazon-ai-listing-pipeline --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/baize/sealeap-baize-amazon-ai-listing-pipeline .cursor/skills/sealeap-baize-amazon-ai-listing-pipeline && 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-baize-amazon-ai-listing-pipeline" agent skill from https://github.com/xjli360/sealeap-amazon-skills/tree/main/amazon-skills/douyin/baize/sealeap-baize-amazon-ai-listing-pipeline into .cursor/skills/sealeap-baize-amazon-ai-listing-pipeline/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "sealeap-baize-amazon-ai-listing-pipeline", 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/baize/sealeap-baize-amazon-ai-listing-pipeline--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-baize-amazon-ai-listing-pipeline -a gemini-cliProject install goes to .agents/skills/; add -g for ~/.gemini/skills/.
$ gh skill install xjli360/sealeap-amazon-skills sealeap-baize-amazon-ai-listing-pipeline --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/baize/sealeap-baize-amazon-ai-listing-pipeline .gemini/skills/sealeap-baize-amazon-ai-listing-pipeline && 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-baize-amazon-ai-listing-pipeline" agent skill from https://github.com/xjli360/sealeap-amazon-skills/tree/main/amazon-skills/douyin/baize/sealeap-baize-amazon-ai-listing-pipeline into .gemini/skills/sealeap-baize-amazon-ai-listing-pipeline/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "sealeap-baize-amazon-ai-listing-pipeline", 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-baize-amazon-ai-listing-pipelineInstalls 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-baize-amazon-ai-listing-pipeline -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/baize/sealeap-baize-amazon-ai-listing-pipeline .github/skills/sealeap-baize-amazon-ai-listing-pipeline && 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-baize-amazon-ai-listing-pipeline" agent skill from https://github.com/xjli360/sealeap-amazon-skills/tree/main/amazon-skills/douyin/baize/sealeap-baize-amazon-ai-listing-pipeline into .github/skills/sealeap-baize-amazon-ai-listing-pipeline/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "sealeap-baize-amazon-ai-listing-pipeline", 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-baize-amazon-ai-listing-pipeline -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-baize-amazon-ai-listing-pipeline --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/baize/sealeap-baize-amazon-ai-listing-pipeline .opencode/skills/sealeap-baize-amazon-ai-listing-pipeline && 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-baize-amazon-ai-listing-pipeline" agent skill from https://github.com/xjli360/sealeap-amazon-skills/tree/main/amazon-skills/douyin/baize/sealeap-baize-amazon-ai-listing-pipeline into .opencode/skills/sealeap-baize-amazon-ai-listing-pipeline/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "sealeap-baize-amazon-ai-listing-pipeline", 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-baize-amazon-ai-listing-pipeline- GitHub stars
- 251
- Token cost
- ~573 tokens
- SKILL.md length
- 134 words
- Files
- 5 (incl. scripts, references)
- Skills in repo
- 179
- Repo updated
- First seen
- Licence
- MIT
At a glance
Turn verified product facts and third-party keyword exports into an auditable AI workflow for filtering queries, selecting ad candidates, drafting listing fields, and preserving evidence for every…
- Works in 4 steps: 诊断：读取现状、证据和缺口，不生成线上写入动作。 → 方案草案：输出可审核的结构、参数范围、实验和回退值。 → 执行准备：只生成待批准变更表或 API/控制台操作草案。 → …
- AI写Listing、关键词表清洗、竞品词过滤、广告词选择、标题五点和后台词草拟
- SKILL.md covers 目标, 不可妥协的边界, 先判断任务模式 and 开始前要拿到, plus 3 more sections
- Runs Python scripts from its folder
What it does
Sealeap Baize Amazon AI Listing Pipeline is an agent skill from xjli360/sealeap-amazon-skills. Turn verified product facts and third-party keyword exports into an auditable AI workflow for filtering queries, selecting ad candidates, drafting listing fields, and preserving evidence for every claim. Use for AI写Listing、关键词表清洗、竞品词过滤、广告词选择、标题五点和后台词草拟. Not for invented claims or direct publishing.
Its SKILL.md is about 570 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
- AI写Listing、关键词表清洗、竞品词过滤、广告词选择、标题五点和后台词草拟
Example prompts
- “/sealeap-baize-amazon-ai-listing-pipeline”
Requirements
- Python 3
Workflow steps
4 steps, taken from the first numbered list in SKILL.md.
- 诊断：读取现状、证据和缺口，不生成线上写入动作。
- 方案草案：输出可审核的结构、参数范围、实验和回退值。
- 执行准备：只生成待批准变更表或 API/控制台操作草案。
- 已批准执行：仅对用户在当前会话明确批准的对象和字段执行，并立即回读核验。
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 Baize Amazon AI Listing Pipeline loads about 573 tokens when it runs, and up to ~2.6k if it reads all its reference files. Until then it costs about 85 tokens; SKILL.md has 134 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). 134 words, ~573 tokens.
Download SKILL.mdSave it as
.claude/skills/sealeap-baize-amazon-ai-listing-pipeline/SKILL.md (or your agent's skills folder). This skill also uses 4 other files; get the full folder from GitHub.- name
- sealeap-baize-amazon-ai-listing-pipeline
- description
- Turn verified product facts and third-party keyword exports into an auditable AI workflow for filtering queries, selecting ad candidates, drafting listing fields, and preserving evidence for every claim. Use for AI写Listing、关键词表清洗、竞品词过滤、广告词选择、标题五点和后台词草拟. Not for invented claims or direct publishing.
Amazon AI Listing 生产线
目标
Turn verified product facts and third-party keyword exports into an auditable AI workflow for filtering queries, selecting ad candidates, drafting listing fields, and preserving evidence for every claim.
不可妥协的边界
- 当前 Amazon 官方政策、账户资格、站点字段和一方数据优先于本 Skill 的经验框架。
- 第三方数据一律标为估算或前台观测，不得写成 Amazon 一方事实。
- 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。
- 一次实验只改变一个主要变量，并记录基线、样本、成功、停止和回退条件。
- 不得复制来源材料或竞品表达；输出必须按当前任务重新组织并可由现有证据支撑。
- 自然位置只是筛选先验；词义和产品事实决定能否使用。
- AI 不得补造材质、尺寸、认证、功效、比较或促销信息。
先判断任务模式
- 诊断：读取现状、证据和缺口，不生成线上写入动作。
- 方案草案：输出可审核的结构、参数范围、实验和回退值。
- 执行准备：只生成待批准变更表或 API/控制台操作草案。
- 已批准执行：仅对用户在当前会话明确批准的对象和字段执行，并立即回读核验。
用户未指定时采用“诊断”。
开始前要拿到
- 目标 marketplace、产品事实、品牌语气和当前政策约束
- 已授权的 Listing、关键词、评论/VOC、图片和竞品证据
- 每项数据的来源、时间、站点、样本和限制
- 人工审核人、发布边界和不可生成的声明或视觉特征
缺失项必须标为 NEEDS_EVIDENCE；不得猜数字、补属性或把不同站点、ASIN、变体、币种和时间窗混在一起。
工作流
先读取 references/playbook.md，确认该方法适用于当前对象。按以下顺序执行：
- 输入产品事实、目标站点、相似竞品和带来源的关键词表。
- 清理空值与明显不相关词，再以自然可见度形成候选集。
- 让模型逐词对照多个竞品属性和本品事实，输出保留或删除理由。
- 区分精准广告候选、探索词根、Listing 前台词和后台词。
- 按购买决策顺序生成标题、要点和描述，并附关键词与事实映射。
- 人工复核字符限制、敏感声明和目标站点当前规则。
最后做数据充分性检查，并把结论分成 FACT / ESTIMATE / HYPOTHESIS / UNKNOWN。若关键证据不足，状态写 HOLD。
第三方 MCP 数据
仅在自有数据不足且当前任务确实需要外部证据时，读取 references/mcp-data-plan.md，再使用 scripts/mcp_research.py。本 Skill 的外部取数目的：取得关键词、竞品 Listing 和搜索需求代理数据；模型只处理已取得证据。
- 先
doctor，再search-tools和describe；工具名及参数以实时tools/list与inputSchema为准。 - Token 只从环境变量读取。不得写入命令参数、URL、Skill、报告、日志或 Git。
tools/call或 Actor 可能计费；先展示 Provider、工具、无密钥业务参数、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。
必须交付的结果
- 清洗日志
- 关键词去向表
- Listing 草稿
- 事实与声明审计
- 数据范围、来源、采集时间、样本与限制。
- 关键假设、待补证据、风险和不可确定项。
- 若有动作：对象、旧值、新值、预期、停止条件、回退值与审批状态。
方案状态使用 READY FOR REVIEW / DRAFT / HOLD / STOP；如已执行，另行记录实际结果及回读证据。未得到明确批准时，不得声称已修改线上对象。
© 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/baize/sealeap-baize-amazon-ai-listing-pipeline 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 Baize Amazon AI Listing Pipeline 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 Baize Amazon AI Listing Pipeline this skillxjli360/sealeap-amazon-skills | 251 | — | ~573 | 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 |
Similar skills
- Official
MCP Server Builder
shareAI-lab/learn-claude-code
Walks through building MCP servers in Python or TypeScript that expose tools, resources and prompts to Claude, with templates, registration and testing.
- Official
MCP Integration for Plugins
anthropics/claude-plugins-official
Explains how to bundle Model Context Protocol servers in a Claude Code plugin, covering config files, stdio, SSE, HTTP and WebSocket server types, and authentication.
Figma use_figma Plugin API Rules
warpdotdev/warp
Required groundwork before any use_figma call: the rules and reference files for running JavaScript in a Figma file through the Plugin API without common failures.
- Official
Stitch to Remotion Walkthrough Videos
google-labs-code/stitch-skills
Builds walkthrough videos from Stitch design projects using Remotion, with transitions, zoom effects and text overlays on each screen.
MCP Development
coollabsio/coolify
A skill your agent uses for Laravel MCP development. An agent skill from coollabsio/coolify.
More from xjli360/sealeap-amazon-skills
All 179 skills in this repoSealeap Amazon Acos Diagnostics
xjli360/sealeap-amazon-skills
Diagnose Amazon Ads ACOS with reconciled CTR, CPC, CVR, AOV, ROAS, TACOS, placement, search-term, benchmark, attribution, and contribution-margin evidence, then produce a single-variable…
Sealeap Amazon Ca Apparel Ads
xjli360/sealeap-amazon-skills
Diagnose and draft Amazon Canada apparel advertising plans with lifecycle and seasonal timing, English/French search coverage, account evidence, profitability guardrails, and approval-ready…
Sealeap Amazon Listing Optimizer
xjli360/sealeap-amazon-skills
Audit, diagnose, rewrite, creatively brief, test, and safely prepare updates for Amazon product detail pages using live marketplace and product-type requirements, verified product facts, Brand…
Sealeap Amazon Prime Day Planning
xjli360/sealeap-amazon-skills
Filter, interpret, and turn the authorized 2025 Amazon Prime Day advertising insight records into a qualified event plan without averaging incompatible slices or treating historical benchmarks as…
Sealeap Amazon Product Targeting
xjli360/sealeap-amazon-skills
Research, diagnose, and draft Amazon Ads ASIN and category product-targeting plans that complement keyword targeting, including audience expansion, competitor and category traffic, cross-sell…
Sealeap Amazon Acos Conversion Diagnostics
xjli360/sealeap-amazon-skills
Diagnose high Amazon Ads ACoS by decomposing CPC, conversion rate, price, query mix, placement mix, and sample sufficiency.
Related
Works with
Questions about Sealeap Baize Amazon AI Listing Pipeline
What does Sealeap Baize Amazon AI Listing Pipeline do?
Turn verified product facts and third-party keyword exports into an auditable AI workflow for filtering queries, selecting ad candidates, drafting listing fields, and preserving evidence for every…. Sealeap Baize Amazon AI Listing Pipeline is an agent skill from xjli360/sealeap-amazon-skills. Turn verified product facts and third-party keyword exports into an auditable AI workflow for filtering queries, selecting ad candidates, drafting listing fields, and preserving evidence for every claim.
When should I use Sealeap Baize Amazon AI Listing Pipeline?
Sealeap Baize Amazon AI Listing Pipeline fits situations like: AI写Listing、关键词表清洗、竞品词过滤、广告词选择、标题五点和后台词草拟.
How do I install Sealeap Baize Amazon AI Listing Pipeline in Claude Code?
Run `npx skills add xjli360/sealeap-amazon-skills --skill sealeap-baize-amazon-ai-listing-pipeline -a claude-code`. Or copy the skill folder (amazon-skills/douyin/baize/sealeap-baize-amazon-ai-listing-pipeline in xjli360/sealeap-amazon-skills) into .claude/skills/sealeap-baize-amazon-ai-listing-pipeline in your project. Claude Code loads it when a task matches its description.
How do I install Sealeap Baize Amazon AI Listing Pipeline in Codex?
Run `npx skills add xjli360/sealeap-amazon-skills --skill sealeap-baize-amazon-ai-listing-pipeline -a codex`. Or copy the skill folder (amazon-skills/douyin/baize/sealeap-baize-amazon-ai-listing-pipeline in xjli360/sealeap-amazon-skills) into .agents/skills/sealeap-baize-amazon-ai-listing-pipeline in your project. Codex loads it when a task matches its description.
Can I use Sealeap Baize Amazon AI Listing Pipeline 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-baize-amazon-ai-listing-pipeline -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-baize-amazon-ai-listing-pipeline, .gemini/skills/sealeap-baize-amazon-ai-listing-pipeline, .github/skills/sealeap-baize-amazon-ai-listing-pipeline and .opencode/skills/sealeap-baize-amazon-ai-listing-pipeline in your project.
What does Sealeap Baize Amazon AI Listing Pipeline need to run?
Going by SKILL.md and its folder, Sealeap Baize Amazon AI Listing Pipeline needs Python for the scripts in its folder. Our summary lists: Python 3.
Does Sealeap Baize Amazon AI Listing Pipeline 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 Baize Amazon AI Listing Pipeline 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 Baize Amazon AI Listing Pipeline use?
Sealeap Baize Amazon AI Listing Pipeline 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 Baize Amazon AI Listing Pipeline use?
About 573 tokens (SKILL.md is roughly 2.3k 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 2k tokens, read only when the agent opens those files.
What are the alternatives to Sealeap Baize Amazon AI Listing Pipeline?
Skills that share tags, products or a category with Sealeap Baize Amazon AI Listing Pipeline: 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 Baize Amazon AI Listing Pipeline?
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.