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 Seasonal Blue Ocean Screening
Screen Amazon product ideas for low-review seasonal niches with clear query intent, manageable competition, entry timing, and paid-traffic economics.
MITAuto-check passed
Install Sealeap Xiezhi Amazon Seasonal Blue Ocean Screening
$ npx skills add xjli360/sealeap-amazon-skills --skill sealeap-xiezhi-amazon-seasonal-blue-ocean-screening -a claude-codeProject install by default; add -g for ~/.claude/skills/.
$ gh skill install xjli360/sealeap-amazon-skills sealeap-xiezhi-amazon-seasonal-blue-ocean-screening --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-seasonal-blue-ocean-screening .claude/skills/sealeap-xiezhi-amazon-seasonal-blue-ocean-screening && 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-seasonal-blue-ocean-screening" agent skill from https://github.com/xjli360/sealeap-amazon-skills/tree/main/amazon-skills/douyin/xiezhi/sealeap-xiezhi-amazon-seasonal-blue-ocean-screening into .claude/skills/sealeap-xiezhi-amazon-seasonal-blue-ocean-screening/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "sealeap-xiezhi-amazon-seasonal-blue-ocean-screening", 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-seasonal-blue-ocean-screeningType 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-seasonal-blue-ocean-screening -a codexProject install goes to .agents/skills/; add -g for ~/.codex/skills/.
$ gh skill install xjli360/sealeap-amazon-skills sealeap-xiezhi-amazon-seasonal-blue-ocean-screening --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-seasonal-blue-ocean-screening .agents/skills/sealeap-xiezhi-amazon-seasonal-blue-ocean-screening && 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-seasonal-blue-ocean-screening" agent skill from https://github.com/xjli360/sealeap-amazon-skills/tree/main/amazon-skills/douyin/xiezhi/sealeap-xiezhi-amazon-seasonal-blue-ocean-screening into .agents/skills/sealeap-xiezhi-amazon-seasonal-blue-ocean-screening/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "sealeap-xiezhi-amazon-seasonal-blue-ocean-screening", 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-seasonal-blue-ocean-screening -a cursorProject install goes to .agents/skills/; add -g for ~/.cursor/skills/.
$ gh skill install xjli360/sealeap-amazon-skills sealeap-xiezhi-amazon-seasonal-blue-ocean-screening --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-seasonal-blue-ocean-screening .cursor/skills/sealeap-xiezhi-amazon-seasonal-blue-ocean-screening && 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-seasonal-blue-ocean-screening" agent skill from https://github.com/xjli360/sealeap-amazon-skills/tree/main/amazon-skills/douyin/xiezhi/sealeap-xiezhi-amazon-seasonal-blue-ocean-screening into .cursor/skills/sealeap-xiezhi-amazon-seasonal-blue-ocean-screening/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "sealeap-xiezhi-amazon-seasonal-blue-ocean-screening", 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-seasonal-blue-ocean-screening--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-seasonal-blue-ocean-screening -a gemini-cliProject install goes to .agents/skills/; add -g for ~/.gemini/skills/.
$ gh skill install xjli360/sealeap-amazon-skills sealeap-xiezhi-amazon-seasonal-blue-ocean-screening --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-seasonal-blue-ocean-screening .gemini/skills/sealeap-xiezhi-amazon-seasonal-blue-ocean-screening && 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-seasonal-blue-ocean-screening" agent skill from https://github.com/xjli360/sealeap-amazon-skills/tree/main/amazon-skills/douyin/xiezhi/sealeap-xiezhi-amazon-seasonal-blue-ocean-screening into .gemini/skills/sealeap-xiezhi-amazon-seasonal-blue-ocean-screening/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "sealeap-xiezhi-amazon-seasonal-blue-ocean-screening", 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-seasonal-blue-ocean-screeningInstalls 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-seasonal-blue-ocean-screening -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-seasonal-blue-ocean-screening .github/skills/sealeap-xiezhi-amazon-seasonal-blue-ocean-screening && 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-seasonal-blue-ocean-screening" agent skill from https://github.com/xjli360/sealeap-amazon-skills/tree/main/amazon-skills/douyin/xiezhi/sealeap-xiezhi-amazon-seasonal-blue-ocean-screening into .github/skills/sealeap-xiezhi-amazon-seasonal-blue-ocean-screening/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "sealeap-xiezhi-amazon-seasonal-blue-ocean-screening", 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-seasonal-blue-ocean-screening -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-seasonal-blue-ocean-screening --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-seasonal-blue-ocean-screening .opencode/skills/sealeap-xiezhi-amazon-seasonal-blue-ocean-screening && 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-seasonal-blue-ocean-screening" agent skill from https://github.com/xjli360/sealeap-amazon-skills/tree/main/amazon-skills/douyin/xiezhi/sealeap-xiezhi-amazon-seasonal-blue-ocean-screening into .opencode/skills/sealeap-xiezhi-amazon-seasonal-blue-ocean-screening/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "sealeap-xiezhi-amazon-seasonal-blue-ocean-screening", 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-seasonal-blue-ocean-screening- GitHub stars
- 251
- Token cost
- ~545 tokens
- SKILL.md length
- 92 words
- Files
- 5 (incl. scripts, references)
- Skills in repo
- 179
- Repo updated
- First seen
- Licence
- MIT
At a glance
Screen Amazon product ideas for low-review seasonal niches with clear query intent, manageable competition, entry timing, and paid-traffic economics.
- Works in 5 steps: 倒排窗口 → 分层初筛 → 验证精准需求 → …
- A user needs a fast first-pass candidate list without treating filter thresholds as a final launch decision
- 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 Seasonal Blue Ocean Screening is an agent skill from xjli360/sealeap-amazon-skills. Screen Amazon product ideas for low-review seasonal niches with clear query intent, manageable competition, entry timing, and paid-traffic economics. Use when a user needs a fast first-pass candidate list without treating filter thresholds as a final launch decision.
Its SKILL.md is about 550 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
- A user needs a fast first-pass candidate list without treating filter thresholds as a final launch decision
Example prompts
- “/sealeap-xiezhi-amazon-seasonal-blue-ocean-screening”
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 Seasonal Blue Ocean Screening loads about 545 tokens when it runs, and up to ~2.9k if it reads all its reference files. Until then it costs about 80 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, ~545 tokens.
Download SKILL.mdSave it as
.claude/skills/sealeap-xiezhi-amazon-seasonal-blue-ocean-screening/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-seasonal-blue-ocean-screening
- description
- Screen Amazon product ideas for low-review seasonal niches with clear query intent, manageable competition, entry timing, and paid-traffic economics. Use when a user needs a fast first-pass candidate list without treating filter thresholds as a final launch decision.
Amazon 季节性冷门机会筛选
目标
从历史月份和未来进场窗口中找出有明确需求、直接竞品较少且能继续验证的候选细分市场。
适用任务
- 按未来旺季倒排选品、生产、运输和上架时间。
- 从大量商品中初筛低评论、适中销量和较高客单价机会。
- 判断一个候选是可研究的细分市场，还是偶发销量或不可复制样本。
开始前要拿到
- 目标站点、计划上架日期、供应链交期与物流时效。
- 价格下限、毛利底线、首批库存上限和可承受广告成本。
- 历史月份的销量、评论、价格、变体和上架时间代理数据。
- 候选产品的精准词、直接竞品与需求场景。
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。
- 不得把筛选结果直接当作可采购产品。
- 不得复制竞品设计；进入采购前必须完成知识产权、产品安全和平台政策核查。
工作流
1. 倒排窗口
从预期需求高峰向前倒排，至少为上架、入仓、评价与广告学习预留缓冲；先排除已经错过窗口的方向。
2. 分层初筛
用评论、销量、价格和历史月份做宽松筛选，并同时保留多组阈值做敏感性分析，避免单一参数制造假蓝海。
3. 验证精准需求
确认至少存在能描述产品属性、对象或场景的精准搜索词，并据此建立真正的直接竞品集合。
4. 检查可复制性
排查异常评论、极端促销、外部爆量、合并变体和短期事件；解释销量来源后再保留候选。
5. 形成候选卡
记录需求驱动、竞争强度、预计 CPC、保守 CVR、单位经济、进场时间和下一步差异化验证。
判断标准
- 评论上限 30/100/200、销量上限 500 等仅是探索分层，不是平台规则或通用答案。
- 优先验证未来三到五个月可能进入高峰的需求，但实际提前量必须由交期和站点时效倒推。
- 低评论且稳定出单只是线索；必须排除异常运营和不可持续流量。
- 候选在纯付费流量的保守情景下至少应接近盈亏平衡，否则标记 HOLD。
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
- 候选细分市场清单
- 直接竞品与精准词表
- 进场时间倒排表
- 单位经济与风险卡
- 继续研究或淘汰结论
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-seasonal-blue-ocean-screening 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 Seasonal Blue Ocean Screening 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 Seasonal Blue Ocean Screening this skillxjli360/sealeap-amazon-skills | 251 | — | ~545 | 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 Xiezhi Amazon Seasonal Blue Ocean Screening
What does Sealeap Xiezhi Amazon Seasonal Blue Ocean Screening do?
Screen Amazon product ideas for low-review seasonal niches with clear query intent, manageable competition, entry timing, and paid-traffic economics. Sealeap Xiezhi Amazon Seasonal Blue Ocean Screening is an agent skill from xjli360/sealeap-amazon-skills. Screen Amazon product ideas for low-review seasonal niches with clear query intent, manageable competition, entry timing, and paid-traffic economics.
When should I use Sealeap Xiezhi Amazon Seasonal Blue Ocean Screening?
Sealeap Xiezhi Amazon Seasonal Blue Ocean Screening fits situations like: A user needs a fast first-pass candidate list without treating filter thresholds as a final launch decision.
How do I install Sealeap Xiezhi Amazon Seasonal Blue Ocean Screening in Claude Code?
Run `npx skills add xjli360/sealeap-amazon-skills --skill sealeap-xiezhi-amazon-seasonal-blue-ocean-screening -a claude-code`. Or copy the skill folder (amazon-skills/douyin/xiezhi/sealeap-xiezhi-amazon-seasonal-blue-ocean-screening in xjli360/sealeap-amazon-skills) into .claude/skills/sealeap-xiezhi-amazon-seasonal-blue-ocean-screening in your project. Claude Code loads it when a task matches its description.
How do I install Sealeap Xiezhi Amazon Seasonal Blue Ocean Screening in Codex?
Run `npx skills add xjli360/sealeap-amazon-skills --skill sealeap-xiezhi-amazon-seasonal-blue-ocean-screening -a codex`. Or copy the skill folder (amazon-skills/douyin/xiezhi/sealeap-xiezhi-amazon-seasonal-blue-ocean-screening in xjli360/sealeap-amazon-skills) into .agents/skills/sealeap-xiezhi-amazon-seasonal-blue-ocean-screening in your project. Codex loads it when a task matches its description.
Can I use Sealeap Xiezhi Amazon Seasonal Blue Ocean Screening 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-seasonal-blue-ocean-screening -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-seasonal-blue-ocean-screening, .gemini/skills/sealeap-xiezhi-amazon-seasonal-blue-ocean-screening, .github/skills/sealeap-xiezhi-amazon-seasonal-blue-ocean-screening and .opencode/skills/sealeap-xiezhi-amazon-seasonal-blue-ocean-screening in your project.
What does Sealeap Xiezhi Amazon Seasonal Blue Ocean Screening need to run?
Going by SKILL.md and its folder, Sealeap Xiezhi Amazon Seasonal Blue Ocean Screening needs Python for the scripts in its folder. Our summary lists: Python 3.
Does Sealeap Xiezhi Amazon Seasonal Blue Ocean Screening 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 Seasonal Blue Ocean Screening 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 Seasonal Blue Ocean Screening use?
Sealeap Xiezhi Amazon Seasonal Blue Ocean Screening 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 Seasonal Blue Ocean Screening use?
About 545 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 2.4k tokens, read only when the agent opens those files.
What are the alternatives to Sealeap Xiezhi Amazon Seasonal Blue Ocean Screening?
Skills that share tags, products or a category with Sealeap Xiezhi Amazon Seasonal Blue Ocean Screening: 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 Seasonal Blue Ocean Screening?
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.