Amazon Alexa
sickn33/agentic-awesome-skills
Integracao completa com Amazon Alexa para criar skills de voz inteligentes, transformar Alexa em assistente com Claude como cerebro (projeto Auri) e integrar com AWS ecosystem (Lambda, DynamoDB…
通过亚马逊前台的 Alexa 购物助手发起自然语言问答,获取与问题相关的导购回答、推荐商品分组、ASIN 列表,以及可继续追问的问题。每次调用仅支持 1 条 prompt,如需追问须由 agent 总结上下文后拼接新问题发起新请求。可用 url 补充亚马逊页面上下文。当用户提到亚马逊 Alexa、Alexa 购物助手、亚马逊智能助手、AI…
$ npx skills add linkfox-ai/linkfox-skills --skill linkfox-amazon-alexa-search -a claude-codeProject install by default; add -g for ~/.claude/skills/.
$ gh skill install linkfox-ai/linkfox-skills linkfox-amazon-alexa-search --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/linkfox-ai/linkfox-skills.git skills-src && mkdir -p .claude/skills && cp -r skills-src/skills/linkfox-amazon-alexa-search .claude/skills/linkfox-amazon-alexa-search && 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 "linkfox-amazon-alexa-search" agent skill from https://github.com/linkfox-ai/linkfox-skills/tree/main/skills/linkfox-amazon-alexa-search into .claude/skills/linkfox-amazon-alexa-search/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "linkfox-amazon-alexa-search", 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/linkfox-ai/linkfox-skills/tree/main/skills/linkfox-amazon-alexa-searchType 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 linkfox-ai/linkfox-skills --skill linkfox-amazon-alexa-search -a codexProject install goes to .agents/skills/; add -g for ~/.codex/skills/.
$ gh skill install linkfox-ai/linkfox-skills linkfox-amazon-alexa-search --agent codexProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/linkfox-ai/linkfox-skills.git skills-src && mkdir -p .agents/skills && cp -r skills-src/skills/linkfox-amazon-alexa-search .agents/skills/linkfox-amazon-alexa-search && rm -rf skills-srcUse ~/.agents/skills/ instead of .agents/skills for a personal install.
Codex skills documentation · loads skills from .agents/skills/
Install the "linkfox-amazon-alexa-search" agent skill from https://github.com/linkfox-ai/linkfox-skills/tree/main/skills/linkfox-amazon-alexa-search into .agents/skills/linkfox-amazon-alexa-search/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "linkfox-amazon-alexa-search", 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 linkfox-ai/linkfox-skills --skill linkfox-amazon-alexa-search -a cursorProject install goes to .agents/skills/; add -g for ~/.cursor/skills/.
$ gh skill install linkfox-ai/linkfox-skills linkfox-amazon-alexa-search --agent cursorProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/linkfox-ai/linkfox-skills.git skills-src && mkdir -p .cursor/skills && cp -r skills-src/skills/linkfox-amazon-alexa-search .cursor/skills/linkfox-amazon-alexa-search && 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 "linkfox-amazon-alexa-search" agent skill from https://github.com/linkfox-ai/linkfox-skills/tree/main/skills/linkfox-amazon-alexa-search into .cursor/skills/linkfox-amazon-alexa-search/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "linkfox-amazon-alexa-search", 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/linkfox-ai/linkfox-skills.git --path skills/linkfox-amazon-alexa-search--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 linkfox-ai/linkfox-skills --skill linkfox-amazon-alexa-search -a gemini-cliProject install goes to .agents/skills/; add -g for ~/.gemini/skills/.
$ gh skill install linkfox-ai/linkfox-skills linkfox-amazon-alexa-search --agent gemini-cliProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/linkfox-ai/linkfox-skills.git skills-src && mkdir -p .gemini/skills && cp -r skills-src/skills/linkfox-amazon-alexa-search .gemini/skills/linkfox-amazon-alexa-search && 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 "linkfox-amazon-alexa-search" agent skill from https://github.com/linkfox-ai/linkfox-skills/tree/main/skills/linkfox-amazon-alexa-search into .gemini/skills/linkfox-amazon-alexa-search/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "linkfox-amazon-alexa-search", 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 linkfox-ai/linkfox-skills linkfox-amazon-alexa-searchInstalls 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 linkfox-ai/linkfox-skills --skill linkfox-amazon-alexa-search -a github-copilotProject install goes to .agents/skills/; add -g for ~/.copilot/skills/.
$ git clone --depth 1 https://github.com/linkfox-ai/linkfox-skills.git skills-src && mkdir -p .github/skills && cp -r skills-src/skills/linkfox-amazon-alexa-search .github/skills/linkfox-amazon-alexa-search && 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 "linkfox-amazon-alexa-search" agent skill from https://github.com/linkfox-ai/linkfox-skills/tree/main/skills/linkfox-amazon-alexa-search into .github/skills/linkfox-amazon-alexa-search/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "linkfox-amazon-alexa-search", 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 linkfox-ai/linkfox-skills --skill linkfox-amazon-alexa-search -a opencodeOpenCode documents no install command of its own. Project install goes to .agents/skills/; add -g for ~/.config/opencode/skills/.
$ gh skill install linkfox-ai/linkfox-skills linkfox-amazon-alexa-search --agent opencodeProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/linkfox-ai/linkfox-skills.git skills-src && mkdir -p .opencode/skills && cp -r skills-src/skills/linkfox-amazon-alexa-search .opencode/skills/linkfox-amazon-alexa-search && 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 "linkfox-amazon-alexa-search" agent skill from https://github.com/linkfox-ai/linkfox-skills/tree/main/skills/linkfox-amazon-alexa-search into .opencode/skills/linkfox-amazon-alexa-search/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "linkfox-amazon-alexa-search", 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.
linkfox-amazon-alexa-search通过亚马逊前台的 Alexa 购物助手发起自然语言问答,获取与问题相关的导购回答、推荐商品分组、ASIN 列表,以及可继续追问的问题。每次调用仅支持 1 条 prompt,如需追问须由 agent 总结上下文后拼接新问题发起新请求。可用 url 补充亚马逊页面上下文。当用户提到亚马逊 Alexa、Alexa 购物助手、亚马逊智能助手、AI…
Linkfox Amazon Alexa Search is an agent skill from linkfox-ai/linkfox-skills. 通过亚马逊前台的 Alexa 购物助手发起自然语言问答,获取与问题相关的导购回答、推荐商品分组、ASIN 列表,以及可继续追问的问题。每次调用仅支持 1 条 prompt,如需追问须由 agent 总结上下文后拼接新问题发起新请求。可用 url 补充亚马逊页面上下文。当用户提到亚马逊 Alexa、Alexa 购物助手、亚马逊智能助手、AI 导购、对话式选品、自然语言购物、亚马逊聊天问答、Amazon Alexa shopping, conversational shopping, AI shopping assistant, follow-up questions、产品推荐对话、上下文追问等场景时触发此技能。即使用户未明确提及"Alexa",只要其需求是"在亚马逊前台用自然语言问出商品推荐",也应触发此技能。
Its SKILL.md is about 3k 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 `references/api.md`, `references/onboarding.md` and `scripts/amazon_alexa_search.py`).
The licence is MIT.
4 steps, taken from the first numbered list in SKILL.md.
Read from SKILL.md and the folder at commit 38fef04. It shows what the files ask for, not the result of running them.
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.
Ships 2 files in scripts/ (Python), which the agent can run.
Shell commands in SKILL.md call:
pythonFrom the folder's file list and the shell code blocks in SKILL.md.
Hosts in commands or code, which the agent is likely to contact:
amazon.comAlso links to:
skill.linkfox.comFrom URLs in SKILL.md, links to its own repository left out.
Names these keys or tokens, usually read from environment variables:
LINKFOX_AGENT_API_KEYLINKFOXAGENT_API_KEYFrom names ending in _API_KEY, _TOKEN, _SECRET, _KEY or _PASSWORD in SKILL.md.
Linkfox Amazon Alexa Search loads about 3k tokens when it runs, and up to ~5k if it reads all its reference files. Until then it costs about 97 tokens; SKILL.md has 1,373 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.
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.
The full file from linkfox-ai/linkfox-skills at commit 38fef04, republished under its MIT licence (© linkfox-ai). 1,373 words, ~3,001 tokens.
.claude/skills/linkfox-amazon-alexa-search/SKILL.md (or your agent's skills folder). This skill also uses 4 other files; get the full folder from GitHub.This skill drives Amazon's storefront Alexa shopping assistant: pose a natural-language question and get an answer, a curated product list (with ASINs and links), and a set of follow-up questions Alexa is willing to continue with. Each call supports only one prompt. For multi-turn conversations, the agent must summarize prior context and concatenate it with the new question in a fresh call.
prompts is an array but only supports 1 element. Each API call sends exactly one question to Alexa and returns one answer. Do not pass multiple elements.prompts[0] in a new call.url): pass an Amazon page URL only when you want the conversation anchored to a specific page (a category page, search results page, or product detail page). Do not pass a plain marketplace homepage URL like https://www.amazon.com/ — it adds no useful context. Omit url entirely when there is no specific page to anchor on.markdown (default) — a single readable Markdown report containing the question, Alexa's answer, recommended product groups, and follow-up questions.json — a structured array under data, where each entry carries prompt, content, products (grouped recommendations), followUpQuestions, and screenshot.resultsNum is the number of conversation turns Alexa actually answered; if 0, Alexa did not produce a usable reply for the input.
| Parameter | Type | Required | Description | Default |
|---|---|---|---|---|
| prompts | string[] | Yes | Conversation prompts. Only 1 element is allowed per call. To ask follow-up questions, make a new call with context summary + new question as prompts[0]. | - |
| format | string | No | Response format: markdown returns a readable report; json returns a structured array. | markdown |
| url | string | No | Specific Amazon page URL (category, search results, or product detail) to anchor the conversation. Skip when there is no specific page; do not pass a plain homepage URL such as https://www.amazon.com/. | - |
| Field | Type | Description |
|---|---|---|
| stdout | string | Markdown report when format=markdown: per-turn question, Alexa answer, recommended product groups, follow-up questions |
| data | array | Structured turns when format=json. Each item has prompt, content, products[], followUpQuestions[], screenshot |
| resultsNum | integer | Number of answered turns (0 = Alexa did not respond) |
| code / errcode | string / integer | 200 on success; non-200 indicates a business error |
| msg / errmsg | string | ok on success; otherwise an error description |
| costTime | integer | API latency in milliseconds |
| costToken | integer | Tokens consumed (only billed on success) |
| taskId | string | Upstream task identifier for tracing |
| type | string | Render hint: stdoutWorkbenches for markdown, json for json |
data[*] shape (format=json)| Field | Type | Description |
|---|---|---|
| prompt | string | The question or follow-up sent for this turn |
| content | string | Alexa's natural-language answer |
| products[].title | string | Group title (e.g. "Top picks", "Best for running") |
| products[].items[].asin | string | Product ASIN |
| products[].items[].title | string | Product title |
| products[].items[].url | string | Product detail page URL |
| products[].items[].cover | string | Product cover image URL |
| products[].items[].price | string | Current price string (with currency) |
| products[].items[].originalPrice | string | List price / strikethrough price |
| products[].items[].score | string | Star rating |
| products[].items[].ratingsCount | string | Review count |
| products[].items[].describe | string | Short product blurb |
| followUpQuestions | string[] | Questions Alexa offers to continue with |
| screenshot | string | Screenshot URL for this turn |
POST /amazon/alexaSearch(完整参数/响应/错误码见 references/api.md)python scripts/amazon_alexa_search.py '<JSON 参数>' [--inline]输出策略(脚本默认行为):
<cwd>/linkfox/<YYYY-MM-DD>/<session>/data/linkfox-amazon-alexa-search-<timestamp>.json(<cwd> 为脚本执行时的工作目录,在 Claude Code 里即当前项目目录;<session> 取自环境变量 SESSION_ID,按用户任务自动聚合;禁止写入 /tmp,当前目录不可写则报错)total/costToken、最大列表字段的长度 + 前 3 条样本)--inline 强制全量打印到 stdout(同样落盘)读数据建议:先看摘要判断是否足够;需要具体字段时优先用 jq或ConvertFrom-Json 从保存的 json 文件按需抽取,避免整份 JSON 进入上下文。
发生以下异常情况时,采用 references/onboarding.md 引导解决问题:
LINKFOX_AGENT_API_KEY,也未配置 LINKFOXAGENT_API_KEY。prompts[0] — include marketplace cue ("on Amazon US"), use case, and any hard constraints (budget, key feature). Alexa weights the opening question heavily.prompts only accepts 1 element. Do not pass multiple elements.prompts[0] in a new API call. Alexa has no memory of prior calls.url only when there's a specific page — pass a category, search results, or product detail URL when the user is reasoning over that page. Skip url for general questions; do not pass a plain homepage like https://www.amazon.com/.format deliberately — markdown is best for showing the user a polished answer; json is better when downstream code needs to extract ASINs, prices, or follow-up questions programmatically.1. Single-turn shopping question
{
"prompts": ["best wireless earbuds for running on Amazon US under $100"]
}2. Follow-up question (agent summarizes prior context and re-asks)
First call:
{
"prompts": ["best electric kettle on Amazon US"]
}Second call (agent summarizes the previous answer and appends the follow-up):
{
"prompts": ["Previously Alexa recommended: 1) Cosori Electric Kettle (B07T1KY5TZ, $35.99, 4.7★), 2) Mueller Ultra Kettle (B09KC7D3HR, $29.97, 4.5★). Now compare these two on noise level and boil time."]
}3. Question anchored to a category page
{
"prompts": ["What are the most popular picks on this page?"],
"url": "https://www.amazon.com/s?k=electric+kettle"
}4. Structured output for downstream extraction
{
"prompts": ["best gift ideas for a 10-year-old who likes science"],
"format": "json"
}format=markdown: stdout is already structured with turn headings, product cards, and follow-up questions — preserve that structure.title, price, score/ratingsCount, and the product URL.prompts[0] in a new call.resultsNum is 0 or data is empty, tell the user Alexa did not produce a usable reply and suggest rephrasing or anchoring with a url.code / errcode is not 200, surface msg / errmsg and suggest retrying with simpler prompts.prompts only accepts 1 element. For follow-ups, the agent must summarize context + new question into a single prompts[0] and make a new call.Applicable — natural-language conversational shopping on Amazon:
| User Says | Scenario |
|---|---|
| "用 Alexa 帮我推荐...", "亚马逊 Alexa 问下..." | Direct Alexa Q&A |
| "在亚马逊上聊聊给我推荐 ...", "对话式选品" | Conversational discovery |
| "顺便再追问一下 / 接着问 ..." | Follow-up (agent summarizes prior result and re-asks in new call) |
| "在这个页面 / 这个分类下推荐...", "基于这个页面再问一下" | Page-anchored conversation (use url) |
| "best XX for YY under $Z on Amazon" | Goal + constraint + budget Q&A |
| "对比 Alexa 给的前两个推荐" | Compare within Alexa's reply |
| "Alexa 还能继续问什么 / 给我一些追问思路" | Surface follow-up questions |
Not applicable — better routed elsewhere:
Boundary judgment: when the user wants a conversation — "ask Amazon, get a recommendation, then keep asking" — this skill applies. If they want raw search-result rows, structured analytics, or a specific ASIN's data, route to the matching specialized skill instead.
按动态规则计费:消耗算力 = 对话轮次 × 12.6。
重要:本技能的服务按倍数动态计算,可能一次性消耗大量算力,必须提醒用户,由用户决定是否继续。
Feedback:
Auto-detect and report feedback via the Feedback API when any of the following apply:
Call the feedback API as specified in references/api.md. Do not interrupt the user's flow.
For more high-quality, professional cross-border e-commerce skills, set LinkFox Skills.
© linkfox-ai, MIT. Rendered from Markdown: HTML in the file is shown as text, images as links, and headings moved down two levels. Raw file
SKILL.md and 4 other files (scripts, references) in skills/linkfox-amazon-alexa-search of linkfox-ai/linkfox-skills.
Open the folder on GitHubat commit 38fef04
We found 2 copies of this SKILL.md (exact, near-identical or edited) in other folders, from 1 other GitHub owner. This page covers the copy in linkfox-ai/linkfox-skills, which our catalogue first saw on October 7, 2026.
Linkfox Amazon Alexa Search 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 |
|---|---|---|---|---|---|---|
| Linkfox Amazon Alexa Search this skilllinkfox-ai/linkfox-skills | 107 | 1 repos | ~3k | Automated safety check: Pass | MIT | |
| Amazon Alexasickn33/agentic-awesome-skills | 47k | 2 repos | ~359 | Automated safety check: Pass | MIT | |
| Amazon ASIN Lookupbrowser-act/skills | 6.1k | 1 repos | ~1.5k | Automated safety check: Pass | MIT | |
| Amazon Alexa Shopping Q&A Automationbrowser-act/skills | 6.1k | — | ~2.8k | Automated safety check: Pass | MIT | |
| Amazonvellum-ai/vellum-assistant | 1.4k | — | ~1.2k | Automated safety check: Pass | MIT | |
| Amazon Reviews Extractorbrowser-act/skills | 6.1k | 1 repos | ~1.4k | Automated safety check: Pass | MIT |
sickn33/agentic-awesome-skills
Integracao completa com Amazon Alexa para criar skills de voz inteligentes, transformar Alexa em assistente com Claude como cerebro (projeto Auri) e integrar com AWS ecosystem (Lambda, DynamoDB…
browser-act/skills
Fetches structured Amazon product details such as title, price, ratings and availability for a given ASIN through BrowserAct's lookup API template.
browser-act/skills
Submits questions to Amazon's Alexa/Rufus shopping assistant through the browser and collects its answers, optionally within a keyword search context.
vellum-ai/vellum-assistant
Shop on Amazon and Amazon Fresh through your browser. An agent skill from vellum-ai/vellum-assistant.
browser-act/skills
Pulls structured Amazon product reviews for an ASIN through BrowserAct's Amazon Reviews API, with no Amazon login, using a bundled Python script.
ComposioHQ/awesome-claude-skills
Automate Asin Data API tasks via Rube MCP (Composio). An agent skill from ComposioHQ/awesome-claude-skills.
linkfox-ai/linkfox-skills
1688平台以图搜图,通过商品图片精准检索外观相似或同款的1688货源,返回标题、价格、起批量、月销量、复购率、交易评分等核心数据。当用户提到1688以图搜图、1688找货源、以图找同款、跨境找工厂、1688识图、图片找货源、找相似货源、image search 1688、find supplier by…
linkfox-ai/linkfox-skills
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linkfox-ai/linkfox-skills
亚马逊反向选品:基于历史商业洞察报告沉淀的指标数据池,按 30+ 项商业维度(市场规模与增长、价格区间与档位份额、竞争密度与头部集中度、人群画像如年龄/性别/收入、评论卖点与痛点等)反向筛选亚马逊赛道与关键词。当用户提到反向选品、指标筛选、细分市场反查、蓝海赛道挖掘、低竞争赛道、新人友好赛道、品牌分散市场、痛点切入、卖点反查、定价档位机会、人群画像选品、Amazon niche reverse…
linkfox-ai/linkfox-skills
通过ASIN获取亚马逊商品详细信息,包括标题、图片、五点描述、规格参数、A+页面、价格、评分评论、变体等;可在取得原始HTML时尝试提取Item Highlights(商品亮点)。当用户提到亚马逊商品详情、ASIN查询、商品页面数据、Listing分析、五点描述提取、Item…
linkfox-ai/linkfox-skills
按ASIN获取并分析亚马逊商品评论,支持15个站点(含美国站),按星级筛选评论。当用户提到亚马逊评论、美国站评论、商品评价、买家投诉、差评、好评、星级评分、评论分析、评论情感、产品改良建议、Vine评论、已验证购买评论、竞品评论研究、Amazon reviews, US reviews, Amazon.com reviews, product feedback, negative review…
linkfox-ai/linkfox-skills
模拟真实用户在亚马逊前台搜索,获取实时关键词排名和搜索结果页数据。当用户提到亚马逊商品搜索、搜索结果抓取、关键词在搜索页的排名、ASIN排名位置查询、竞品发现、搜索页价格对比、广告商品分析、新品监控、前台搜索模拟、Amazon search, keyword ranking, search results, ASIN ranking position, competitor…
通过亚马逊前台的 Alexa 购物助手发起自然语言问答,获取与问题相关的导购回答、推荐商品分组、ASIN 列表,以及可继续追问的问题。每次调用仅支持 1 条 prompt,如需追问须由 agent 总结上下文后拼接新问题发起新请求。可用 url 补充亚马逊页面上下文。当用户提到亚马逊 Alexa、Alexa 购物助手、亚马逊智能助手、AI…. Linkfox Amazon Alexa Search is an agent skill from linkfox-ai/linkfox-skills.
Run `npx skills add linkfox-ai/linkfox-skills --skill linkfox-amazon-alexa-search -a claude-code`. Or copy the skill folder (skills/linkfox-amazon-alexa-search in linkfox-ai/linkfox-skills) into .claude/skills/linkfox-amazon-alexa-search in your project. Claude Code loads it when a task matches its description.
Run `npx skills add linkfox-ai/linkfox-skills --skill linkfox-amazon-alexa-search -a codex`. Or copy the skill folder (skills/linkfox-amazon-alexa-search in linkfox-ai/linkfox-skills) into .agents/skills/linkfox-amazon-alexa-search in your project. Codex loads it when a task matches its description.
Cursor, Gemini CLI, GitHub Copilot and OpenCode also load SKILL.md folders. With the skills CLI, run `npx skills add linkfox-ai/linkfox-skills --skill linkfox-amazon-alexa-search -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/linkfox-amazon-alexa-search, .gemini/skills/linkfox-amazon-alexa-search, .github/skills/linkfox-amazon-alexa-search and .opencode/skills/linkfox-amazon-alexa-search in your project.
Going by SKILL.md and its folder, Linkfox Amazon Alexa Search needs Python for the scripts in its folder, the command-line tools its instructions call (python) and credentials named LINKFOX_AGENT_API_KEY and LINKFOXAGENT_API_KEY. Our summary lists: Python 3; A credential in LINKFOX_AGENT_API_KEY; A credential in LINKFOXAGENT_API_KEY.
SKILL.md names 2 domains. In commands or code: amazon.com; the agent is likely to contact it when it follows the instructions. As links in the text: skill.linkfox.com. This is read from the text; nothing was executed.
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.
Linkfox Amazon Alexa Search is published under the MIT licence (the repository's licence). It allows redistribution, so the full SKILL.md is shown on this page.
About 3k tokens (SKILL.md is roughly 12k 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.
Skills that share tags, products or a category with Linkfox Amazon Alexa Search: Amazon Alexa (sickn33/agentic-awesome-skills, 47k stars), Amazon ASIN Lookup (browser-act/skills, 6.1k stars), Amazon Alexa Shopping Q&A Automation (browser-act/skills, 6.1k stars) and Amazon (vellum-ai/vellum-assistant, 1.4k stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.
linkfox-ai (a GitHub user) maintains it in linkfox-ai/linkfox-skills, which has 107 GitHub stars. The repository holds 177 skills in this directory. The repository was last updated on September 14, 2026.
Source: linkfox-ai/linkfox-skills on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.