Agent skill

Linkfox Amazon Alexa Search

by linkfox-ai in 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…

MITAuto-check passed

Install Linkfox Amazon Alexa Search

skills CLI
$ npx skills add linkfox-ai/linkfox-skills --skill linkfox-amazon-alexa-search -a claude-code

Project install by default; add -g for ~/.claude/skills/.

GitHub CLI
$ gh skill install linkfox-ai/linkfox-skills linkfox-amazon-alexa-search --agent claude-code

Project scope by default; add --scope user for a personal install. Needs GitHub CLI 2.90.0 or later (public preview).

Manual copy
$ 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-src

Use ~/.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/

Facts

Skill name
linkfox-amazon-alexa-search
GitHub stars
107
Used in
1 other repo
Token cost
~3k tokens
SKILL.md length
1,373 words
Files
5 (incl. scripts, references)
Skills in repo
177
Repo updated
First seen
Licence
MIT

At a glance

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…

  • Works in 4 steps: Single-turn per call: prompts is an… → Cross-call context is not preserved:… → Optional page context (url): pass an… → …
  • SKILL.md covers Core Concepts, Parameters, Response Fields and 调用方式, plus 6 more sections
  • Runs Python scripts from its folder; calls python; reaches amazon.com; needs LINKFOX_AGENT_API_KEY and LINKFOXAGENT_API_KEY

What it does

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.

Example prompts

  • “,只要其需求是”
  • “/linkfox-amazon-alexa-search”

Requirements

  • Python 3
  • A credential in LINKFOX_AGENT_API_KEY
  • A credential in LINKFOXAGENT_API_KEY

Workflow steps

4 steps, taken from the first numbered list in SKILL.md.

  1. Single-turn per call: prompts is an array but only supports 1 element. Each API call sends exactly one question to Alexa and returns one…
  2. Cross-call context is not preserved: every call starts a brand-new Alexa session. To ask follow-up questions, the agent must summarize the…
  3. Optional page context (url): pass an Amazon page URL only when you want the conversation anchored to a specific page (a category page…
  4. Two output formats

What it can do on your machine

Read from SKILL.md and the folder at commit 38fef04. 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 2 files in scripts/ (Python), which the agent can run.

    Shell commands in SKILL.md call:

    • python

    From the folder's file list and the shell code blocks in SKILL.md.

  • Network

    Hosts in commands or code, which the agent is likely to contact:

    • amazon.com

    Also links to:

    • skill.linkfox.com

    From URLs in SKILL.md, links to its own repository left out.

  • Credentials

    Names these keys or tokens, usually read from environment variables:

    • LINKFOX_AGENT_API_KEY
    • LINKFOXAGENT_API_KEY

    From names ending in _API_KEY, _TOKEN, _SECRET, _KEY or _PASSWORD in SKILL.md.

Context cost

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.

Always · name and description, kept in context so the agent knows when to use it
~97
When it runs · the whole SKILL.md, loaded when a task matches
~3k
With references · SKILL.md plus every file in references/, read only if the agent opens them
~5k

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 linkfox-ai/linkfox-skills at commit 38fef04, republished under its MIT licence (© linkfox-ai). 1,373 words, ~3,001 tokens.

Download SKILL.mdSave it as .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.
name
linkfox-amazon-alexa-search
description
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。

Amazon Alexa Shopping Assistant

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.

Core Concepts

  1. Single-turn per 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.
  2. Cross-call context is not preserved: every call starts a brand-new Alexa session. To ask follow-up questions, the agent must summarize the previous answer (key recommendations, ASINs, relevant context) and concatenate it with the new question as prompts[0] in a new call.
  3. Optional page context (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.
  4. Two output formats:
    • 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.

Parameters

ParameterTypeRequiredDescriptionDefault
promptsstring[]YesConversation 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].-
formatstringNoResponse format: markdown returns a readable report; json returns a structured array.markdown
urlstringNoSpecific 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/.-

Response Fields

FieldTypeDescription
stdoutstringMarkdown report when format=markdown: per-turn question, Alexa answer, recommended product groups, follow-up questions
dataarrayStructured turns when format=json. Each item has prompt, content, products[], followUpQuestions[], screenshot
resultsNumintegerNumber of answered turns (0 = Alexa did not respond)
code / errcodestring / integer200 on success; non-200 indicates a business error
msg / errmsgstringok on success; otherwise an error description
costTimeintegerAPI latency in milliseconds
costTokenintegerTokens consumed (only billed on success)
taskIdstringUpstream task identifier for tracing
typestringRender hint: stdoutWorkbenches for markdown, json for json
Structured data[*] shape (format=json)
FieldTypeDescription
promptstringThe question or follow-up sent for this turn
contentstringAlexa's natural-language answer
products[].titlestringGroup title (e.g. "Top picks", "Best for running")
products[].items[].asinstringProduct ASIN
products[].items[].titlestringProduct title
products[].items[].urlstringProduct detail page URL
products[].items[].coverstringProduct cover image URL
products[].items[].pricestringCurrent price string (with currency)
products[].items[].originalPricestringList price / strikethrough price
products[].items[].scorestringStar rating
products[].items[].ratingsCountstringReview count
products[].items[].describestringShort product blurb
followUpQuestionsstring[]Questions Alexa offers to continue with
screenshotstringScreenshot URL for this turn

调用方式

  • API 端点:POST /amazon/alexaSearch(完整参数/响应/错误码见 references/api.md)
  • Python 脚本:python scripts/amazon_alexa_search.py '<JSON 参数>' [--inline]
  • 成本约束:本工具会消耗算力;同一会话同一参数组合默认只调用一次,脚本带 24h 本地缓存。失败/空结果不得自动换关键词、翻页或改邮编连续试探;需要继续检索时先向用户说明会产生额外消耗。

输出策略(脚本默认行为):

  • 始终将完整响应写入 <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)
  • 响应体 ≤ 8 KB:落盘后把完整 JSON 打印到 stdout
  • 响应体 > 8 KB:落盘后 stdout 只输出摘要(顶层字段、常见计数如 total/costToken、最大列表字段的长度 + 前 3 条样本)
  • 加 --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。

解决认证和算力问题

发生以下异常情况时,采用 references/onboarding.md 引导解决问题:

异常情况
  • 未配置API Key:环境变量未配置 LINKFOX_AGENT_API_KEY,也未配置 LINKFOXAGENT_API_KEY。
  • 响应401或402状态码
  • 响应提示算力或余额不足:消息含"算力余额不足/计费不足/余额不足/quota exceeded/insufficient balance/套餐到期/需充值/请充值",或类似含义的内容。

How to Build Queries

  1. Front-load the user's intent in prompts[0] — include marketplace cue ("on Amazon US"), use case, and any hard constraints (budget, key feature). Alexa weights the opening question heavily.
  2. One question per call — prompts only accepts 1 element. Do not pass multiple elements.
  3. For follow-ups, summarize and re-ask — when the user wants to continue the conversation, the agent must: (a) summarize the key points from the previous Alexa response (answer highlights, recommended ASINs, relevant context); (b) concatenate the summary with the new question; (c) send as prompts[0] in a new API call. Alexa has no memory of prior calls.
  4. Anchor with 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/.
  5. Pick 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.
Usage Examples

1. Single-turn shopping question

json
{
  "prompts": ["best wireless earbuds for running on Amazon US under $100"]
}

2. Follow-up question (agent summarizes prior context and re-asks)

First call:

json
{
  "prompts": ["best electric kettle on Amazon US"]
}

Second call (agent summarizes the previous answer and appends the follow-up):

json
{
  "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

json
{
  "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

json
{
  "prompts": ["best gift ideas for a 10-year-old who likes science"],
  "format": "json"
}
Show full SKILL.md (561 more words)Show less

Display Rules

  1. Render the Markdown directly when format=markdown: stdout is already structured with turn headings, product cards, and follow-up questions — preserve that structure.
  2. Surface the recommended ASINs so the user can click through; show title, price, score/ratingsCount, and the product URL.
  3. Show the follow-up questions Alexa returned — they are usable prompts the user can pick to continue digging. When the user picks one, summarize the current answer and use the selected follow-up as prompts[0] in a new call.
  4. Don't reroute to a data-analysis sandbox: the answer body is conversational and the recommended products are nested groups, not a flat tabular dataset suitable for SQL-like aggregation.
  5. Flag empty results: if 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.
  6. Indicate freshness: results reflect Alexa's live answer at call time; mention this when the user asks about timing.
  7. Handle business errors: if code / errcode is not 200, surface msg / errmsg and suggest retrying with simpler prompts.

Important Limitations

  • Alexa-driven, not deterministic: same prompts can yield different answers across calls — Alexa's response varies with time, traffic, and context.
  • No cross-call memory: each tool call is a fresh Alexa session; the agent must summarize prior context and embed it in the new question.
  • One prompt per call: 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.
  • Marketplace coverage: anchored on Amazon's storefront Alexa experience (primarily amazon.com); availability on non-US marketplaces depends on Alexa rollout.
  • Output mix: primary value is the conversational answer plus a curated handful of products; this is not a substitute for SERP-wide product extraction.

User Expression & Scenario Quick Reference

Applicable — natural-language conversational shopping on Amazon:

User SaysScenario
"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:

  • Pulling the full SERP for a keyword with positions, sponsored flags, etc. (use the storefront search-simulation skill).
  • Historical search-term analytics or volume trends (use the ABA data explorer).
  • Detailed product detail / A+ / bullets for a known ASIN (use the Amazon product detail skill).
  • Review-level sentiment analysis (use the Amazon reviews skill).
  • Image-based similar product discovery (use the image search skill).
  • Aggregated statistics over a flat product list (no structured table here).

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.

算力消耗规则

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:

  1. The functionality or purpose described in this skill does not match actual behavior
  2. The skill's results do not match the user's intent
  3. The user expresses dissatisfaction or praise about this skill
  4. Anything you believe could be improved

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

Files

SKILL.md and 4 other files (scripts, references) in skills/linkfox-amazon-alexa-search of linkfox-ai/linkfox-skills.

  • SKILL.md
  • references/api.md
  • references/onboarding.md
  • scripts/amazon_alexa_search.py
  • scripts/onboarding.py

Open the folder on GitHubat commit 38fef04

Used in 1 other repository

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.

Compare with similar skills

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.

Linkfox Amazon Alexa Search compared with similar skills
SkillStarsUsed inTokensAuto-checkLicenceRepo updated
Linkfox Amazon Alexa Search this skilllinkfox-ai/linkfox-skills1071 repos~3kAutomated safety check: PassMIT
Amazon Alexasickn33/agentic-awesome-skills47k2 repos~359Automated safety check: PassMIT
Amazon ASIN Lookupbrowser-act/skills6.1k1 repos~1.5kAutomated safety check: PassMIT
Amazon Alexa Shopping Q&A Automationbrowser-act/skills6.1k—~2.8kAutomated safety check: PassMIT
Amazonvellum-ai/vellum-assistant1.4k—~1.2kAutomated safety check: PassMIT
Amazon Reviews Extractorbrowser-act/skills6.1k1 repos~1.4kAutomated safety check: PassMIT

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  • Linkfox Amazon Search

    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…

    107 GitHub starsUsed in 1 repo~2.4k tokens
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Questions about Linkfox Amazon Alexa Search

What does Linkfox Amazon Alexa Search do?

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.

How do I install Linkfox Amazon Alexa Search in Claude Code?

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.

How do I install Linkfox Amazon Alexa Search in Codex?

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.

Can I use Linkfox Amazon Alexa Search 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 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.

What does Linkfox Amazon Alexa Search need to run?

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.

Does Linkfox Amazon Alexa Search access the network?

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.

Is Linkfox Amazon Alexa Search 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 Linkfox Amazon Alexa Search use?

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.

How many tokens does Linkfox Amazon Alexa Search use?

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.

What are the alternatives to Linkfox Amazon Alexa Search?

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.

Who maintains Linkfox Amazon Alexa Search?

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.