SEO Content Brief Generator
AgriciDaniel/claude-seo
Builds research-backed SEO content briefs with competitor scoring, per-section word counts and page-type templates, for new pages or improving existing ones.
基于Sorftime数据的亚马逊多维度产品搜索与筛选，涵盖14个站点，支持历史月份快照回看。当用户提到Sorftime产品搜索、亚马逊产品筛选、竞品调研、类目分析、品牌热销、卖家分析、季节性产品、历史快照回看、产品搜索、月销量月销额、ABA关键词找产品、价格范围筛选、新品发现、多条件组合筛选、product search, competitor research, category…
Install Linkfox Sorftime Amazon Product Query
$ npx skills add linkfox-ai/linkfox-skills --skill linkfox-sorftime-amazon-product-query -a claude-codeProject install by default; add -g for ~/.claude/skills/.
$ gh skill install linkfox-ai/linkfox-skills linkfox-sorftime-amazon-product-query --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-sorftime-amazon-product-query .claude/skills/linkfox-sorftime-amazon-product-query && 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-sorftime-amazon-product-query" agent skill from https://github.com/linkfox-ai/linkfox-skills/tree/main/skills/linkfox-sorftime-amazon-product-query into .claude/skills/linkfox-sorftime-amazon-product-query/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "linkfox-sorftime-amazon-product-query", 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-sorftime-amazon-product-queryType 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-sorftime-amazon-product-query -a codexProject install goes to .agents/skills/; add -g for ~/.codex/skills/.
$ gh skill install linkfox-ai/linkfox-skills linkfox-sorftime-amazon-product-query --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-sorftime-amazon-product-query .agents/skills/linkfox-sorftime-amazon-product-query && 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-sorftime-amazon-product-query" agent skill from https://github.com/linkfox-ai/linkfox-skills/tree/main/skills/linkfox-sorftime-amazon-product-query into .agents/skills/linkfox-sorftime-amazon-product-query/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "linkfox-sorftime-amazon-product-query", 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-sorftime-amazon-product-query -a cursorProject install goes to .agents/skills/; add -g for ~/.cursor/skills/.
$ gh skill install linkfox-ai/linkfox-skills linkfox-sorftime-amazon-product-query --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-sorftime-amazon-product-query .cursor/skills/linkfox-sorftime-amazon-product-query && 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-sorftime-amazon-product-query" agent skill from https://github.com/linkfox-ai/linkfox-skills/tree/main/skills/linkfox-sorftime-amazon-product-query into .cursor/skills/linkfox-sorftime-amazon-product-query/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "linkfox-sorftime-amazon-product-query", 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-sorftime-amazon-product-query--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-sorftime-amazon-product-query -a gemini-cliProject install goes to .agents/skills/; add -g for ~/.gemini/skills/.
$ gh skill install linkfox-ai/linkfox-skills linkfox-sorftime-amazon-product-query --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-sorftime-amazon-product-query .gemini/skills/linkfox-sorftime-amazon-product-query && 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-sorftime-amazon-product-query" agent skill from https://github.com/linkfox-ai/linkfox-skills/tree/main/skills/linkfox-sorftime-amazon-product-query into .gemini/skills/linkfox-sorftime-amazon-product-query/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "linkfox-sorftime-amazon-product-query", 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-sorftime-amazon-product-queryInstalls 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-sorftime-amazon-product-query -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-sorftime-amazon-product-query .github/skills/linkfox-sorftime-amazon-product-query && 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-sorftime-amazon-product-query" agent skill from https://github.com/linkfox-ai/linkfox-skills/tree/main/skills/linkfox-sorftime-amazon-product-query into .github/skills/linkfox-sorftime-amazon-product-query/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "linkfox-sorftime-amazon-product-query", 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-sorftime-amazon-product-query -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-sorftime-amazon-product-query --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-sorftime-amazon-product-query .opencode/skills/linkfox-sorftime-amazon-product-query && 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-sorftime-amazon-product-query" agent skill from https://github.com/linkfox-ai/linkfox-skills/tree/main/skills/linkfox-sorftime-amazon-product-query into .opencode/skills/linkfox-sorftime-amazon-product-query/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "linkfox-sorftime-amazon-product-query", 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
linkfox-sorftime-amazon-product-query- GitHub stars
- 107
- Token cost
- ~2.6k tokens
- SKILL.md length
- 1,092 words
- Files
- 5 (incl. scripts, references)
- Skills in repo
- 177
- Repo updated
- First seen
- Licence
- MIT
At a glance
基于Sorftime数据的亚马逊多维度产品搜索与筛选，涵盖14个站点，支持历史月份快照回看。当用户提到Sorftime产品搜索、亚马逊产品筛选、竞品调研、类目分析、品牌热销、卖家分析、季节性产品、历史快照回看、产品搜索、月销量月销额、ABA关键词找产品、价格范围筛选、新品发现、多条件组合筛选、product search, competitor research, category…
- Works in 6 steps: Always specify the marketplace: Use… → Choose the right query mode: Use… → Match queryType with queryValue format:… → …
- Tasks that involve Competitor analysis
- SKILL.md covers Core Concepts, Data Fields, Supported Marketplaces and 调用方式, plus 6 more sections
- Runs Python scripts from its folder; calls python; needs LINKFOX_AGENT_API_KEY and LINKFOXAGENT_API_KEY
What it does
Linkfox Sorftime Amazon Product Query is an agent skill from linkfox-ai/linkfox-skills. 基于Sorftime数据的亚马逊多维度产品搜索与筛选，涵盖14个站点，支持历史月份快照回看。当用户提到Sorftime产品搜索、亚马逊产品筛选、竞品调研、类目分析、品牌热销、卖家分析、季节性产品、历史快照回看、产品搜索、月销量月销额、ABA关键词找产品、价格范围筛选、新品发现、多条件组合筛选、product search, competitor research, category analysis, brand bestsellers, seller analysis, seasonal products, historical snapshot时触发此技能。即使用户未明确提及"Sorftime"，只要其需求涉及亚马逊产品搜索、筛选、对比或类目/品牌/卖家维度的产品探索，也应触发此技能。
Its SKILL.md is about 2.6k 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/onboarding.py`).
It sits in Marketing & SEO, covering Competitor analysis. The licence is MIT.
When your agent uses it
- Tasks that involve Competitor analysis
Example prompts
- “Sorftime”
- “/linkfox-sorftime-amazon-product-query”
Requirements
- Python 3
- A credential in LINKFOX_AGENT_API_KEY
- A credential in LINKFOXAGENT_API_KEY
Workflow steps
6 steps, taken from the first numbered list in SKILL.md.
- Always specify the marketplace: Use lowercase site codes, e.g., us, de, jp
- Choose the right query mode: Use queryMode=1 for a single filter; use queryMode=2 to combine multiple filters with AND logic
- Match queryType with queryValue format: Each queryType expects a specific format - see the table below. Mismatched formats will cause errors
- Mind price units: Price filters (queryType=8) use smcurrency unit (cents for USD), so $19.99 = 1999
- Use open ranges when appropriate: Omit one end for open range - ,1000 means "up to 1000"; 100, means "100 or more"
- Use queryMonth for historical comparison: Format yyyy-MM; compare with a second call without queryMonth to see changes over time
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
Links to these hosts (documentation or services it may open):
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_KEYLINKFOXAGENT_API_KEY
From names ending in _API_KEY, _TOKEN, _SECRET, _KEY or _PASSWORD in SKILL.md.
Context cost
Linkfox Sorftime Amazon Product Query loads about 2.6k tokens when it runs, and up to ~5.2k if it reads all its reference files. Until then it costs about 97 tokens; SKILL.md has 1,092 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 linkfox-ai/linkfox-skills at commit 38fef04, republished under its MIT licence (© linkfox-ai). 1,092 words, ~2,582 tokens.
Download SKILL.mdSave it as
.claude/skills/linkfox-sorftime-amazon-product-query/SKILL.md (or your agent's skills folder). This skill also uses 4 other files; get the full folder from GitHub.- name
- linkfox-sorftime-amazon-product-query
- description
- 基于Sorftime数据的亚马逊多维度产品搜索与筛选，涵盖14个站点，支持历史月份快照回看。当用户提到Sorftime产品搜索、亚马逊产品筛选、竞品调研、类目分析、品牌热销、卖家分析、季节性产品、历史快照回看、产品搜索、月销量月销额、ABA关键词找产品、价格范围筛选、新品发现、多条件组合筛选、product search, competitor research, category analysis, brand bestsellers, seller analysis, seasonal products, historical snapshot时触发此技能。即使用户未明确提及"Sorftime"，只要其需求涉及亚马逊产品搜索、筛选、对比或类目/品牌/卖家维度的产品探索，也应触发此技能。
Sorftime Product Search
This skill guides you on how to search and filter Amazon products via Sorftime across multiple dimensions, helping Amazon sellers discover products, analyze competitors, and explore market opportunities.
Core Concepts
Sorftime Product Search supports multi-dimensional product retrieval with 16 query types, single or multi-condition AND combinations, and historical monthly snapshot lookback from January 2024. Data covers pricing, BSR rankings, monthly sales, FBA fees, and profit analysis.
Key differentiator: This tool is for searching and filtering across products. If you need detailed trend data (sales/price/BSR history) for a specific ASIN, use the Sorftime Product Detail skill instead.
Data Fields
Response data covers the following categories (see references/api.md for complete field reference):
- Basic info: ASIN, title, brand, listing URL, images (main + list), parent ASIN, variation count, weight, size
- Pricing & profit: current price, sale price (after coupon), strikethrough price, coupon, FBA fees (with detail breakdown), platform fee, profit amount & rate
- Sales: monthly sales units, monthly revenue, daily sales, daily revenue (values of -1 = cannot estimate)
- Rankings: BSR rank, category, sub-category rankings
- Ratings: rating score, rating count
- Listing info: listing date, days online
- Seller: Buybox seller name/ID/country, FBA status, seller count
- Listing features: A+ content, video, brand store
Supported Marketplaces
US (United States), GB (United Kingdom), DE (Germany), FR (France), IN (India), CA (Canada), JP (Japan), ES (Spain), IT (Italy), MX (Mexico), AE (United Arab Emirates), AU (Australia), BR (Brazil), SA (Saudi Arabia)
Default marketplace is US. Use us when the user doesn't specify a marketplace.
Note: Sorftime uses lowercase codes (e.g., us, gb, de), and UK is coded as gb (not uk).
调用方式
- API 端点：
POST /sorftime/amazon/productQuery（完整参数/响应/错误码见references/api.md） - Python 脚本：
python scripts/sorftime_product_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-sorftime-amazon-product-query-<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
The key parameters are marketplace (required), queryMode, queryType, and queryValue. The query system has two modes and 16 filter types that can be combined flexibly.
Principles for Building Queries
- Always specify the marketplace: Use lowercase site codes, e.g.,
us,de,jp - Choose the right query mode: Use
queryMode=1for a single filter; usequeryMode=2to combine multiple filters with AND logic - Match queryType with queryValue format: Each queryType expects a specific format - see the table below. Mismatched formats will cause errors
- Mind price units: Price filters (queryType=8) use smcurrency unit (cents for USD), so $19.99 =
1999 - Use open ranges when appropriate: Omit one end for open range -
,1000means "up to 1000";100,means "100 or more" - Use queryMonth for historical comparison: Format
yyyy-MM; compare with a second call without queryMonth to see changes over time
Query Types (queryType, for queryMode=1)
| queryType | Name | queryValue Format | Example |
|---|---|---|---|
| 1 | ASIN Similar | ASIN | B0CVM8TXHP |
| 2 | Category | NodeId | 3743561 |
| 3 | Brand | Brand name | Anker |
| 4 | Seller Name | Store name | AnkerDirect |
| 5 | Seller ID | SellerId | A294P4X9EWVXLJ |
| 6 | ABA Keyword | Keyword | Power Bank |
| 7 | Title/Attribute Match | Keywords | 10,000mAh 30W |
| 8 | Price Range | min,max (in cents) | 1,1000 (=$0.01~$10) |
| 9 | Monthly Sales Range | min,max | 100,1000 |
| 10 | Seasonal Products | Month list | 1,2,3 (peak in Jan-Mar) |
| 11 | Listing Date Range | start,end (yyyy-MM-dd) | 2024-06-01,2024-12-01 |
| 12 | Rating Range | min,max | 3,5 |
| 13 | Review Count Range | min,max | 10,500 |
| 14 | Rank Range | bsr_min,bsr_max;sub_min,sub_max | 500,5000;1,100 |
| 15 | Fulfillment | FBA / FBM | FBA,FBM |
| 16 | Variation Count | min,max | 1,50 |
Important: queryType=1 (ASIN Similar) finds products similar to the given ASIN, not the ASIN itself. To query a single product's detail, use the Sorftime Product Detail skill.
Historical Snapshots (queryMonth)
Set queryMonth (format yyyy-MM) to query a past month's product data snapshot. This lets users compare historical prices, rankings, and sales with current data.
- Supported range: January 2024 to present (~2 years)
- US, GB, DE support full "unlimited" lookback mode
- Other sites support Top 100 products only in lookback
- AU, BR, IN do not support lookback
Show full SKILL.md (432 more words)Show less
Query Examples for Common Scenarios
1. Fititors of a given ASIN
queryMode: 1, queryType: 1, queryValue: B0CVM8TXHP, marketplace: us2. Browse a category's top products
queryMode: 1, queryType: 2, queryValue: 3743561, marketplace: us3. Analyze a brand's product portfolio
queryMode: 1, queryType: 3, queryValue: Anker, marketplace: us4. Search by ABA keyword
queryMode: 1, queryType: 6, queryValue: Power Bank, marketplace: us5. Discover seasonal products (Q4 peak)
queryMode: 1, queryType: 10, queryValue: 10,11,12, marketplace: us6. Compare historical vs current data
queryMonth: 2024-11, queryMode: 1, queryType: 2, queryValue: 3743561, marketplace: us
-> Compare with current data (no queryMonth) to see price/sales changes7. Multi-condition: new FBA products with good sales
queryMode: 2
queryValue: [{"QueryType":11,"Content":"2024-06-01,"},{"QueryType":9,"Content":"300,"},{"QueryType":15,"Content":"FBA"}]
marketplace: us8. Find low-price high-sales products
queryMode: 2
queryValue: [{"QueryType":8,"Content":",2000"},{"QueryType":9,"Content":"500,"}]
marketplace: us9. Check a seller's product portfolio
queryMode: 1, queryType: 4, queryValue: AnkerDirect, marketplace: usDisplay Rules
- Present data only: Show query results in clear tables without subjective business advice
- Ranking clarification: When showing ranking data, remind users that lower values mean better rankings
- Pagination notice: Search results return max 100 products per page, up to 200 pages. If results are large, show highlights and remind users to paginate
- Sales estimation caveat: Values of
-1in sales/revenue fields mean "cannot estimate" - explain this to the user rather than showing -1 directly - Error handling: When a query fails, explain the reason based on the
msgfield and suggest adjusting query criteria
Important Limitations
- Pagination: Max 100 products per page, max 200 pages
- **Historisupported
- Non-structured data: Results do not support secondary analysis via
_dataQuery_executeDynamicQuery - Sales estimation: Products in non-standard categories may return -1 for sales fields
- ABA keyword search (queryType=6): Currently only supports ABA keywords, not arbitrary search terms
User Expression & Scenario Quick Reference
Applicable - Product search and filtering on Amazon:
| User Says | Scenario |
|---|---|
| "找一下这个类目下卖得好的产品" | Category exploration |
| "Anker品牌有哪些热销产品" | Brand analysis |
| "这个ASIN的竞品有哪些" | Competitor discovery |
| "帮我找一些季节性产品" | Seasonal product discovery |
| "新品中月销量超过500的有哪些" | Filtered product discovery |
| "去年双十一这个类目的价格快照" | Historical snapshot comparison |
| "这个卖家还卖了什么产品" | Seller portfolio |
| "帮我筛选利润率高于30%的FBA产品" | Profit-focused filtering |
| "月销量1000以上，评分4星以上的产品" | Multi-condition filtering |
| "标题包含wireless charger的产品" | Title keyword search |
Not applicable - Needs beyond product search:
- Detailed trend/history data for a specific ASIN (use Sorftime Product Detail)
- ABA search term ranking data (use ABA Data Explorer)
- Advertising / PPC strategy
- Product reviews content analysis
- Patent or trademark checks
Boundary judgment: When users say "competitor analysis" or "market research", if they need to discover and compare products across dimensions (category, brand, price range, etc.), this skill applies. If they need historical trend curves for a specific ASIN, use the Prt Detail skill. If they need keyword search volume data, use ABA Data Explorer.
算力消耗规则
按动态规则计费：消耗算力 = Sorftime内部查询次数 × 6。Sorftime内部查询次数：不同查询条件需要的查询次数可能不同，该次数由Sorftime决定。
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:
- The functionality or purpose described in this skill does not match actual behavior
- The skill's results do not match the user's intent
- The user expresses dissatisfaction or praise about this skill
- Anything you believe could be improved
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SKILL.md and 4 other files (scripts, references) in skills/linkfox-sorftime-amazon-product-query of linkfox-ai/linkfox-skills.
- SKILL.md
- references/api.md
- references/onboarding.md
- scripts/onboarding.py
- scripts/sorftime_product_search.py
Open the folder on GitHubat commit 38fef04
Compare with similar skills
Linkfox Sorftime Amazon Product Query 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 Sorftime Amazon Product Query this skilllinkfox-ai/linkfox-skills | 107 | — | ~2.6k | Automated safety check: Pass | MIT | |
| SEO Content Brief GeneratorAgriciDaniel/claude-seo | 19k | 2 repos | ~2.6k | Automated safety check: Pass | MIT | |
| SEO DataforseoAgriciDaniel/codex-seo | 799 | 2 repos | ~4.6k | Automated safety check: Pass | MIT | |
| Competitor ProfilingNexus-JPF/note-companion | 870 | 4 repos | ~3.5k | Automated safety check: Pass | MIT | |
| Startup Competitorsferdinandobons/startup-skill | 1.2k | — | ~4.1k | Automated safety check: Pass | MIT | |
| Amazon Listing Competitor Analysisbrowser-act/skills | 6.1k | 1 repos | ~3.2k | Automated safety check: Pass | MIT |
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Questions about Linkfox Sorftime Amazon Product Query
What does Linkfox Sorftime Amazon Product Query do?
基于Sorftime数据的亚马逊多维度产品搜索与筛选，涵盖14个站点，支持历史月份快照回看。当用户提到Sorftime产品搜索、亚马逊产品筛选、竞品调研、类目分析、品牌热销、卖家分析、季节性产品、历史快照回看、产品搜索、月销量月销额、ABA关键词找产品、价格范围筛选、新品发现、多条件组合筛选、product search, competitor research, category…. Linkfox Sorftime Amazon Product Query is an agent skill from linkfox-ai/linkfox-skills.
When should I use Linkfox Sorftime Amazon Product Query?
Linkfox Sorftime Amazon Product Query fits situations like: tasks that involve Competitor analysis.
How do I install Linkfox Sorftime Amazon Product Query in Claude Code?
Run `npx skills add linkfox-ai/linkfox-skills --skill linkfox-sorftime-amazon-product-query -a claude-code`. Or copy the skill folder (skills/linkfox-sorftime-amazon-product-query in linkfox-ai/linkfox-skills) into .claude/skills/linkfox-sorftime-amazon-product-query in your project. Claude Code loads it when a task matches its description.
How do I install Linkfox Sorftime Amazon Product Query in Codex?
Run `npx skills add linkfox-ai/linkfox-skills --skill linkfox-sorftime-amazon-product-query -a codex`. Or copy the skill folder (skills/linkfox-sorftime-amazon-product-query in linkfox-ai/linkfox-skills) into .agents/skills/linkfox-sorftime-amazon-product-query in your project. Codex loads it when a task matches its description.
Can I use Linkfox Sorftime Amazon Product Query 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-sorftime-amazon-product-query -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-sorftime-amazon-product-query, .gemini/skills/linkfox-sorftime-amazon-product-query, .github/skills/linkfox-sorftime-amazon-product-query and .opencode/skills/linkfox-sorftime-amazon-product-query in your project.
What does Linkfox Sorftime Amazon Product Query need to run?
Going by SKILL.md and its folder, Linkfox Sorftime Amazon Product Query 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 Sorftime Amazon Product Query access the network?
SKILL.md names 1 domain. As links in the text: skill.linkfox.com. This is read from the text; nothing was executed.
Is Linkfox Sorftime Amazon Product Query 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 Sorftime Amazon Product Query use?
Linkfox Sorftime Amazon Product Query 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 Sorftime Amazon Product Query use?
About 2.6k tokens (SKILL.md is roughly 10k 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 2.6k tokens, read only when the agent opens those files.
What are the alternatives to Linkfox Sorftime Amazon Product Query?
Skills that share tags, products or a category with Linkfox Sorftime Amazon Product Query: SEO Content Brief Generator (AgriciDaniel/claude-seo, 19k stars), SEO Dataforseo (AgriciDaniel/codex-seo, 799 stars), Competitor Profiling (Nexus-JPF/note-companion, 870 stars) and Startup Competitors (ferdinandobons/startup-skill, 1.2k stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.
Who maintains Linkfox Sorftime Amazon Product Query?
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.