Agent skill

Linkfox Junglescout Product Database

by linkfox-ai in linkfox-ai/linkfox-skills

Jungle Scout产品数据库多条件筛选,支持按品类、价格、销量、收入、评论、评分、重量、BSR排名、LQS、卖家类型等维度筛选亚马逊商品,覆盖10个站点。当用户提到亚马逊选品、产品数据库筛选、BSR排名筛选、品类选品、高评分低竞争选品、FBA选品、亚马逊商品搜索、产品筛选、Amazon product database, product research, product…

MITAuto-check passedProduct & Project Management

Install Linkfox Junglescout Product Database

skills CLI
$ npx skills add linkfox-ai/linkfox-skills --skill linkfox-junglescout-product-database -a claude-code

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

GitHub CLI
$ gh skill install linkfox-ai/linkfox-skills linkfox-junglescout-product-database --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-junglescout-product-database .claude/skills/linkfox-junglescout-product-database && 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-junglescout-product-database
GitHub stars
107
Used in
1 other repo
Token cost
~2.1k tokens
SKILL.md length
696 words
Files
5 (incl. scripts, references)
Skills in repo
177
Repo updated
First seen
Licence
MIT

At a glance

Jungle Scout产品数据库多条件筛选,支持按品类、价格、销量、收入、评论、评分、重量、BSR排名、LQS、卖家类型等维度筛选亚马逊商品,覆盖10个站点。当用户提到亚马逊选品、产品数据库筛选、BSR排名筛选、品类选品、高评分低竞争选品、FBA选品、亚马逊商品搜索、产品筛选、Amazon product database, product research, product…

  • Works in 6 steps: 站点映射:用户说"美国站"→ us,"日本站"→ jp,"德国站"→… → 关键词:includeKeywords 支持逗号分隔多个词(标题或ASIN),如… → 品类匹配:categories 必须使用对应站点的英文标准分类名,如美国站… → …
  • Product & Project Management work in your project
  • 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 Junglescout Product Database is an agent skill from linkfox-ai/linkfox-skills. Jungle Scout产品数据库多条件筛选,支持按品类、价格、销量、收入、评论、评分、重量、BSR排名、LQS、卖家类型等维度筛选亚马逊商品,覆盖10个站点。当用户提到亚马逊选品、产品数据库筛选、BSR排名筛选、品类选品、高评分低竞争选品、FBA选品、亚马逊商品搜索、产品筛选、Amazon product database, product research, product filtering, BSR rank filter, category product search, niche product finder, FBA product search, Amazon product discovery, low competition products, Jungle Scout product database时触发此技能。即使用户未明确提及"Jungle Scout"或"产品数据库",只要其需求涉及按多条件筛选亚马逊商品或发现潜力产品,也应触发此技能。

Its SKILL.md is about 2.1k 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/junglescout_product_database.py`).

It sits in Product & Project Management. The licence is MIT.

When your agent uses it

  • Product & Project Management work in your project

Example prompts

  • “Jungle Scout”
  • “/linkfox-junglescout-product-database”

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.

  1. 站点映射:用户说"美国站"→ us,"日本站"→ jp,"德国站"→ de;未指定时默认 us
  2. 关键词:includeKeywords 支持逗号分隔多个词(标题或ASIN),如 yoga mat,fitness;excludeKeywords 排除含特定词的商品
  3. 品类匹配:categories 必须使用对应站点的英文标准分类名,如美国站 Sports & Outdoors、Home & Kitchen 等;多个品类逗号分隔
  4. 数值范围:min/max 成对使用,可只传一端;如只设 minSales=300 表示月销量≥300
  5. 排序:sort 字段名前加 - 表示降序,如 -sales 按销量从高到低;默认按 name 升序
  6. 结果数量:needCount 控制返回结果总数,不设则返回默认数量

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_KEY
    • LINKFOXAGENT_API_KEY

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

Context cost

Linkfox Junglescout Product Database loads about 2.1k tokens when it runs, and up to ~4.8k if it reads all its reference files. Until then it costs about 119 tokens; SKILL.md has 696 words of instructions outside code blocks.

Always · name and description, kept in context so the agent knows when to use it
~119
When it runs · the whole SKILL.md, loaded when a task matches
~2.1k
With references · SKILL.md plus every file in references/, read only if the agent opens them
~4.8k

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). 696 words, ~2,076 tokens.

Download SKILL.mdSave it as .claude/skills/linkfox-junglescout-product-database/SKILL.md (or your agent's skills folder). This skill also uses 4 other files; get the full folder from GitHub.
name
linkfox-junglescout-product-database
description
Jungle Scout产品数据库多条件筛选,支持按品类、价格、销量、收入、评论、评分、重量、BSR排名、LQS、卖家类型等维度筛选亚马逊商品,覆盖10个站点。当用户提到亚马逊选品、产品数据库筛选、BSR排名筛选、品类选品、高评分低竞争选品、FBA选品、亚马逊商品搜索、产品筛选、Amazon product database, product research, product filtering, BSR rank filter, category product search, niche product finder, FBA product search, Amazon product discovery, low competition products, Jungle Scout product database时触发此技能。即使用户未明确提及"Jungle Scout"或"产品数据库",只要其需求涉及按多条件筛选亚马逊商品或发现潜力产品,也应触发此技能。

Jungle Scout — 产品数据库查询

This skill queries the Jungle Scout Product Database via the LinkFox tool gateway, enabling multi-condition filtering of Amazon products across 10 marketplaces. Sellers can discover products by category, price range, sales volume, revenue, reviews, rating, BSR rank, Listing Quality Score (LQS), seller type, and more.

Core Concepts

Jungle Scout 产品数据库是亚马逊商品级别的多维筛选工具,帮助卖家从海量商品中快速锁定目标产品:

  • 品类选品:按亚马逊主分类筛选特定品类下的商品
  • 销量/收入筛选:通过月销量和月收入范围圈定市场规模合适的产品
  • 竞争度评估:通过评论数、评分、卖家数量判断竞争激烈程度
  • Listing 质量评估:LQS(Listing Quality Score,1-10分)帮助发现优化空间大的产品
  • 产品类型过滤:区分 FBA/FBM/AMZ 卖家类型、标准尺寸/超大尺寸
  • 新品发现:通过上架日期筛选近期上架的新品

Internal paging: The API handles pagination automatically; you specify needCount to control how many results you want, and the backend fetches them across pages internally.

Data Fields

Key Output Fields
FieldAPI NameDescriptionExample
商品标题title产品标题Yoga Mat Non Slip...
品牌brand品牌名称Liforme
主分类category亚马逊主分类Sports & Outdoors
分类路径breadcrumbPath完整分类层级Sports & Outdoors > Exercise & Fitness
价格price当前售价 (USD)29.99
月销量approximate30DayUnitsSold近30天预估销量1200
月收入approximate30DayRevenue近30天预估收入 (USD)35988.00
BSR排名productRankBest Sellers Rank3456
评论数reviews累计评论数850
评分rating平均评分 (1.0-5.0)4.5
LQSlistingQualityScoreListing质量评分 (1-10)8
卖家数量numberOfSellers在售卖家数3
卖家类型sellerType卖家类型 (amz/fba/fbm)fba
首次上架日期dateFirstAvailable产品首次上架日期2024-06-15
重量weightValue / weightUnit产品重量2.5 lbs
尺寸lengthValue / widthValue / heightValue / dimensionsUnit产品尺寸24×8×8 inches
父ASINparentAsin父体ASINB0XXXXXXXX
Buy Box持有者buyBoxOwnerBuy Box 当前持有卖家BrandName
费用明细feeBreakdownFBA费用、推荐费、总费用等{fbaFee: 5.40, ...}
子分类排名subcategoryRanks子分类BSR排名列表[{subcategory: "Yoga Mats", rank: 12}]
消耗TokencostToken本次调用消耗的 token 数5

Supported Marketplaces

us (United States), uk (United Kingdom), de (Germany), in (India), ca (Canada), fr (France), it (Italy), es (Spain), mx (Mexico), jp (Japan)

Default marketplace is us. Use us when the user doesn't specify a marketplace.

调用方式

  • API 端点:POST /tool-jungle-scout/product-database/query(完整参数/响应/错误码见 references/api.md)
  • Python 脚本:python scripts/junglescout_product_database.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-junglescout-product-database-<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

Only marketplace is required. All other parameters are optional filters — combine them to narrow results.

Principles for Building API Calls
  1. 站点映射:用户说"美国站"→ us,"日本站"→ jp,"德国站"→ de;未指定时默认 us
  2. 关键词:includeKeywords 支持逗号分隔多个词(标题或ASIN),如 yoga mat,fitness;excludeKeywords 排除含特定词的商品
  3. 品类匹配:categories 必须使用对应站点的英文标准分类名,如美国站 Sports & Outdoors、Home & Kitchen 等;多个品类逗号分隔
  4. 数值范围:min/max 成对使用,可只传一端;如只设 minSales=300 表示月销量≥300
  5. 排序:sort 字段名前加 - 表示降序,如 -sales 按销量从高到低;默认按 name 升序
  6. 结果数量:needCount 控制返回结果总数,不设则返回默认数量
Common Query Scenarios

1. 关键词搜索 + 按销量筛选

json
{
  "marketplace": "us",
  "includeKeywords": "yoga mat",
  "minSales": 300,
  "maxSales": 5000,
  "sort": "-sales",
  "needCount": 50
}

2. 品类 + 价格区间筛选

json
{
  "marketplace": "us",
  "categories": "Home & Kitchen",
  "minPrice": 15,
  "maxPrice": 50,
  "minSales": 100,
  "sort": "-revenue",
  "needCount": 50
}

3. 高评分低竞争选品(评论少但评分高)

json
{
  "marketplace": "us",
  "categories": "Beauty & Personal Care",
  "minRating": 4.0,
  "maxReviews": 200,
  "minSales": 100,
  "sort": "-sales",
  "needCount": 50
}

4. 仅 FBA 产品筛选

json
{
  "marketplace": "us",
  "includeKeywords": "phone stand",
  "sellerTypes": "fba",
  "productTiers": "standard",
  "minSales": 200,
  "sort": "-sales",
  "needCount": 50
}

5. 排除头部品牌 + 发现蓝海机会

json
{
  "marketplace": "us",
  "categories": "Sports & Outdoors",
  "excludeTopBrands": true,
  "minSales": 300,
  "maxReviews": 500,
  "minRating": 4.0,
  "sort": "-sales",
  "needCount": 50
}

6. 按上架日期发现新品

json
{
  "marketplace": "us",
  "categories": "Electronics",
  "minUpdatedAt": "2026-01-01",
  "minSales": 50,
  "sort": "-sales",
  "needCount": 50
}
Show full SKILL.md (304 more words)Show less

Display Rules

  1. Table format: Present results in a structured table with key columns: title, brand, price, monthly sales, monthly revenue, BSR rank, reviews, rating, LQS
  2. Sorting note: Remind the user what sorting was applied and how many results were returned
  3. Highlight insights: Mark products with notably low reviews but high sales (potential opportunity), or high LQS scores
  4. Fee breakdown: When users ask about profitability, include feeBreakdown details (FBA fee, referral fee, total fees)
  5. Image links: Include imageUrl when displaying individual product details
  6. Error handling: When a query fails, explain the reason based on the error response and suggest adjusting parameters

Important Limitations

  • marketplace 必填:每次查询必须指定站点
  • 品类名需匹配:categories 值必须与对应站点的标准主分类名完全一致
  • 关键词限制:includeKeywords / excludeKeywords 最多各100项,每项最长50字符
  • 数据时效:数据来源于 Jungle Scout 定期更新,非实时数据
  • 评分范围:minRating / maxRating 取值 1.0-5.0
  • 重量单位:minWeight / maxWeight 以磅(pounds)为单位

User Expression & Scenario Quick Reference

Applicable - Amazon product multi-condition filtering and discovery:

User SaysScenario
"帮我找月销量500以上的瑜伽垫"关键词 + 销量筛选
"美国站厨房品类30美金以下有什么好产品"品类 + 价格筛选
"评论少但评分高的蓝海产品"高评分低竞争选品
"找FBA标准尺寸的手机支架"卖家类型 + 产品尺寸筛选
"排除大品牌的运动品类机会"排除头部品牌
"最近新上架的电子产品有哪些卖得好"新品发现
"BSR排名1万以内的家居产品"BSR排名筛选
"LQS低于5分的高销量产品"Listing优化机会

Not applicable - Beyond product database filtering:

  • 关键词搜索量/趋势分析(需要关键词历史搜索量工具)
  • ABA搜索词排名(需要ABA工具)
  • 商品详情页/Listing内容分析
  • 广告/PPC投放策略
  • 非亚马逊平台商品数据

Boundary judgment: When users say "选品", "找产品", or "市场调研", if their need is to filter products by specific criteria (price, sales, category, reviews, etc.) from Amazon's product catalog, this skill applies. If they need keyword-level search volume data, advertising insights, or non-Amazon platform data, it does not apply.

算力消耗规则

按动态规则计费:消耗算力 = 实际查询页数 × 63.75。

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, visit 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-junglescout-product-database of linkfox-ai/linkfox-skills.

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

Open the folder on GitHubat commit 38fef04

Used in 1 other repository

We found 1 copy 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 Junglescout Product Database 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 Junglescout Product Database compared with similar skills
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Game Changing FeaturesopenstatusHQ/data-table-filters2.3k3 repos~2.1kAutomated safety check: PassMIT
CCPM Project Managementautomazeio/ccpm8.4k—~1.1kAutomated safety check: PassMIT
Convex Create Componentspokvulcan/poker-planning1158 repos~2.6kAutomated safety check: PassMIT
Self Improving Agentfarm-fe/farm5.6k2 repos~3.3kAutomated safety check: NotesMIT

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    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…

    107 GitHub starsUsed in 1 repo~3k tokens
    Auto-check passed
  • 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…

    107 GitHub starsUsed in 1 repo~3k tokens
    Auto-check passed
  • Linkfox Amazon Product Detail

    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…

    107 GitHub starsUsed in 1 repo~2.5k tokens
    Auto-check passed
  • Linkfox Amazon Reviews List

    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…

    107 GitHub starsUsed in 1 repo~2.5k tokens
    Auto-check passed

Questions about Linkfox Junglescout Product Database

What does Linkfox Junglescout Product Database do?

Jungle Scout产品数据库多条件筛选,支持按品类、价格、销量、收入、评论、评分、重量、BSR排名、LQS、卖家类型等维度筛选亚马逊商品,覆盖10个站点。当用户提到亚马逊选品、产品数据库筛选、BSR排名筛选、品类选品、高评分低竞争选品、FBA选品、亚马逊商品搜索、产品筛选、Amazon product database, product research, product…. Linkfox Junglescout Product Database is an agent skill from linkfox-ai/linkfox-skills.

When should I use Linkfox Junglescout Product Database?

Linkfox Junglescout Product Database fits situations like: product & Project Management work in your project.

How do I install Linkfox Junglescout Product Database in Claude Code?

Run `npx skills add linkfox-ai/linkfox-skills --skill linkfox-junglescout-product-database -a claude-code`. Or copy the skill folder (skills/linkfox-junglescout-product-database in linkfox-ai/linkfox-skills) into .claude/skills/linkfox-junglescout-product-database in your project. Claude Code loads it when a task matches its description.

How do I install Linkfox Junglescout Product Database in Codex?

Run `npx skills add linkfox-ai/linkfox-skills --skill linkfox-junglescout-product-database -a codex`. Or copy the skill folder (skills/linkfox-junglescout-product-database in linkfox-ai/linkfox-skills) into .agents/skills/linkfox-junglescout-product-database in your project. Codex loads it when a task matches its description.

Can I use Linkfox Junglescout Product Database 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-junglescout-product-database -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-junglescout-product-database, .gemini/skills/linkfox-junglescout-product-database, .github/skills/linkfox-junglescout-product-database and .opencode/skills/linkfox-junglescout-product-database in your project.

What does Linkfox Junglescout Product Database need to run?

Going by SKILL.md and its folder, Linkfox Junglescout Product Database 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 Junglescout Product Database 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 Junglescout Product Database 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 Junglescout Product Database use?

Linkfox Junglescout Product Database 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 Junglescout Product Database use?

About 2.1k tokens (SKILL.md is roughly 8.3k characters). Agents keep only the skill's name and description in context until a task matches; then they load SKILL.md in full. Its references folder adds about 2.7k tokens, read only when the agent opens those files.

What are the alternatives to Linkfox Junglescout Product Database?

Skills that share tags, products or a category with Linkfox Junglescout Product Database: User Story Writer (deanpeters/Product-Manager-Skills, 7.2k stars), Game Changing Features (openstatusHQ/data-table-filters, 2.3k stars), CCPM Project Management (automazeio/ccpm, 8.4k stars) and Convex Create Component (spokvulcan/poker-planning, 115 stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.

Who maintains Linkfox Junglescout Product Database?

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.