Getting it into your agent
One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.
npx skills add linkfox-ai/linkfox-skills --skill linkfox-junglescout-sales-estimatesgit clone --depth 1 https://github.com/linkfox-ai/linkfox-skillsWrote this? Show the measurements
A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.
[](https://agentmods.dev/skills/linkfox-ai/linkfox-skills/linkfox-junglescout-sales-estimates)<a href="https://agentmods.dev/skills/linkfox-ai/linkfox-skills/linkfox-junglescout-sales-estimates"><img src="https://agentmods.dev/badge/skills/linkfox-ai/linkfox-skills/linkfox-junglescout-sales-estimates/github.svg" alt="Measured on agentmods" height="20"></a>Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.
<a href="https://agentmods.dev/skills/linkfox-ai/linkfox-skills/linkfox-junglescout-sales-estimates"><img src="https://agentmods.dev/badge/skills/linkfox-ai/linkfox-skills/linkfox-junglescout-sales-estimates.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- Socket warn
- Snyk pass
- NVIDIA SkillSpector warn
SkillSpector: 1 finding, up to high
These are SkillSpector’s own severities. On a checked sample its high-severity flags on skills were ~96% false positives — a documented command, a public API, a “never do X” rule — so we show them as a caution to read, not a verdict. Why →
- high System Prompt Leakage · line 136 Skill contains instructions that could directly expose system prompts, internal rules, or hidden instructions to users or external parties.Fix: Remove any instructions that reveal, print, or output system prompts or internal rules. System instructions should never be exposed to end users.
What it costs to keep this loaded
Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5.1 | $0.00174 | $0.02779 |
| Opus 5 | $0.00087 | $0.01389 |
| Sonnet 5 | $0.00035 | $0.00556 |
| Haiku 4.5 | $0.00017 | $0.00278 |
Grade A, and why
linkfox-junglescout-sales-estimates scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 9d ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
How it starts
The opening of the file, as written. The whole thing — 193 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Jungle Scout — ASIN 销售估算
This skill queries daily sales estimates and last known price for a given Amazon ASIN via the Jungle Scout data source, returning day-level data points over a specified date range across 10 Amazon marketplaces.
Core Concepts
Jungle Scout ASIN 销售估算工具提供亚马逊各站点单个 ASIN 的日维度预估销量及最近已知价格。卖家可以通过查询指定时间范围内的销量变化来：
- 监控竞品销量：了解竞品每日出单量，评估其市场份额
- 验证选品机会：用实际销量数据验证产品需求是否足够大
- 追踪季节性规律：观察产品在不同月份的销量波动，判断旺淡季
- 评估定价影响：结合价格与销量的变化关系，辅助定价决策
- 新品表现跟踪：追踪新品上架后的销量爬升曲线
数据粒度：每条记录代表 1 天，包含该日的预估售出件数和最近已知价格（美元）。
Data Fields
Output Fields
| Field | API Name | Description | Example |
|---|---|---|---|
| ASIN | asin | 查询的 ASIN | B0CXXX1234 |
| 数据标识 | id | 数据点标识 | sales_estimate_B0CXXX1234_20260301 |
| 资源类型 | type | 固定值 | sales_estimate_result |
| 父 ASIN | parentAsin | 父体 ASIN（变体场景） | B0CXXX0000 |
| 是否父体 | isParent | 是否为父体商品 | true / false |
| 是否变体 | isVariant | 是否为变体商品 | true / false |
| 是否独立 | isStandalone | 是否为独立商品（非变体） | true / false |
| 变体列表 | variants | 该父体下的变体 ASIN 数组 | ["B0CX1", "B0CX2"] |
| 每日估算 | dailyEstimates | 每日数据数组 | 见下方 |
| 消耗 Token | costToken | 本次调用消耗的 token 数 | 1 |
dailyEstimates 数组中每个对象
| Field | API Name | Description | Example |
|---|---|---|---|
| 日期 | date | 数据日期（YYYY-MM-DD） | 2026-03-15 |
| 预估日销量 | estimatedUnitsSold | 当日预估售出件数 | 42 |
| 最近已知价格 | lastKnownPrice | 最近已知价格（USD） | 29.99 |
Supported Marketplaces
10 个亚马逊站点：us（美国）、uk（英国）、de（德国）、in（印度）、ca（加拿大）、fr（法国）、it（意大利）、es（西班牙）、mx（墨西哥）、jp（日本）。默认站点为 us。当用户未指定站点时，使用 us。
调用方式
- API 端点：
POST /tool-jungle-scout/sales-estimates/query（完整参数/响应/错误码见references/api.md） - Python 脚本：
python scripts/junglescout_sales_estimates.py '<JSON 参数>' [--inline] - 成本约束：本工具会消耗积分；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-sales-estimates-<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）
What ships with it
4 files beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.
What this file has done since we first saw it
Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.
- 9d ago First seen · 193 lines · 174 tokens per session scan A 0cd8d71c4f69
linkfox-junglescout-sales-estimates is a skill published in the GitHub repository linkfox-ai/linkfox-skills (101 stars, last pushed 22d ago), licensed MIT. It adds 174 tokens to every session and 2,779 once invoked, about $0.0009 per session on Opus 5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-09-03.
Other skills, from other repositories
amazon-reviews-api-skill
This skill helps users automatically extract Amazon product reviews via the Amazon Reviews API. Agent should proactively apply this skill when users express needs like getting reviews for Amazon product with ASIN B07TS6R1SF, analyzing customer feedback for a specific Amazon item, getting ratings and comments for a…
amazon-competitor-analyzer
Scrapes Amazon product data from ASINs using browseract.com automation API and performs surgical competitive analysis. Compares specifications, pricing, review quality, and visual strategies to identify competitor moats and vulnerabilities.
asc-subscription-localization
Bulk-localize subscription, subscription-group, and in-app purchase display names across App Store locales using asc, including API 4.4.1 version-scoped v2 resources. Use when filling or updating subscription/IAP names and descriptions without App Store Connect UI work.
food-order
Reorder previous Foodora orders, preview cart contents, and track delivery ETA/status with ordercli. Use when the user wants to reorder food, check delivery status, or browse recent Foodora order history. Never confirm an order without explicit user approval.
product-description-generator
E-commerce product description generator for any platform. Generates optimized titles, bullet points, descriptions, and backend keywords using competitor research + keyword scoring + FABE copywriting. Two modes: (A) Create — generate listing from product specs with optional competitor analysis, (B) Optimize — improve…
amazon-price-tracker
Amazon price monitoring and competitive pricing intelligence. Real-time price tracking, Buy Box analysis, promotion detection, and dynamic pricing strategy optimization. Use when the user asks about price monitoring, competitor pricing, Buy Box tracking, or pricing strategy.