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-amazon-opportunity-report-by-keywordgit 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-amazon-opportunity-report-by-keyword)<a href="https://agentmods.dev/skills/linkfox-ai/linkfox-skills/linkfox-amazon-opportunity-report-by-keyword"><img src="https://agentmods.dev/badge/skills/linkfox-ai/linkfox-skills/linkfox-amazon-opportunity-report-by-keyword/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-amazon-opportunity-report-by-keyword"><img src="https://agentmods.dev/badge/skills/linkfox-ai/linkfox-skills/linkfox-amazon-opportunity-report-by-keyword.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- 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 74 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 | $0.00169 | $0.01709 |
| Opus 5 | $0.00084 | $0.00855 |
| Sonnet 5 | $0.00034 | $0.00342 |
| Haiku 4.5 | $0.00017 | $0.00171 |
Grade A, and why
linkfox-amazon-opportunity-report-by-keyword 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 12d 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 — 130 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Amazon Market Opportunity Report
This skill guides you on how to generate comprehensive AI-powered market insight reports for Amazon keywords, helping sellers make data-driven product selection and market entry decisions.
Core Concepts
This tool generates a comprehensive business insight report by analyzing six core dimensions of an Amazon keyword:
- Market Potential - Search volume, demand trends, and growth opportunity
- Product Characteristics - Common product attributes, materials, features
- User Reviews - Customer sentiment, pain points, and satisfaction drivers
- Customer Profile - Buyer demographics, preferences, and behavior patterns
- Search Trends - Keyword popularity trajectory and seasonality
- Pricing Analysis - Price distribution, competitive pricing landscape
The report is generated by AI from real-time Amazon data and delivered as a structured Markdown document. It is a snapshot analysis for decision support, not a real-time monitoring tool.
Parameters
| Parameter | Type | Required | Description | Default |
|---|---|---|---|---|
| site | string | Yes | Amazon marketplace code (currently US only) | US |
| keyword | string | Yes | The search keyword to analyze | - |
Supported Marketplaces
Currently only US (United States) is supported. Always set site to US. If a user requests other marketplaces, inform them this tool currently only covers the US market.
调用方式
- API 端点：
POST /amazon/opportunity/reportByKeyword（完整参数/响应/错误码见references/api.md） - Python 脚本：
python scripts/amazon_opportunity_report.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-amazon-opportunity-report-by-keyword-<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.
- 12d ago First seen · 130 lines · 169 tokens per session scan A 75f24c0ee1be
linkfox-amazon-opportunity-report-by-keyword is a skill published in the GitHub repository linkfox-ai/linkfox-skills (101 stars, last pushed 22d ago), licensed MIT. It adds 169 tokens to every session and 1,709 once invoked, about $0.0008 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 2026-08-30.
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