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 kennyzir/7deer_skills --skill keyword-competition-analysisgit clone --depth 1 https://github.com/kennyzir/7deer_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/kennyzir/7deer_skills/keyword-competition-analysis)<a href="https://agentmods.dev/skills/kennyzir/7deer_skills/keyword-competition-analysis"><img src="https://agentmods.dev/badge/skills/kennyzir/7deer_skills/keyword-competition-analysis/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/kennyzir/7deer_skills/keyword-competition-analysis"><img src="https://agentmods.dev/badge/skills/kennyzir/7deer_skills/keyword-competition-analysis.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector pass
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 | $0.00068 | $0.00672 |
| Opus 5 | $0.00034 | $0.00336 |
| Sonnet 5 | $0.00014 | $0.00134 |
| Haiku 4.5 | $0.00007 | $0.00067 |
Grade A, and why
keyword-competition-analysis 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.
What it actually says
Keyword Competition Analysis
基于 Google 搜索结果页的关键词竞争度分析技能。
工作流程
Step 1：发起搜索
使用 browser 工具打开 Google 搜索结果页：
https://www.google.com/search?q=<URL编码的关键词>
Step 2：获取快照
用 browser snapshot compact=true 抓取搜索结果页，识别：
- 广告数量和广告主
- 前10自然结果标题 + 域名
- 是否有精选摘要、视频结果、People Also Search For
- 结果类型分布（官方文档/社区/工具/视频/论坛）
Step 3：二次验证（如需要）
打开1-2个典型结果页面，快速确认：
- 内容深度（页面字数/内容量级）
- 页面优化痕迹（标题、H标签、keywords标签）
- 域名大致权重感
Step 4：输出报告
按以下结构输出，详见 references/output-template.md：
- 基本信号评分表
- 竞争者画像
- 机会识别
- 综合判断
评分维度说明
| 维度 | 评估重点 |
|---|---|
| 广告主密度 | 多 = 商业价值高 = 竞争激烈 |
| 结果主体 | 高权重站（官方/维基/Quora）为主 = 壁垒高 |
| 内容深度 | 300字浅页面 vs 3000字+深度内容 |
| 精选摘要 | 有 = SEO空间被压缩 |
| 视频结果 | 有 = 视频布局已是红海 |
| 域名年龄感 | 全是老站 = 难；有机会站点出现 = 可切入 |
低竞争突破口识别
- 结果里有 PDF/PPT/论坛/Quora → 内容生态弱，机会
- 没有视频结果 → 视频是机会
- 工具/导航类结果多 → 内容站有机会
- Search Intent 混杂（教程+产品混排）→ 细分人群可切
长尾词发现
从 People Also Search For 区域提取高价值长尾方向：
- 资源导向（...GitHub, ...examples）
- 评测导向（Best ...，...vs...）
- 教程导向（how to ..., ...tutorial）
注意事项
- Google 搜索有反爬，优先用
browser工具而非web_search - 不要依赖结果总数（谷歌已取消精确数字）
- 综合判断要带时效性提示（新市场窗口 vs 成熟红海）
What ships with it
1 file 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 · 74 lines · 68 tokens per session scan A 8f362aab4a14
keyword-competition-analysis is a skill published in the GitHub repository kennyzir/7deer_skills (313 stars, last pushed 4d ago), licensed MIT. It adds 68 tokens to every session and 672 once invoked, about $0.0003 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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