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 agentmods add skills/gingiris-1031/gingiris-skills/gr-competitornpx skills add Gingiris-1031/gingiris-skills --skill gr-competitorgit clone --depth 1 https://github.com/Gingiris-1031/gingiris-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/gingiris-1031/gingiris-skills/gr-competitor)<a href="https://agentmods.dev/skills/gingiris-1031/gingiris-skills/gr-competitor"><img src="https://agentmods.dev/badge/skills/gingiris-1031/gingiris-skills/gr-competitor.svg" alt="Measured on agentmods" height="20"></a>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 | $0.00099 | $0.01536 |
| Opus 5 | $0.00049 | $0.00768 |
| Sonnet 5 | $0.00020 | $0.00307 |
| Haiku 4.5 | $0.00010 | $0.00154 |
Grade A, and why
gr-competitor scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 6d ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
How it starts
The opening of the file, as written. The whole thing — 190 lines — stays where its author put it; the contents beside it link to each section on GitHub.
gr-competitor — 竞品扫描
什么时候用
- "帮我分析一下 10 个对手的落地页"
- "看一下 XX 的定价模式"
- "这 5 个竞品博客最近 30 天发了什么"
- "对标一下产品的 features"
底层:actionbook
这个 skill 是 orchestrator —— 真正干活的是 actionbook。 它能:
- 10x 快(直接调一方 API,跳过 DOM 解析)
- 省 90% token(返回结构化数据而非 DOM 快照)
- 30 tab 并发(一次扫完 top 30)
安装 actionbook(首次使用)
# macOS / Linux
npm install -g @actionbookdev/cli
# 或用 npx 临时跑
npx @actionbookdev/cli browser start
Chrome 扩展:从 Chrome Web Store 搜 "Actionbook Extension" 或 https://actionbook.dev
验证可用
actionbook --version # 应输出 0.x.x
actionbook browser start # 启动 local browser server
调用流程(4 步)
Step 1:search action manual
对每个目标站点,先查 actionbook 是否已有 manual:
actionbook search "product hunt"
actionbook search "crunchbase"
有 manual → 跳 Step 3 无 manual → Step 2
Step 2:fallback 到通用 extract
actionbook extract <url> \
--fields "title,h1,intro,pricing_tier,cta_text" \
--output json
actionbook 会:
- 用通用 selector 探测
- 产出 JSON + 可复跑的 Playwright 脚本
Step 3:并发扫描
# 30 个对手一起扫
for url in "${urls[@]}"; do
actionbook extract "$url" --fields "..." --session scan1 &
done
wait
Step 4:合成报告
Claude 把 30 个 JSON 合成:
- Title / Tagline 矩阵
- 定价分层对比
- 共同 CTA 动词("get started" vs "book demo" vs "try free")
- 差异点 → 我们可钻的空隙
常用 prompt 模板
模板 1:产品落地页扫描
用 gr-competitor 扫这 10 个对手的落地页,产出一张表:
- 对手名 | tagline | 主 CTA | pricing 起步价 | 主 hero 视觉特征(3 个关键词)
对手:
1. https://...
2. ...
输出:markdown 表格 + 3 条"我们可以差异化"的建议
模板 2:博客内容对比
用 gr-competitor 抓这 5 个对手博客 index 页的 title 列表(top 10 最新):
- https://a.com/blog
- https://b.com/blog
...
然后告诉我:
1. 重叠主题(我们已写过)
2. 他们写我们没写的(我们的选题机会)
3. 他们写得不好的(我们可以超越的)
模板 3:定价页审计
用 gr-competitor 抓这 8 家 SaaS 定价页:
- 分层数量
- 最低价 / 企业价
- Annual 折扣
- Free tier 限制
汇总成对比表,标出"市场中位数"和"我们的相对位置"
级联推荐
- 发现对手新打法 →
gr-blog-post写回应稿件 - 发现对手定价漏洞 →
gr-b2b-growth重设我方定价 - 发现对手被用户吐槽 →
gr-user-interview访谈吐槽用户验证 - 扫描结果加入监控 → 建 scheduled task 每周重扫
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.
- 6d ago First seen · 190 lines · 99 tokens per session scan A 56cf8b736680
gr-competitor is a skill published in the GitHub repository Gingiris-1031/gingiris-skills (77 stars, last pushed yesterday), licensed MIT. It adds 99 tokens to every session and 1,536 once invoked, about $0.0005 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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