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 malue-ai/dazee-small --skill competitive-intelgit clone --depth 1 https://github.com/malue-ai/dazee-smallWrote 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/malue-ai/dazee-small/competitive-intel)<a href="https://agentmods.dev/skills/malue-ai/dazee-small/competitive-intel"><img src="https://agentmods.dev/badge/skills/malue-ai/dazee-small/competitive-intel.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 | $0.00022 | $0.00855 |
| Opus 5 | $0.00011 | $0.00428 |
| Sonnet 5 | $0.00004 | $0.00171 |
| Haiku 4.5 | $0.00002 | $0.00085 |
Grade C, and why
competitive-intel scanned grade C with 2 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 7d ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Downloads and executes remote codehighSupply chain
curl | sh runs whatever the server returns today, which is not necessarily what it returned when this was reviewed.
curl -s "https://competitor.com/pricing" | python3 -c " Makes network callslowCapability
Not a fault in itself. Listed so you know the mod talks to something, and to what.
curl -s "https://competitor.com/pricing" | python3 -c " What it actually says
竞品动态监控
监控竞品网站、产品更新和社交媒体动态,生成竞争情报报告。
使用场景
- 用户说「帮我跟踪一下 XX 竞品的动态」「XX 最近有什么更新」
- 产品经理需要定期了解竞品变化
- 创业者需要监控市场动态
监控方式
1. 网站变更检测
# 抓取网页内容快照
curl -s "https://competitor.com/pricing" | python3 -c "
import sys
from html.parser import HTMLParser
class TextExtractor(HTMLParser):
def __init__(self):
super().__init__()
self.texts = []
def handle_data(self, data):
text = data.strip()
if text:
self.texts.append(text)
parser = TextExtractor()
parser.feed(sys.stdin.read())
print('\n'.join(parser.texts[:50]))
" > /tmp/competitor_$(date +%Y%m%d).txt
# 与上次快照对比
diff /tmp/competitor_prev.txt /tmp/competitor_$(date +%Y%m%d).txt
2. RSS/博客监控
配合 blogwatcher Skill 追踪竞品博客更新。
3. GitHub 监控(开源竞品)
配合 github Skill 追踪竞品仓库的 Release、Issue、PR。
# 查看竞品最近的 Release
gh release list --repo competitor/product --limit 5
4. 社交媒体关键词监控
# 通过公开 API 搜索关键词(示例:Twitter/X API)
# 需要 API Key,可选
curl -s "https://api.twitter.com/2/tweets/search/recent?query=竞品名称" \
-H "Authorization: Bearer $TWITTER_BEARER_TOKEN"
报告格式
## 竞品动态报告 — {竞品名称}
**报告日期**: 2025-02-07
**监控周期**: 过去 7 天
### 产品更新
- [2025-02-05] 发布 v3.2,新增 XX 功能
- [2025-02-03] 定价页面调整,企业版涨价 10%
### 社交媒体动态
- 官方博客发布了关于 AI 集成的文章
- Twitter 上获得 500+ 转发
### 关键变化
1. 功能差异:新增了我们没有的 XX 功能
2. 定价变化:企业版价格上调
3. 市场信号:加大了 AI 方向的投入
### 建议行动
- 评估 XX 功能的用户需求优先级
- 关注其 AI 集成方案的用户反馈
数据存储
# 竞品追踪配置
mkdir -p ~/.xiaodazi/competitive
# 竞品列表
cat > ~/.xiaodazi/competitive/watchlist.json << 'EOF'
{
"competitors": [
{
"name": "CompetitorA",
"website": "https://competitor-a.com",
"blog_rss": "https://competitor-a.com/blog/rss",
"github": "competitor-a/product",
"keywords": ["竞品A", "CompetitorA"]
}
]
}
EOF
输出规范
- 报告简洁,聚焦「变化」和「行动建议」
- 区分事实(客观变化)和分析(主观判断)
- 注明信息来源和时间
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.
- 7d ago First seen · 124 lines · 22 tokens per session scan C dba150ff2d20
competitive-intel is a skill published in the GitHub repository malue-ai/dazee-small (36 stars, last pushed 5mo ago), licensed MIT. It adds 22 tokens to every session and 855 once invoked, about $0.0001 per session on Opus 5. A static security scan graded it C with 2 findings (downloads and executes remote code, makes network calls). No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-31.
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