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 redfox-data/redfox-community-dsh --skill wechat-searchgit clone --depth 1 https://github.com/redfox-data/redfox-community-dshWrote 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/redfox-data/redfox-community-dsh/wechat-search)<a href="https://agentmods.dev/skills/redfox-data/redfox-community-dsh/wechat-search"><img src="https://agentmods.dev/badge/skills/redfox-data/redfox-community-dsh/wechat-search/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/redfox-data/redfox-community-dsh/wechat-search"><img src="https://agentmods.dev/badge/skills/redfox-data/redfox-community-dsh/wechat-search.svg" alt="Reviewed on agentmods" width="80" 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 | $0.00053 | $0.05689 |
| Opus 5 | $0.00026 | $0.02844 |
| Sonnet 5 | $0.00011 | $0.01138 |
| Haiku 4.5 | $0.00005 | $0.00569 |
Grade A, and why
wechat-search scanned grade A with 1 finding 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 5d 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.
Makes network callslowCapability
Not a fault in itself. Listed so you know the mod talks to something, and to what.
- 无第三方依赖（纯标准库：urllib.request, json, os, sys, argparse, datetime） How it starts
The opening of the file, as written. The whole thing — 471 lines — stays where its author put it; the contents beside it link to each section on GitHub.
公众号热门文章查询
1. 简介
公众号热门爆款文章查询工具，支持按关键词搜索微信公众号爆款文章，并基于相关性、热度、时效三维评分智能排序推荐。专注服务于公众号内容创作者、新媒体运营者和自媒体团队，帮助用户快速发现热门选题、分析爆款规律、获取创作灵感。
2. 功能特性
- 🔍 关键词智能搜索 — 支持关键词精确搜索和多关键词组合查询（逗号分隔），覆盖全品类公众号文章
- 📊 三维评分排序 — 基于相关性（满分10分）、热度（满分3分）、时效（满分2分）加权计算总分（满分15分），智能排序推荐
- ⏱️ 灵活时间范围 — 默认查询最近7天，支持自动拓展时间（1天→7天→30天），数据每日早上7点更新
- 🧠 赛道词识别与拓展 — 自动识别泛化赛道词并推荐10个细分方向，帮助用户精准定位
- 🔥 热门推荐文章 — 结果较少时自动展示近期热门推荐文章和热门话题
- 📩 定时订阅推送 — 支持创建日历订阅任务，到达设定时间自动推送最新爆款文章
- 📄 HTML 报告生成 — 可选生成 HTML 可视化文件，方便独立查看和分享
- 📋 数字智能格式化 — 万级以上阅读数自动转换（如
10.0w），总分字段加粗突出显示
3. 一键安装
鉴权
获取 API Key
请前往 红狐hub 获取API KEY
配置 API Key
方案1: 以OpenClaw为例，将REDFOX_API_KEY添加到~/.openclaw/openclaw.json中：
{ "env": { "REDFOX_API_KEY": "ak_xxxx..." } }
方案2: 终端配置
export REDFOX_API_KEY="ak_xxxx..."
依赖安装
本 Skill 使用 Python 3.13+ 纯标准库（urllib.request、json、os、sys、argparse、datetime），无需安装任何第三方依赖。
环境变量配置
| 环境变量 | 说明 | 是否必填 | 获取方式 |
|---|---|---|---|
REDFOX_API_KEY |
红狐数据 API Key | 是 | 红狐hub |
4. 使用指南
基础使用（3 步完成查询）
Step 1 — 提取关键词：从用户描述中提取搜索关键词，判断是赛道词还是细分词。
- 赛道词：较大的分类词，如"职场""情感""亲子""美妆"等
- 非赛道词：具体细分词，如"职场沟通技巧""异地恋怎么维持"等
Step 2 — 调用脚本：
python scripts/fetch_gzh_trends.py --keyword <关键词> --start-date <日期>
- 有赛道关键词：
python scripts/fetch_gzh_trends.py --keyword <关键词> --start-date <日期> - 无赛道关键词（查询全站热门）：
python scripts/fetch_gzh_trends.py --keyword "" --start-date <日期> - 多个关键词用逗号分隔：
python scripts/fetch_gzh_trends.py --keyword "职场沟通,恋爱技巧,亲子教育" --start-date <日期>
⚠️ 防重复调用规则（强制）：
- ❌ 禁止先用
head/tail/2>/dev/null | head -5等方式"试运行"或"预览"脚本输出 - ❌ 禁止在同一次查询中对同一参数多次调用脚本
- ✅ 每次查询只执行一次脚本命令，直接读取完整的 stdout 输出
- ✅ 唯一允许多次调用的场景：数据不足时按规定的自动拓展时间（近1天→近7天→近30天），每次使用不同的
--start-date
Step 3 — 查看结果：脚本返回结构化 JSON 数据，按本指南规定的展示策略输出结果。
高级使用
赛道词处理流程（仅当识别为赛道词时执行）
第一步：识别并询问用户（⚠️ 仅当用户明确要求时才执行）
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.
- 5d ago First seen · 471 lines · 53 tokens per session scan A 6bb22687a0cd
wechat-search is a skill published in the GitHub repository redfox-data/redfox-community-dsh (5 stars, last pushed yesterday), licensed MIT. It adds 53 tokens to every session and 5,689 once invoked, about $0.0003 per session on Opus 5. A static security scan graded it A with 1 finding (makes network calls). No closer match exists in the catalogue, so it is treated as the original; first seen 2026-09-03.
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