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-covergit 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-cover)<a href="https://agentmods.dev/skills/redfox-data/redfox-community-dsh/wechat-cover"><img src="https://agentmods.dev/badge/skills/redfox-data/redfox-community-dsh/wechat-cover/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-cover"><img src="https://agentmods.dev/badge/skills/redfox-data/redfox-community-dsh/wechat-cover.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 | $0.00110 | $0.02213 |
| Opus 5 | $0.00055 | $0.01107 |
| Sonnet 5 | $0.00022 | $0.00443 |
| Haiku 4.5 | $0.00011 | $0.00221 |
Grade A, and why
wechat-cover 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 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.
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 — 176 lines — stays where its author put it; the contents beside it link to each section on GitHub.
公众号封面图制作
📋 概述
基于全网每日收录的爆款文章数据，获取同赛道爆款封面的视觉元素，通过AI分析总结高转化视觉规律，生成贴合文章内容、符合平台流量审美的封面设计方案（含案例+生图提示词）。仅在主Agent中执行，不派发给子Agent。
🎯 触发规则
| 场景 | 处理方式 |
|---|---|
| 用户提供内容主题/赛道 | 执行任务流程 |
| 用户要求生成封面方案 | 执行任务流程 |
| 用户上传文案或图片要求分析 | 执行任务流程 |
| 用户询问技能功能/用法 | 仅介绍技能 |
| 用户未提供明确创作主题 | 仅介绍技能 |
📝 术语规范
统一使用"爆款封面"，禁止使用：爆炸封面→爆款封面、爆炸数据→爆款数据、抓取数据→获取/查询数据、抓取封面→获取封面。
🔒 数据来源
所有爆款数据必须来自接口，禁止联网搜索、使用其他数据源或脑补数据。数据不足时明确告知用户。
🔑 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..."
⚙️ 前置准备
- 依赖：
requests（pip install requests） - 凭证：环境变量
REDFOX_API_KEY（详见鉴权章节） - 数据范围：仅含昨天至30天前的数据，默认查询近30天
🔄 操作流程
步骤1：意图解析
结构化解析用户需求，提取4个维度：
| 维度 | 说明 | 示例 |
|---|---|---|
| 内容主题 | 优先领域词 | 护肤、穿搭、美食、职场 |
| 内容类型 | 内容形式 | 干货、测评、种草、教程 |
| 风格偏好 | 视觉/调性 | 专业、吸引点击、情绪、极简 |
| 核心关键词 | 搜索关键词 | 秋冬、美白、护肤、干皮 |
提取2-5个核心关键词（逗号分隔），优先细分领域词，结合风格偏好补充场景词。
步骤2：爆款数据查询
# 有赛道关键词
python3 scripts/fetch_explosive_covers.py --keyword <关键词1,关键词2,关键词3>
# 无赛道关键词
python3 scripts/fetch_explosive_covers.py --keyword ""
- 最多5个关键词，总长度≤200字符
- 关键词整体一次传入接口，不做拆分循环调用
- 时间参数默认不传（接口自行决定默认范围）；用户指定"近N天"时 startDate = 今天 - (N-1)天
步骤3：智能匹配筛选
| 数据量 | 处理 |
|---|---|
| ≥20条 | 直接使用 |
| <20条 | 扩展关键词（如：美白→美白、护肤、美白祛斑），重新查询，合并数据 |
筛选规则：按阅读数从高到低排序，取前20条。关键词扩展最多1-2次，每次2-3个相似词。
步骤4：AI图像分析与特征提取
- 解析脚本返回的JSON数据（含
articles文章数组，以及latestHotArticles、hotTopics、relatedSearches辅助数据） - 提取
imageUrl字段合并为封面候选池——直接使用原始值，不做任何修改（新接口字段名为imageUrl，旧接口为coverUrl，脚本已做兑容） - 按互动量从高到低取前20条
- 逐张分析封面图（使用原生图片理解能力，直接访问 imageUrl）
7维度分析：
| 维度 | 分析内容 |
|---|---|
| 文字内容 | 是否有文字、内容、字体大小、位置、颜色、醒目程度 |
| 主体元素 | 人物/产品/场景/图案等主要视觉元素 |
| 色彩特征 | 主色调、配色方案、对比度、冷暖色调 |
| 构图布局 | 画面结构、元素分布、主体位置、留白处理 |
| 视觉风格 | 实拍/插画/拼贴/极简/炫酷等风格类型 |
| 点击吸引力 | 痛点/好奇/美感/实用——为什么吸引点击 |
| 尺寸检测 | 宽x高，是否合格（≥10px） |
What ships with it
6 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.
- 7d ago First seen · 176 lines · 110 tokens per session scan A c0927ba6f936
wechat-cover is a skill published in the GitHub repository redfox-data/redfox-community-dsh (5 stars, last pushed today), licensed MIT. It adds 110 tokens to every session and 2,213 once invoked, about $0.0006 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 2026-09-03.
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