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 taoma888/awesome-ai-skills --skill content-autopilotgit clone --depth 1 https://github.com/taoma888/awesome-ai-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/taoma888/awesome-ai-skills/content-autopilot)<a href="https://agentmods.dev/skills/taoma888/awesome-ai-skills/content-autopilot"><img src="https://agentmods.dev/badge/skills/taoma888/awesome-ai-skills/content-autopilot/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/taoma888/awesome-ai-skills/content-autopilot"><img src="https://agentmods.dev/badge/skills/taoma888/awesome-ai-skills/content-autopilot.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 | $0.00000 | $0.00705 |
| Opus 5 | $0.00000 | $0.00352 |
| Sonnet 5 | $0.00000 | $0.00141 |
| Haiku 4.5 | $0.00000 | $0.00071 |
Grade A, and why
content-autopilot 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
🚗 内容自动驾驶 — Content Autopilot
全自动：热点发现 → AI改写 → 去AI化 → 多平台适配 → 自动发布 → 数据追踪
触发条件
用户说：写文章、创作、内容、更新文章、自动发布、
热点蹭热度、伪原创、改写、AI写作
核心流水线（7步）
Step 1: 热点发现 → 抓取微博/知乎/微信/B站热搜
Step 2: 内容规划 → 生成5W1H大纲
Step 3: 素材搜集 → 抓取权威来源（TechCrunch/机器之心等）
Step 4: AI改写 → 低查重率伪原创（<40%）
Step 5: 去AI化处理 → 口语化+情绪词+设问互动
Step 6: 多平台适配 → 公众号/微博/知乎格式
Step 7: 自动发布 → 写入D1 / 发布到平台
改写标准（必须遵守）
| 指标 | 要求 |
|---|---|
| 查重率 | < 40%（用句式变化而非词替换） |
| AI感 | 去除"首先、其次、因此、综上所述" |
| 情绪词 | 加"说实话、我个人、没想到、真的太" |
| 互动 | 加"你们觉得呢？评论区告诉我！" |
| 字数 | 800-2000字 |
| 配图 | Unsplash CC0 图片一张 |
| 格式 | 公众号格式：emoji + 分割线 + 加粗 |
| 原创标识 | 每篇文章末尾加"原创 by AI" |
使用示例
# 获取今日热点
python scripts/fetch_trending.py --platforms weibo,zhihu --limit 10
# 改写文章
python scripts/article_rewriter.py --topic "Claude 4发布" --length 1200
# 一键发布到D1
python scripts/auto_publisher.py --article "output/claude4_rewrite.md" --platforms d1,weixin
脚本说明
fetch_trending.py
抓取多平台热搜，支持：
- 微博热搜 TOP50
- 知乎热榜 TOP20
- 微信热文（搜一搜）
- 百度指数飙升
- Google Trends
article_rewriter.py
AI改写核心引擎：
- 输入：原始文章URL或关键词
- 输出：改写后文章（Markdown格式）
- 去AI化处理（口语化/情绪化）
auto_publisher.py
多平台自动发布：
- D1数据库（直接写入）
- 微信公众号（API发布）
- 知乎专栏
- 微博长文
配置
export D1_DATABASE_ID="xxx"
export CF_ACCOUNT_ID="xxx"
export CF_API_TOKEN="xxx"
export AI_MODEL="qwen3.5-plus" # 阿里云百炼
What ships with it
3 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.
- 12d ago First seen · 93 lines · 0 tokens per session scan A 2f4a7c80777e
content-autopilot is a skill published in the GitHub repository taoma888/awesome-ai-skills (5 stars, last pushed 4mo ago), licensed MIT. It costs nothing until one of its globs matches a file; then it loads 705 tokens. 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 2026-08-31.
Other skills, from other repositories
systematic-debugging
Use when encountering any bug, test failure, or unexpected behavior, before proposing fixes.
local-ai-agents
Build local-first AI agents that run entirely on a developer workstation with Microsoft Foundry Local and Qwen function-calling models. Covers Small Language Models (SLMs), the OpenAI-compatible local endpoint, sandboxed local tools, local RAG with Chroma, local MCP servers, hybrid cloud/local routing, and the…
next-cache-components-adoption
Turn on Cache Components in a Next.js app and resolve the blocking routes it surfaces. Use when the user wants to enable, adopt, or migrate to Cache Components, flip the cacheComponents flag, work through a flood of blocking-prerender / instant validation errors, run the cache-components-instant-false codemod, or…
chat-pet-sprite-creation
Use when creating or changing VS Code chat pet sprite art, sprite sheets, state animations, eye treatments, Stable/Insiders variants, or pet transitions under src/vs/workbench/contrib/chat/browser/widget/media/chatPet.
cpu-profile-analysis
Analyze V8/Chrome CPU profiles (.cpuprofile) and DevTools trace files (Trace-.json). Use when: profiling performance, investigating slow functions, comparing code paths, finding bottlenecks, analyzing timeToRequest, understanding call trees from sampling profiler data, analyzing layout/paint/rendering, investigating…
insight-error-page
Write or audit an insight-kind error page for the Next.js dev overlay. Use when creating a new errors/ .mdx page, auditing an existing one, or checking that a page matches the framework fix cards. Covers page structure, title alignment, FixCard cards with Copy prompt button, code snippets, terminology verification…