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 LiHongwei-cn/lihongwei-cn --skill cheat-trendsgit clone --depth 1 https://github.com/LiHongwei-cn/lihongwei-cnWrote 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/lihongwei-cn/lihongwei-cn/cheat-trends)<a href="https://agentmods.dev/skills/lihongwei-cn/lihongwei-cn/cheat-trends"><img src="https://agentmods.dev/badge/skills/lihongwei-cn/lihongwei-cn/cheat-trends/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/lihongwei-cn/lihongwei-cn/cheat-trends"><img src="https://agentmods.dev/badge/skills/lihongwei-cn/lihongwei-cn/cheat-trends.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 | $0.02606 |
| Opus 5 | $0.00000 | $0.01303 |
| Sonnet 5 | $0.00000 | $0.00521 |
| Haiku 4.5 | $0.00000 | $0.00261 |
Grade A, and why
cheat-trends 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 11d 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 — 204 lines — stays where its author put it; the contents beside it link to each section on GitHub.
/cheat-trends — 热点抓取
多 adapter 模式：读各 trend-sources adapter 的输出 → 去重 → 粗打分 → 写入 candidates.md。
Overview
[用户：抓热点]
↓
[Phase 0: 读 .cheat-state.json 拿 enabled adapters]
↓
[Phase 1: 对每个 adapter 调 fetch]
↓
[Phase 2: normalize 到 candidate-schema]
↓
[Phase 3: 去重（vs candidates / predictions / trends-history）]
↓
[Phase 4: 对每个新 item 粗打分（调 cheat-score 内联逻辑）]
↓
[Phase 5: 排序 + 询问用户哪些加入 candidates.md]
↓
[Phase 6: 写入 + 更新 trends-history.jsonl 缓存]
Constants
- TREND_SOURCES = ["manual-paste"] — 启用的 adapter 列表（默认仅 manual-paste，最稳）
- LOOKBACK_HOURS = 24 — 抓最近 N 小时的热点
- MAX_PER_SOURCE = 20 — 每个 adapter 最多 N 条
- DEDUPE = true — 去重开关
- AUTO_SCORE = true — 抓回来后自动调 cheat-score 粗打分
- MIN_COMPOSITE_TO_SUGGEST = 6.0 — 低于此分的不推荐用户加入候选池（仍写入 trends-history 避免下次重复推）
💡 调用时覆盖：
/cheat-trends — sources: manual-paste,hackernews,bilibili-popular — max-per: 10
Inputs
| 必填 | 来源 |
|---|---|
.cheat-state.json |
默认 sources |
adapters/trend-sources/<name>.md |
各 adapter 的实现描述 |
candidates.md |
去重对照 |
predictions/*.md |
去重对照（已发的不再推） |
.cheat-cache/trends-history.jsonl |
历史抓取去重缓存 |
Workflow
Phase 0: 读启用的 adapters
# 伪代码
state = read('.cheat-state.json')
enabled_adapters = args.sources or state.get('enabled_trend_sources', ['manual-paste'])
如 enabled_adapters 为空 → 输出引导：
你目前没有启用任何热点源。
最快配法：
- 临时跑：/cheat-trends — sources: manual-paste,hackernews
- 永久启用：编辑 .cheat-state.json 的 enabled_trend_sources 数组
可用 adapter（详见 adapters/trend-sources/）：
- manual-paste（默认，永远能用）
- hackernews（HN Algolia API，无需 key）
- reddit-rising（公开 .json 端点）
- youtube-trending（需 YouTube Data API key）
- bilibili-popular（公开端点，偶有变动）
- xhs-explore / douyin-hot（fragile，需 cookie）
- thirdparty-paid（新榜 / 飞瓜，需自己接 API）
Phase 1-2: 对每个 adapter 调 fetch + normalize
对每个 adapter，读其 adapters/trend-sources/<name>.md 中描述的 fetch 接口（实际是 Bash 调底层 Python / shell / WebFetch）：
| Adapter | 实现机制 |
|---|---|
manual-paste |
询问用户："粘贴你今天的候选 URL/标题列表（每行一条）" → 解析每行，对 URL 做 WebFetch 拓展 snippet |
hackernews |
WebFetch HN Algolia API：https://hn.algolia.com/api/v1/search?tags=front_page&hitsPerPage={N} → 提取 title/url/snippet |
reddit-rising |
WebFetch Reddit JSON：https://www.reddit.com/r/<subreddit>/rising.json?limit={N} |
youtube-trending |
需 API key 配置在 .env 或 .cheat-state.json，调 YouTube Data API v3 videos?chart=mostPopular |
bilibili-popular |
WebFetch B 站 popular 接口 |
xhs-explore / douyin-hot |
需用户提供 cookie 路径，调对应 platform-stub 描述的接口；缺 cookie → skip 该 adapter |
thirdparty-paid |
schema only——读 adapters/trend-sources/thirdparty-paid.md，让用户自己接 |
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.
- 11d ago First seen · 204 lines · 0 tokens per session scan A c381ba986580
cheat-trends is a skill published in the GitHub repository LiHongwei-cn/lihongwei-cn (5 stars, last pushed 1mo ago), licensed MIT. It costs nothing until one of its globs matches a file; then it loads 2,606 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.
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