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 hanzhcn/laohan-skills --skill laohan-rediangit clone --depth 1 https://github.com/hanzhcn/laohan-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/hanzhcn/laohan-skills/laohan-redian)<a href="https://agentmods.dev/skills/hanzhcn/laohan-skills/laohan-redian"><img src="https://agentmods.dev/badge/skills/hanzhcn/laohan-skills/laohan-redian/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/hanzhcn/laohan-skills/laohan-redian"><img src="https://agentmods.dev/badge/skills/hanzhcn/laohan-skills/laohan-redian.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector pass
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 | $0.00123 | $0.04429 |
| Opus 5 | $0.00062 | $0.02214 |
| Sonnet 5 | $0.00025 | $0.00886 |
| Haiku 4.5 | $0.00012 | $0.00443 |
Grade A, and why
laohan-redian 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 — 174 lines — stays where its author put it; the contents beside it link to each section on GitHub.
①选题决策
热点只用于发现，最终结果是一个可审计的生产决策：为什么现在做、给谁看、论点凭什么成立、抖音上有哪些重复角度、为什么淘汰其他候选，以及发布后如何按固定窗口复盘。
边界
- 本 skill 是①唯一主写者，写 signals、candidates、source-health 和
00-选题.*。 laohan-douyinsousuo只写00-抖音搜索证据.{json,md}；同一 Agent 宿主按 bianpai 路由执行，不做 programmatic skill-to-skill 调用。- ②才写口播稿；①不生成正文、大纲段落或封面。
- ⑤才做完整事实核验；①仍须给最终事实前提找到至少一条 PRIMARY 原始来源。
- 不安装新浏览器、爬虫、Python runtime 或第三方 skill。抖音平台访问只用已安装 OpenCLI。
- 同一事件可以形成观点候选和教程候选；受众任务、标题承诺和内容路径真正不同时可分别参加比较。②—④沿用选中 lane，不混写。
输入
Episode 模式必须读取：
- 本期
episode-config.json与00-编排/冻结产物。 - 本期已显式登记的反馈快照；没有就记录
NOT_AVAILABLE，不得扫描旧 episode 猜经验。 - 本轮真实 signals 与抖音搜索证据。
标准 Episode 固定为 REVIEW_GATED：AI自主完成发现与候选，但不得替Jeffrey选中。Jeffrey 明确给题时走 USER_SEED，仍须给出至少一个真实替代候选、抖音取证、PRIMARY 证据和测量合同；最终同样经过情绪与表达欲筛选。
Jeffrey给出的是软件、方法或系列方向时，先走USER_DIRECTION_RESEARCH：读取项目docs/系列选题研究与分期规格.md，完成四平台定向搜索、内容级拆解、需求判断、系列分期和单期资料包。它不运行与方向无关的9账号泛扫描来凑热度。只有DEMAND_VALIDATED可进入三期以上系列，EXPERIMENTAL_ONE_OFF只进入单期，DIRECTION_REJECTED停止。正式episode仍须提供替代候选并经过Jeffrey情绪筛选。
工作流
1. 采集当前信号
先写00-选题-signals.json.discovery_mode：无方向为AUTONOMOUS_SCAN；Jeffrey已给方向为USER_DIRECTION_RESEARCH。后者把已通过node scripts/check-series-research.mjs的series_research_path与SHA写入direction_research，并把哔哩哔哩、小红书、抖音、知乎四路结果分别登记为signals来源。DEMAND_VALIDATED至少两个平台有真实需求信号；EXPERIMENTAL_ONE_OFF只按研究包内已验证的官方新事件、Jeffrey亲历或小众任务依据进入单期，不强制伪造两个平台热度。
Episode 模式执行唯一确定性入口：
node ~/Documents/laohan-skills/laohan-redian/scripts/collect-topic-signals.mjs \
--episode episodes/<slug>
AUTONOMOUS_SCAN候选源固定为三条线：9个登记抖音对标账号逐账号近期扫描、全面热点扫描、script-pool/Jeffrey个人表达池.md。默认发现与展示优先级为BENCHMARK_CREATOR(1) > BROAD_HOTSPOT(2) > PERSONAL_EXPRESSION(3)；这是找题效率顺序，不是自动入选分数，个人题仍可在获得公共兴趣证据后胜出。全面热点默认 route 为 AIHOT、Hacker News、知乎、微博、36kr、B站、抖音热榜、头条、贴吧和虎扑；某一路失败如实记录，其他热点路继续，但9个对标账号任一失败都停止候选生成，正常空结果记EMPTY且算完成。需要缩小热点route时才传 --sources，不能借此跳过对标账号和个人池。
脚本只写：
00-选题-signals.json- 初始
00-选题-source-health.json
脚本不选题、不访问旧 episode、不调用 douyin-ai.js。
2. 标准化、去重、形成候选
读取 signals，按稳定 signal id 聚类同一事实事件；排除同 URL/同承诺/同路径的重复表达。对标账号只提炼母题、公众需求和异常信号，不复制标题、文案、案例或结论。同一事件只有在“帮观众作判断”和“带观众完成任务”分别成立时才生成两个形态。写 schema 3 00-选题-candidates.json，先用顶层 screening_summary 留下筛选链路，再写至少两个真正不同的短名单候选。screening_summary 只包含：
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.
- 11d ago First seen · 174 lines · 123 tokens per session scan A e355678ccdf1
laohan-redian is a skill published in the GitHub repository hanzhcn/laohan-skills (11 stars, last pushed today), licensed MIT. It adds 123 tokens to every session and 4,429 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 2026-08-30.
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