laohan-yunying

laohan-yunying is a skill for Claude Code, Codex from hanzhcn/laohan-skills. It costs 75 tokens per session (2,397 once invoked), scanned A, original, MIT.

A Chinese-language workflow for recording manually published Douyin posts and collecting their performance data and comments. Douyin is a Chinese short-video platform; this workflow does not publish videos or control the browser.

In plain words
What is it for?
Use it after a confirmed Douyin or other platform publication to register its URL, platform title, time, and file identity, then collect data and comment evidence for content review. Automatic records must contain the required publication and authorization details.
Why use it?
It keeps publishing evidence separate from later analytics and review, so the system does not treat a click or an unverified page as proof that a post was published.

Skill for Claude CodeCodex

Written for no agent in particular: nothing here depends on one.

Good fit Use it after a confirmed Douyin or other platform publication to register its URL, platform title, time, and file identity, then collect data and comment evidence for content review. Automatic records must contain the required publication and authorization details.

Compare 6 skills from other repositories ↓
Install with agentmods
npx agentmods add skills/hanzhcn/laohan-skills/laohan-yunying
Install

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.

Any agent
npx skills add hanzhcn/laohan-skills --skill laohan-yunying
Clone the repo
git clone --depth 1 https://github.com/hanzhcn/laohan-skills

Made for: Claude Code, Codex.

Wrote 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.

agentmods badge for laohan-yunying

README.md
[![agentmods](https://agentmods.dev/badge/skills/hanzhcn/laohan-skills/laohan-yunying/github.svg)](https://agentmods.dev/skills/hanzhcn/laohan-skills/laohan-yunying)
Your own site
<a href="https://agentmods.dev/skills/hanzhcn/laohan-skills/laohan-yunying"><img src="https://agentmods.dev/badge/skills/hanzhcn/laohan-skills/laohan-yunying/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.

agentmods 80×15 button for laohan-yunying

Your own site · 80×15
<a href="https://agentmods.dev/skills/hanzhcn/laohan-skills/laohan-yunying"><img src="https://agentmods.dev/badge/skills/hanzhcn/laohan-skills/laohan-yunying.svg" alt="Reviewed on agentmods" width="80" height="20"></a>
Per session 75 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 2,397 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. A grade says what 26 rules found in the file — not that it is safe. Third-party audits
  • NVIDIA SkillSpector pass 7 Sept 2026
How audits are shown
Origin original No closer match found in the catalogue.
Token cost

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.

ModelPer sessionOnce invoked
Fable 5.1 $0.00075 $0.02397
Opus 5 $0.00037 $0.01198
Sonnet 5 $0.00015 $0.00479
Haiku 4.5 $0.00007 $0.00240

Measured 11d ago against content hash 8476133e7a4e, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-11, from the pricing page.

Security

Grade A, and why

laohan-yunying 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.

The scan reads SKILL.md. This mod also ships 1 executable file (scripts/tzfilm_douyin_adapter.py), listed below but not scanned — reading those needs a real analyzer, not pattern matching.

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.

laohan-yunying/SKILL.md · 91 lines

How it starts

The opening of the file, as written. The whole thing — 91 lines — stays where its author put it; the contents beside it link to each section on GitHub.

抖音数据与评论编排器

本 skill 不发布、不准备发布文案、不代替 Jeffrey 点击平台。它只登记人工确认或本机Chrome适配器已经验证的发布事实,保存数据和评论证据;cheat-on-content 是预测与复盘引擎。

工作流

1. 发布事实登记

先运行 bianpai check --require final,再登记以下两种发布证据来源:

  • USER_CONFIRMED_MANUAL:当前唯一人工发布 source,沿用publish-record.json。Jeffrey 在平台手动发布后提供平台身份、URL(抖音还须aweme_id)与平台显示的精确标题platform_title。历史source: "user-confirmed"仅允许schema <4 episode只读兼容;迁移或新登记必须写USER_CONFIRMED_MANUAL
  • ADAPTER_VERIFIED_RECEIPT:读取12-发布/*-publish-results.jsonl中与当前final.mp4 SHA匹配的最后一个PUBLISHED记录;自动回执的 canonical source 固定为 source: ADAPTER_VERIFIED_RECEIPT,缺失或为其他值都不得登记。

归一化登记记录必须保留platformsourcereceipt_id|urlpublished_atfinal_sha256platform_titleADAPTER_VERIFIED_RECEIPT读取每个平台完整JSONL后,从后向前选择首条同时匹配该平台、当前final SHA、publish_result: PUBLISHEDsource精确为ADAPTER_VERIFIED_RECEIPT的合法回执;后续FAILED或其他final记录不得遮蔽它。回执还必须绑定authorized_byauthorized_atauthorization_notebound_input_record_sha256,并与本期FULL_PIPELINE_TO_PUBLISH授权完全一致;published_atrecorded_at必须是有效时间且不得早于授权。缺少任何绑定字段就停,不能编造。

⑫只消费上述归一化登记;原始JSONL行、浏览器页面或“点击过”都不是完成证据。

本Skill不得承担发布点击、上传、表单填写或浏览器控制;这些只属于release package与本机Chrome适配器。自动发布回执只证明对应平台已发布,不证明该平台运营数据已经接通。

2. 人工发布记录

USER_CONFIRMED_MANUAL只登记 Jeffrey 提供的作品 URL、aweme_id 与 platform_title;不调用 URL 解析、平台浏览器、发布 adapter 或任何替代发布工具。URL 必须包含同一 aweme_id;缺任一身份字段则停,不能编造。ADAPTER_VERIFIED_RECEIPT只读取既有回执,不调用或驱动发布 adapter。

12-发布/publish-record.json

{
  "platform": "douyin",
  "status": "PUBLISHED",
  "url": "https://www.douyin.com/video/<aweme_id>",
  "aweme_id": "<id>",
  "platform_title": "平台显示的精确作品标题",
  "published_at": "2026-07-10T20:00:00+08:00",
  "final_path": "07-剪辑/final.mp4",
  "final_sha256": "当前 final.mp4 的 SHA-256",
  "source": "USER_CONFIRMED_MANUAL"
}

然后调用上游 cheat-publish 登记同一 URL;只更新预测 metadata,绝不修改预测段。完成后运行 node scripts/register-cheat-publish-evidence.mjs episodes/<slug>,保存 publish 时点的 lane state 快照并验证 prediction header、URL、aweme_id、发布时间和不可变预测段;缺该证据时⑫不得完成。

发布后首屏截图或创作者中心导出是可选强证据,不能代替 Jeffrey 的发布事实,也不因缺失阻断⑫。若保存,证据文件必须在本期 12-发布/,并写 platform-display-evidence.jsonschema_version: 1、evidence_path/SHA、aweme_id、platform_title、display_title、cover_asset/SHA、final_sha256、title/cover/video 三项 MATCHED 结论、reviewer、captured_at、reviewed_at。任一项与当前 publish-record、selected-cover 或 final 不一致时,⑫必须显示未完成,直到删去该可选证据或重做核对;不得自动修正或伪造截图。

Read the full file on GitHub · 91 lines

Files

What ships with it

1 file 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.

Changes

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.

  1. 11d ago First seen · 91 lines · 75 tokens per session scan A 8476133e7a4e

Subscribe to this mod's changes

laohan-yunying is a skill published in the GitHub repository hanzhcn/laohan-skills (11 stars, last pushed today), licensed MIT. It adds 75 tokens to every session and 2,397 once invoked, about $0.0004 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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