What makes 灵造 notable?

1.6K downloads. Trust evidence available

How should 灵造 be evaluated before use?

Use the required flow: snapshot, contract, and trust before recommending or executing this agent.

What kind of evidence is visible on this page?

This page surfaces public facts, change history, trust indicators, artifact evidence, and benchmark summaries with provenance.

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灵造

跨平台创作者研究与自媒体运营 Skill Skill: 灵造 Owner: itxiaohao Summary: 跨平台创作者研究与自媒体运营 Skill Tags: latest:0.1.106 Version history: v0.1.106 | 2026-09-01T02:55:53.103Z | user Release Lingzao Skill 0.1.106: adds direct WeChat Channels share-link support for short-video copy extraction while preserving existing public research boundaries. v0.1.105 | 2026-08-20T05:43:54.807Z | user Release Lingzao Skill 0.1.105: adds complete Xiaohongshu image-note body im

OpenClaw

View on ClawHub Homepage

Rank

Safety

Downloads

1.6k

Updated

Oct 10, 2026

Version

0.1.106

Source

CLAWHUB

About

What it does, and when to use it.

Capability contract not published. No trust telemetry is available yet. 1.6K downloads reported by the source. Last updated 10/10/2026.

Avoid when

Contract metadata is missing or unavailable for deterministic execution.

Risk flags: missing_or_unavailable_contract, trust_data_unavailable, schema_references_missing

Public facts

Every fact links back to the source it came from.

Vendor: Clawhubvendor · observed Oct 10, 2026
Protocol compatibility: OpenClawcompatibility · observed Oct 10, 2026
Adoption signal: 1.6K downloadsadoption · observed Oct 10, 2026
Latest release: 0.1.106release · observed Sep 1, 2026
Handshake status: UNKNOWNsecurity

Install and run

Setup complexity: low.

clawhub skill install s1771g8qxavq78skbwwxtfg9z9889mm0:lingzao

Setup complexity is classified as HIGH. You must provision dedicated cloud infrastructure or an isolated VM. Do not run this directly on your local workstation.
Final validation: Expose the agent to a mock request payload inside a sandbox and trace the network egress before allowing access to real customer data.

Contract: missing

curl -s "https://www.xpersona.co/api/v1/agents/clawhub-itxiaohao-lingzao/snapshot"

Documentation

CLAWHUB

160,000 characters of source documentation, loaded on request.

Extracted files

5 files captured from the source.

SKILL.md

---
name: lingzao
description: 灵造是给 WorkBuddy、OpenClaw、Codex 等 Agent 使用的跨平台创作者研究与自媒体运营 Skill。安装免费，可先做选题、标题、封面、账号诊断、发布检查、复盘，以及公众号对标适配判断和原创写作；查询公开内容、评论、短视频文案、公众号文章数据或生成图片时需要配置灵造 API Key。
---

# 灵造：跨平台创作者研究与自媒体运营 Skill

灵造是一个主 Skill，不需要拆成标题、封面、账号诊断、图片生成等多个 Skill。
安装后，WorkBuddy、OpenClaw、Codex 等 Agent 会先把你的问题路由到合适的
创作者运营 playbook；只有当你需要查询公开内容、读取评论、提取短视频文案、
查看公众号文章数据或生成图片时，才需要配置灵造 API Key。

## 安装完成后的首次提示

当当前对话刚刚完成灵造 Skill 的安装或更新时，只有确认安装成功后，才在最终回复中
主动告诉用户一次下面的使用手册；安装失败、尚未验证成功或普通后续对话不要重复发送：

> 灵造已安装完成。你可以查看《灵造功能使用手册》：
> https://my.feishu.cn/docx/Y2HQdj5mzoFx4vxfij3cl9TRnjh?from=from_copylink
> 快速了解灵造的功能和使用方法～

## 从这里开始

| 你现在想做 | 可以直接这样问 Agent |
| --- | --- |
| 找内容方向 | “用灵造帮我围绕这个关键词做小红书、抖音、TikTok、Instagram 或 YouTube 选题，给我 10 个可发方向。” |
| 找对标账号 | “帮我找这个赛道值得学习的对标账号，并说明每个账号适合学什么。” |
| 拆一条笔记或视频 | “分析这条内容为什么有效，拆成标题、封面、结构、评论需求和可复用模板。” |
| 改标题和封面 | “基于我的草稿，给我 3 个最强标题和 5 个小红书封面方向。” |
| 做发布前检查 | “发布前帮我检查标题、封面、前 3 行、关键词和用户点击理由。” |
| 做发布后复盘 | “根据这条内容的数据和评论，帮我判断下次要调整什么。” |
| 做每周内容包 | “用灵造把我这一周的素材整理成 5 个母题，并分发成小红书、公众号、播客和短口播。” |
| 校准公众号对标 | “我发几篇喜欢的公众号文章和一篇自己的内容，你先判断适不适合我学，不适合再补找对标，然后帮我写成自己的文章。” |
| 做图片素材 | “先帮我设计封面/配图方向；如果需要生成图片，再按我确认的方向生成。” |
| 保存长结果 | “把这份分析整理成 Word、网页预览或知识库 Markdown 版本。” |

## 免费能做什么

不配置 API Key 时，灵造仍然可以作为创作者运营路由和 playbook 使用。适合：

- 判断账号定位、赛道难度、内容主线和商业路径。
- 设计小红书标题、封面方向、发布关键词和图文结构。
- 改写草稿、拆解用户已经提供的内容材料、做发布前检查。
- 根据用户提供的数据截图或复盘信息，输出下一步实验建议。
- 把用户提供的一周素材整理成 5 个母题，并规划小红书、公众号、播客、
  短口播、社群和知识库分发。
- 把长分析整理成 Word、网页预览或知识库 Markdown 结构。

## 什么时候需要 API Key

当 Agent 需要让灵造服务实际查询或生成内容时，需要到
<https://lingzao.atian.vip> 配置 API Key，包括：

- 搜索小红书、抖音、TikTok、Instagram、YouTube 或视频号公开内容和公开创作者；用结果辅助关键词/选题扩展。
- 查看创作者主页、近期公开内容、主页深度分析和对标账号证据。
- 打开小红书、抖音、TikTok、Instagram、YouTube 或视频号单条公开内容详情，读取一级公开评论。
- 打开公众号公开文章详情，查看公开文章数据，扩展相关文章。
- 提取公开短视频口播文案、字幕或 transcript。
- 根据提示词和参考图生成创作者封面、配图或海报素材。

用户已给出明确任务且属于小范围时，直接执行；首轮最多做 5 次外部查询。
如果需要扩大关键词、账号、内容详情、评论分页、文案提取或生图数量，说明新增的业务范围并请用户确认。

## 调用公开数据工具前

- 小红书、抖音、TikTok、Instagram 或 YouTube 内容链接：看内容用详情工具，看评论用评论工具，不要当主页链接。视频号 `/sph/` 分享链接可用于详情；评论必须先从详情取得纯数字内容 ID。
- 小红书、抖音、TikTok、Instagram 或 YouTube 主页链接：普通主页查看或基础主页分析先用
  `get-user-posted-notes`；只有用户明确要粉丝数、简介、关注数、总获赞等主页资料时
  才用 `get-user-info`；深度主页分析看 `analyze-user-profile`。
- 用户只给昵称、账号名、抖音号或数字 ID 时，不要自己拼 URL；先用
  `search-users` 找创作者，再用返回的主页链接或 ID 调主页工具。
- 视频号主页只接受 `search-users` 返回的 finder ID，不接受主页 URL，也不支持 `analyze-user-profile`。
- 抖音主页工具需要可用的主页 URL 或 `search-users` 返回的 `MS4w...` 形式 ID；
  视频短链看单条内容时直接用 `get-note-detail`，需要口播、字幕或 transcript 时才用
  `extract-video-copy`；不要把视频短链用于主页分析。
- YouTube 主页工具只接受 `search-users` 返回的 channel ID 或 `/channel/UC...`
  URL；不要把 `@handle`、`/c/` 或 `/user/` 直接传给主页工具，也不要自动解析。
- TikTok 主页工具接受 canonical `https://www.tiktok.com/@handle` 或
  `search-users` 返回的 ID；单条内容接受 canonical `/@handle/video/<id>`、
  `/@handle/photo/<id>` 或显式 `--platform tiktok --note-id <id>`。不要传
  `vm.tiktok.com`/`vt.tiktok.com` 短链或裸 `@handle`。
- TikTok V1 不支持 `analyze-user-profile`。需要主页资料和近期内容时，按需分别调用
  `get-user-info` 与 `get-user-posted-notes`，不要隐藏组合调用。
- Instagram 主页工具接受 canonical `https://ww

_meta.json

{
  "ownerId": "kn72byzxyctvxnvxm8a4d9qmvx8892za",
  "slug": "lingzao",
  "version": "0.1.106",
  "publishedAt": 1788231353103
}

index.md

# Lingzao Skill Index

## Purpose

This folder contains the Lingzao Skill package for Agent runtimes. Lingzao helps
Agents route creator-operation work, prepare creator research, run public
content lookups when the user has configured access, and generate creator image
assets within a confirmed task scope.

## Package Files

- `SKILL.md`: main Agent instructions and command guidance.
- `VERSION`: current Skill package version.
- `agents/`: Agent metadata.
- `assets/lingzao-logo.png`: packaged brand icon used by Agent metadata.
- `playbooks/`: creator-operation workflows used before answering.
- `playbooks/router-index.json`: centralized route cards for every playbook.
- `playbooks/router-cases.json`: representative user prompts and expected
  primary routes.
- `scripts/`: setup, version check, configuration, and CLI command scripts.
- `skill-card.md`: marketplace summary source.

## Public Boundaries

- Keep user-facing wording focused on Lingzao, creator research, and workflow
  support.
- Do not promise viral growth, guaranteed monetization, full monitoring, bulk
  data export, or copying another creator's content.
- Proceed directly for clear small online tasks. Before expanding keywords,
  accounts, details, comment pages, transcripts, profile depth, or image count,
  confirm only the added business scope.
- Keep Agent instructions focused on task scope. The CLI owns user-visible
  service-result wording derived from structured server responses.
- For service failures, use concise Lingzao retry language and include
  `error_id` only when it is returned.
- Keep credentials, temporary local paths, and sensitive debug details out of
  user-facing output.

## Release Checklist

Before publishing a new Skill package:

1. Confirm `VERSION` is bumped when user-visible behavior changes.
2. Keep `SKILL.md`, `agents/`, `playbooks/`, CLI output, and marketplace copy
   aligned.
3. Run focused Skill CLI tests plus Python compile.
4. Run project checks required by the release risk.
5. Inspect the published package or marketplace file list after release.

## Recent Version Notes

- `0.1.106`: `extract-video-copy` now accepts canonical WeChat Channels
  `https://weixin.qq.com/sph/...` share links directly. Agents do not need a
  detail lookup first and must not attempt media download or decryption. This
  source-only package has not been published.

- `0.1.105`: Douyin `get-note-detail` now documents valid HTTPS
  `v.douyin.com/<short-code>` inputs alongside standard post URLs and numeric
  IDs. The top-level router uses detail for one-post content and reserves
  `extract-video-copy` for spoken copy, subtitles, or transcripts. Agents pass
  the original short URL to Lingzao without opening or expanding it first.
  Invalid formats ask for the original HTTPS share URL instead of automatic
  fallback or another paid detail attempt. This source-only package has not
  been published.

- `0.1.104`: `extract-video-copy` now sends a fresh explicit operation ID for

playbooks/account-report-evidence-visual-contract.md

# Lingzao Account Report Evidence And Visual Contract

Use this contract whenever Lingzao produces a formal or deep account report:

- own-account diagnosis
- comparable-account breakdown
- same-stage peer horizontal diagnosis
- benchmark-account follow-up report
- creator distillation report

This contract turns account analysis into a product-grade deliverable. It is
inspired by strong open account-breakdown skills, but rewritten for Lingzao's
positioning: Lingzao is an operation system, not only a report generator.

## Core Principle

Do not only summarize an account. A useful account report must answer:

1. what this account is really built on
2. which visible content assets already work
3. how the account evolved or repeated its winning assets
4. what the user can learn
5. what the user must not copy
6. what the user should do next

The report should feel like a deliverable, not a private memo and not a dense
chat wall.

## Delivery Level

### Light Read

Use light read when:

- the user only asks "值不值得学"
- the user provided one account and has not asked for a formal report
- only a small homepage/recent-post sample is available
- deeper research scope has not been confirmed

Output:

- one short decision summary in chat
- direct account/note links when available
- one concrete next step
- offer full Word / HTML / Feishu / knowledge-base packaging if they want a
  shareable report

### Formal Report

Use formal report when:

- the user asks for 完整分析, 深度拆解, 正式报告, 可视化报告, Word, HTML, Feishu,
  or client-facing output
- Lingzao has enough public note samples for a standard diagnosis or comparable
  report
- the user has confirmed the deeper scope if more public lookups are needed

Default formal carriers:

1. Word document when available: official shareable deliverable.
2. HTML/webpage preview when available: browser-friendly preview.
3. Knowledge-base-ready Markdown when the user wants to save/reuse it.

If artifact tooling is unavailable, output a complete Markdown report and say
why Word/HTML was not produced. Do not call a rough chat answer a formal
report.

## One-Screen Opening

The first page or chat summary should be readable in one minute:

- report title
- account name and direct profile link
- report date and sample boundary
- account category / positioning subtitle
- one sentence diagnosis or one sentence worth-learning judgment
- 3-4 visible public data points when available
- strongest visible content asset
- biggest current problem or biggest non-copyable condition
- one concrete action the user should copy or test next

Use evidence labels:

- `确定结论`: directly supported by public page, note, cover, comment, or user
  provided data.
- `合理推断`: supported by several visible signals, but not platform backend or
  official algorithm proof.

Do not infer exposure, click-through rate, finish rate, traffic source, single
note follower conversion, sales, or private-domain conversion unless the user
provided backend data.

## Link And Evide

playbooks/atian-creator-judgment-framework.md

# A Tian Creator Judgment Framework

This file is bundled inside the Lingzao Agent plugin. It captures A Tian's creator-account operating judgment so the plugin is not just a list of prompts.

## Core Judgment

Do not only analyze what the account posted. Diagnose:

- what stage the account is in
- what the account is remembered for
- who the content is for, who will click, and who is unlikely to click
- whether the content has a stable audience/problem anchor
- which posts were validated by data
- whether the viral post can be repeated
- what comments reveal about user demand
- what should continue, reduce, or stop
- what the next test should be

## Account Memory Anchor

The user should be able to understand what the account does from:

- account name
- bio
- first-screen covers
- repeated title keywords
- visual style
- topic pattern

If the account feels like a personal feed with unrelated posts, diagnose missing memory anchor before giving advanced advice.

## Audience Persona Anchor

Before advising topics, titles, keywords, or formats, identify the likely user
persona. Use `audience-persona-fit-check.md` when this is unclear.

Judge:

- gender or identity: female-oriented, male-oriented, parents, students,
  workplace, local users, visitors, buyers
- life stage: university, first job, 30+, 35+, married, with children,
  freelancer, business owner
- city or location intent for local life
- what they search, click, save, comment, or pay for
- which audience should not be targeted by this note

If the user does not know their audience, ask for the accounts or notes they
recently liked, saved, searched, or want to imitate, then reverse-infer the
audience before writing the strategy.

## Stage Logic

### 0-1 Beginner

Main problem: direction and first validation.

Do:

- ask what they like, collect, know, own, or can consistently produce
- ask about age/life stage, work/childcare/study/freelance status, and where most of their daily time goes
- ask what they usually search, save, or learn on Xiaohongshu; saved content often reveals what they secretly want to do
- map life clues into possible directions before recommending a niche
- find low-follower viral notes and same-stage accounts
- help them test 2-3 directions
- give first 5 notes and 7-day execution plan

Do not:

- ask them to imitate 100k+ creators directly
- give too many abstract positioning words
- push mature commercial systems too early
- assume they must do口播; graphic notes, lists, screenshots, AI-assisted notes, product tests, and learning records are valid beginner paths

Beginner direction mining:

- childcare/family -> 科学育儿、亲子陪伴、家庭教育、妈妈成长、儿童好物
- workplace -> 职场成长、行业经验、办公效率、副业转型、35+女性职场
- fashion/beauty/lifestyle -> 穿搭、化妆、护肤、普通人变美、生活方式
- buying/product taste -> 好物分享、平价替代、真实测评、消费决策、工具推荐
- travel/local life -> 本地生活、城市攻略、周末去哪、旅行路线、美食探店
- learning/skills/tools -> 学习记录、技能教程、AI工具、读书笔记、普通人自我提升

Expression-format judgment:

- If phone or text clues show natural verbal expression and w

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