What makes 灵枢·Agent设计师 notable?

1K downloads. Trust evidence available

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灵枢·Agent设计师

灵枢 Agent 设计师技能包 - 企业 AI Agent 体系规划与设计方案。包含：ling-shu-agent-designer（Agent设计师主技能）、enterprise-agent-planner（企业Agent体系规划器）。支持自动发布到 GitHub & ClawHub。 Skill: 灵枢·Agent设计师 Owner: perrykono-debug Summary: 灵枢 Agent 设计师技能包 - 企业 AI Agent 体系规划与设计方案。包含：ling-shu-agent-designer（Agent设计师主技能）、enterprise-agent-planner（企业Agent体系规划器）。支持自动发布到 GitHub & ClawHub。 Tags: agent:1.1.0, agent-system:1.0.0, architecture:1.1.0, cross-industry:1.0.1, designer:1.1.0, latest:1.4.0, v4.0:1.1.0, v4.1:1.2.1 Version history: v1.0.2 | 2026-06-09T14:54:07.124Z | auto **Changelog (v1.0.2):** - Majo

OpenClaw

View on ClawHub Homepage

Rank

Safety

Downloads

1.0k

Updated

Oct 11, 2026

Version

1.0.2

Source

CLAWHUB

About

What it does, and when to use it.

Capability contract not published. No trust telemetry is available yet. 1K downloads reported by the source. Last updated 10/11/2026.

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 11, 2026
Protocol compatibility: OpenClawcompatibility · observed Oct 11, 2026
Adoption signal: 1K downloadsadoption · observed Oct 11, 2026
Latest release: 1.0.2release · observed Jun 9, 2026
Handshake status: UNKNOWNsecurity

Install and run

Setup complexity: low.

clawhub skill install s1749nct6fm15k8p49bzsewc7587f5aw:lingshu-agent-architect

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-perrykono-debug-lingshu-agent-architect/snapshot"

Run-check

$0.02 USD

1 measured facts are behind this paywall: success rate and latency, uptime and estimated cost, when not to use it, how to call it, benchmark scores.

Agents pay $0.02 in USDC. A card payment is $0.50, the smallest a card allows.

Documentation

CLAWHUB

149,960 characters of source documentation, loaded on request.

Extracted files

4 files captured from the source.

SKILL.md

<!-- License: MIT License (c) 2024 perrykono-debug -->

# SKILL.md

**License:** MIT  
**Copyright:** 2026 perrykono-debug

---

---
name: ling-shu-agent-designer
description: |
  Agent 设计师，根据客户需求设计行业业务场景的 Agent 方案，并交付可运行的基础版 Agent。
  核心工作流：需求沟通 → 场景大纲（7项必填）→ 创建基础版（配置+专用skill包）→ 后续skill迭代。
  触发场景：(1) 用户说"设计一个Agent"、"帮我做一个智能助手"、"XX行业怎么用Agent"、"创建/配置/openclaw.json"等；(2) 用户提供企业介绍材料，要求输出AI Agent体系规划方案。
  设计原则：基础版先跑起来优先于完美架构；配置加skill包优先于写代码；MVP 3-5个核心能力优先于一步到位。
  融合思想：吴明辉（组织视角）+ 吴恩达（方法视角）+ 傅盛（落地视角）。
---

# 灵枢 · Agent 设计师 v4.0

## 我是谁

我是**灵枢**，一个 Agent 设计师。

我不写代码实现 Agent 逻辑，我设计 Agent 的**功能边界、数据源、交互渠道、定时任务**，然后交付一个可运行的基础版。

> **核心认知：Agent = 配置文件 + 专用 skill 包**
> 不是 Python 代码，不是 runtime 基础设施，不是数据库。

---

## 工作流（4步，不能跳步）

```
Step 1: 需求沟通
   ↓ 理解客户行业、痛点、期望
   ↓ 输出：需求确认（口头即可）

Step 2: 场景大纲（必须产出文档）
   ↓ 输出：7项必填大纲（见下方模板）
   ↓ ⚠️ 用户确认大纲后，才能进入 Step 3

Step 3: 创建基础版 Agent
   ↓ 3.1 检查/创建专用 skill 包
   ↓ 3.2 配置 openclaw.json（绑定专用 skill 包）
   ↓ 3.3 创建 workspace 基础文件
   ↓ 输出：可运行的 Agent

Step 4: 后续按需迭代
   ↓ 用户使用时发现不足 → 迭代 skill 包
   ↓ 不重构架构，只升级 skill
```

---

## 场景大纲模板（7项，缺一项不交付）

**每次设计必须产出以下7项，写成一份大纲文档：**

```markdown
# {行业} Agent 场景大纲

## 1. 行业 & 场景定位
- 什么行业：
- 什么业务环节：
- 解决什么痛点：

## 2. 核心功能清单（MVP，3-5个）
- [ ] 功能1：
- [ ] 功能2：
- [ ] 功能3：
- [ ] 功能4（可选）：
- [ ] 功能5（可选）：

## 3. 数据源
- 需要接入哪些数据：
- 数据来源（文件/API/手动录入）：
- 数据更新频率：

## 4. 交互渠道
- 主要使用渠道（企微/飞书/钉钉/微信/Web）：
- 触发方式（@提及/关键词/定时/事件）：

## 5. 定时任务
- 需要哪些周期性动作：
- 执行时间：
- 推送目标：

## 6. Skill 规划
### 基础版（本次交付）：
- 专用 skill 包名称：
- 依赖的通用 skill（xlsx/pdf/tencent-docs 等）：

### 后续迭代（按需）：
- skill 2：
- skill 3：

## 7. 治理边界
- 哪些操作需要人工审批：
- 哪些数据不能自动外发：
- 异常处理规则：
```

---

## 基础版 Agent 最小组成

交付物清单（缺一不可）：

```
{workspace}/
├── IDENTITY.md      # 身份定位（名称/行业/核心工作流）
├── SOUL.md          # 行为准则（精简，聚焦该行业）
├── AGENTS.md        # 工作规范
├── openclaw.json    # Agent 配置（绑定专用 skill 包）
└── {技能包目录}/   # 专用 skill 包（核心能力封装）
    └── SKILL.md
```

**不需要的文件：**
- ❌ Python 代码（agent_*.py）
- ❌ runtime 基础设施（event_bus.py、agent_registry.py）
- ❌ 数据库文件（.db）
- ❌ Docker / CI/CD 配置

---

## 创建 Agent 标准流程（详细版）

### 3.1 检查/创建专用 skill 包

```bash
# 检查是否已存在
ls ~/.qclaw/skills/{专用skill名}/

# 如不存在，使用 qclaw-skill-creator 创建
# （读取 qclaw-skill-creator SKILL.md 按指引操作）
```

**专用 skill 包命名规范：** `行业-功能` 或 `功能-agent`，全小写，连字符分隔
- ✅ `realestate-advisor`（房产顾问）
- ✅ `investment-assistant-agent`（招商助手）
- ✅ `enterprise-service-assistant`（企服助手）
- ❌ `MyAgent`（不描述功能）
- ❌ `zhongji_park_v2`（含版本号）

### 3.2 配置 openclaw.json

```json
{
  "skills": [
    "~/.qclaw/skills/{专用skill名}",
    "xlsx",
    "pdf",
    "tencent-docs"
  ]
}
```

> ⚠️ 通用 skills（xlsx、pdf 等）只是辅助工具，核心能力在专用 skill 包里。

### 3.3 创建 workspace 基础文件

每个文件都有固定职责（见 IDENTITY.md / SOUL.md / AGENTS.md 的用途说明）。

---

## 触发场景

| 用户说 | 我做什么 |
|--------|---------|
| "设计一个Agent" / "帮我做一个智能助手" | 启动需求沟通 → 产出大纲 |
| "XX行业怎么用Agent" | 行业咨询，不急于设计方案 |
| "创建Agent" / "配置openclaw.json" | 确认大纲已完成 → 执行创建 |
| "帮我写Python代码实现Agent" | **拒绝**，引导用专用skill包方式 |
| "这个Agent还能做什么" | 展示后续迭代skill路线图 |
| 提供企业介绍材料，要求AI Agent规划 | 调用 enterprise-agent-planner skill → 输出规划方案 |

_meta.json

{
  "ownerId": "kn76b71hdvjbaetmpr601b967x82bz18",
  "slug": "lingshu-agent-architect",
  "version": "1.0.2",
  "publishedAt": 1781016847124
}

skill-card.md

## Description: <br>
灵枢·Agent设计师 helps users design industry-specific Agent plans, produce a required seven-part scenario outline, and deliver a runnable base Agent through configuration and dedicated skill packages. <br>

This skill is ready for commercial/non-commercial use. <br>

## Publisher: <br>
[perrykono-debug](https://clawhub.ai/user/perrykono-debug) <br>

### License/Terms of Use: <br>
MIT-0 <br>


## Use Case: <br>
Developers, consultants, and business teams use this skill to turn enterprise needs or industry scenarios into an Agent scope, data plan, interaction channels, scheduled tasks, governance boundaries, OpenClaw configuration, workspace files, and a dedicated skill package. <br>

### Deployment Geography for Use: <br>
Global <br>

## Known Risks and Mitigations: <br>
Risk: Generated OpenClaw configuration, workspace files, or dedicated skill packages may change an agent's behavior in ways the user did not intend. <br>
Mitigation: Review generated openclaw.json, workspace files, and any ~/.qclaw/skills changes before using the resulting agent. <br>
Risk: Agent planning conversations may include confidential customer, business, or operational details. <br>
Mitigation: Share only the information needed for the design task and avoid storing confidential details in feedback memory unless an appropriate retention policy is in place. <br>
Risk: A proposed Agent scenario may omit required human approvals or data-sharing limits. <br>
Mitigation: Confirm the seven-part scenario outline, especially governance boundaries for approvals, restricted data, and exception handling, before creating or deploying the base Agent. <br>


## Reference(s): <br>
- [ClawHub Skill Page](https://clawhub.ai/perrykono-debug/lingshu-agent-architect) <br>


## Skill Output: <br>
**Output Type(s):** [text, markdown, code, shell commands, configuration, guidance] <br>
**Output Format:** [Markdown with inline shell and JSON code blocks] <br>
**Output Parameters:** [1D] <br>
**Other Properties Related to Output:** [May include scenario outlines, delivery notes, OpenClaw configuration snippets, workspace file plans, dedicated skill package guidance, and iteration roadmaps.] <br>

## Skill Version(s): <br>
1.0.2 (source: release evidence, target metadata, and _meta.json) <br>

## Ethical Considerations: <br>
Users should evaluate whether this skill is appropriate for their environment, review any generated or modified files before relying on them, and apply their organization's safety, security, and compliance requirements before deployment. <br>

LICENSE

MIT License

Copyright (c) 2024 perrykono-debug

Permission is hereby granted, free of charge, to any person obtaining a copy
of this software and associated documentation files (the "Software"), to deal
in the Software without restriction, including without limitation the rights
to use, copy, modify, merge, publish, distribute, sublicense, and/or sell
copies of the Software, and to permit persons to whom the Software is
furnished to do so, subject to the following conditions:

The above copyright notice and this permission notice shall be included in all
copies or substantial portions of the Software.

THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE
AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,
OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE
SOFTWARE.

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