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Agent Skill · 研究检索

yuanyuan-blueprint-workshop(缘缘蓝图工作坊)

yuanyuan-blueprint-workshop 用于查找、检索和筛选相关信息,适合在 OpenClaw 中需要根据关键词、任务场景或来源线索快速定位候选结果时使用。可结合来源仓库、安装命令和原始 README 继续核验具体用法。安装前建议确认权限范围、维护状态,以及是否会触发联网、命令执行或文件读写。

yuanyuan-blueprint-workshop 是研究检索类 Agent Skill,可用宿主为 OpenClaw,通过ClawHub获取,权限为需要联网;许可证为 MIT-0,第三方扫描已通过,按安装量在研究检索类的 73,675 个 Skill 里排第 18,222。

总安装 6,205周安装 256GitHub Stars 公开资料未说明下载 2,028核验 2026-05-01

安装说明

本站只整理中文说明,不托管安装包,也不代用户安装。
GitHub
许可证
MIT-0
版本
1.0.0

安装方式

通过对话安装

复制提示词发给支持本地命令或 Skills 的 AI 助手,先确认命令和权限,再让它执行。

请帮我安装这个 Agent Skill:yuanyuan-blueprint-workshop(缘缘蓝图工作坊)
来源仓库:https://github.com/beachanger/yuanyuan-blueprint-workshop
安装命令:
openclaw skills install yuanyuan-blueprint-workshop
安装前请先检查当前环境是否支持对应 CLI,并向我确认将要执行的命令、安装目录、联网范围和文件读写权限;确认后再执行。

命令行安装

复制命令到本机终端执行。该命令会通过 OpenClaw 从第三方来源获取 Skill;本站只展示命令,不托管安装包,也不自动执行。

ClawHubOpenClaw
openclaw skills install yuanyuan-blueprint-workshop

这个 Skill 是做什么的

研究检索类 Skill 主要解决「找资料、核对事实、把来源整理清楚」的问题,通常会让助手先检索再总结。

通过 5 步研讨会指导用户将隐性知识转化为包含场景、SOP、依赖关系和技能来源的可测试代理蓝图。

上手步骤

4 步
  1. 1

    确认自己的宿主工具

    公开资料标注支持 OpenClaw;先确认自己用的是其中之一,再按对应工具的 Skills 目录放置。

  2. 2

    拿到安装命令

    可以直接复制的命令是 openclaw skills install yuanyuan-blueprint-workshop;命令里的占位符换成自己的路径或密钥再执行。

  3. 3

    安装后重启宿主

    命令执行完要完全退出宿主工具再打开,让新装的 Skill 被重新扫描到,否则列表里可能看不到。

  4. 4

    按最小权限试用

    它需要需要联网,先在测试目录或测试账号里跑,确认没问题再放到正式项目。

常见问题

6 条

yuanyuan-blueprint-workshop 怎么安装?

在终端执行 openclaw skills install yuanyuan-blueprint-workshop。装完完全退出宿主工具再打开,让它重新扫描本地 Skill。

yuanyuan-blueprint-workshop 支持哪些 AI 工具?

公开资料标注支持 OpenClaw。其他工具只要能读取本地 Skill 目录,一般也能手动放进去,但要自己确认触发方式是否一致。

yuanyuan-blueprint-workshop 需要什么权限?

权限级别是需要联网。该 Skill 可能需要联网访问来源站点、仓库或外部 API;具体网络访问范围需要结合源码和 README 复核。

yuanyuan-blueprint-workshop 是免费的吗?

来源标注的许可证是 MIT-0。本站不代收任何费用,也不托管安装包;能否商用、要不要署名,以许可证原文为准。

yuanyuan-blueprint-workshop 用的人多吗?

公开数据是累计安装 6,205 次,近一周安装 256 次,下载 2,028 次。这些数字来自第三方目录统计,只能当作热度参考,不代表质量或安全性。

yuanyuan-blueprint-workshop 安全吗?

第三方扫描结果为通过,但这只覆盖已知的静态检查项,不能替代自己读一遍源码和安装命令。

值得选的地方和要先想清楚的地方

值得选的地方

  • 专注 OpenClaw 一种宿主,触发方式和使用习惯不用来回切换。
  • 许可证明确为 MIT-0,商用和分发边界好判断。
  • 第三方扫描已通过,常见的高风险行为没有命中。

先想清楚的地方

  • 第三方目录整理,版本更新和行为细节以来源仓库为准。

适不适合你

更适合

  • 已经在用 OpenClaw,想直接扩展它能力的人。
  • 需要处理研究检索类任务、又不想每次都手写提示词的人。
  • 需要许可证清楚、并且有第三方扫描结果的团队项目。

不太适合

  • 需要厂商级技术支持和 SLA 的生产系统。

研究检索类 Skill 对比

6 个同类
Skill总安装GitHub 星权限许可证扫描
find-skills

寻找技能 · Codex、Claude

31,199,81316,486操作浏览器MIT有提醒
self-improving-agent

自我改进 Agent · OpenClaw

16,464,0023,396接触敏感数据MIT-0通过
soultrace

灵魂追踪 · Codex、Claude

7,588,94412需要联网未明确有提醒
self-improving

自我完善 · OpenClaw

6,829,2841,046需要联网MIT-0通过
microsoft-foundry

微软代工厂 · Codex、Claude

6,614,144764调用外部服务未明确有提醒
yuanyuan-blueprint-workshop

缘缘蓝图工作坊 · 本页

6,205—需要联网MIT-0通过

按安装量取同分类前几名;数字来自第三方目录统计,只作热度参考,不代表质量结论。

SKILL.md 原文

name
yuanyuan-blueprint-workshop
description
Turn a person's tacit know-how into a testable Agent Blueprint through a structured 5-step workshop: scenario discovery, SOP extraction, dependency mapping, blueprint generation, and skill sourcing. Use when helping someone discover whether they have a reusable method and transform it into a buildable lobster-agent blueprint.

Yuanyuan Blueprint Workshop

Purpose

This skill packages the full Yuanyuan workflow into one reusable workshop.

Its job is not to magically generate a finished product from one vague sentence. Its job is to help a user:

  1. discover a real scenario worth turning into an agent,
  2. extract their implicit know-how,
  3. map the required knowledge and tools,
  4. produce a real Agent Blueprint,
  5. plan how the missing skills should be sourced.

Use this skill when

Use it when the user says things like:

  • “I think I have some experience, but I don't know if it can become an agent.”
  • “Help me turn my know-how into a lobster agent.”
  • “I want to productize my method.”
  • “Help me figure out whether this workflow is structured enough.”
  • “Take me from idea → blueprint → skill gap plan.”

Do NOT use this skill when

  • The user only wants a small factual answer.
  • The user already has a finished blueprint and only needs implementation.
  • The user asks for direct coding or deployment without discovery.
  • The task is only to install/publish one isolated skill.

Core promise

This workshop should produce two feelings for the user:

  1. “The AI actually understands what I'm good at.”
  2. “Aha — I really do have a reusable method.”

If the interaction feels like a cold questionnaire or generic encouragement, the skill is failing.


Hard rules

  1. Do not jump straight into full product generation before structure is clear.
  2. Do not confuse domain knowledge with decision logic.
  3. Do not overpromise that every idea deserves to become an agent.
  4. Do not replace user delivery with a file path.

- Save files internally if useful. - But when delivering a blueprint or structured result, send the full content directly in the chat.

  1. Do not install many skills blindly.

- First reuse local capabilities. - Then search ClawHub. - Then vet/scan. - Only then install or write new skills.


The 5-step workshop

Step 1 — Scenario Discovery

Goal: narrow a vague direction into one concrete, testable scenario.

Questions to drive:

  • What are you consistently better at than most people?
  • What do people repeatedly come to you for?
  • If we only productize one scenario first, which one should it be?

Judging standard:

  • Input can be defined
  • Judgment can be structured
  • Output can be verified

Output:

  • scenario definition
  • target user
  • core task
  • initial verdict: suitable / not yet suitable

Step 2 — SOP Extraction

Goal: extract the actual method, not just abstract knowledge.

Methods:

  • Ask “When someone comes to you for this, how do you usually handle it?”
  • Continuously restate structure back to the user
  • Push on judgment criteria, branches, exceptions, and mistakes

Output:

  • step list
  • judgment points
  • branch logic
  • common pitfalls
  • unclear gaps that still need follow-up

Step 3 — Knowledge & Tools Mapping

Goal: identify what this future agent needs in order to really work.

Distinguish:

  • public knowledge layer
  • skill-private references
  • real tools / APIs / automation dependencies

Output:

  • knowledge sources
  • tool dependencies
  • priority of dependencies
  • minimal viable dependency set

Step 4 — Agent Blueprint Generation

Goal: turn the findings into a buildable blueprint.

The blueprint should at minimum include:

  1. scenario definition
  2. target user
  3. core task
  4. SOP flow
  5. judgment rules
  6. knowledge requirements
  7. skill/tool requirements
  8. risks and boundaries
  9. test suggestions
  10. next build steps

Delivery rule:

  • Give the user the full blueprint directly in chat.
  • Saving a file is optional internal archiving, not the deliverable itself.

Step 5 — Skill Sourcing Plan

Goal: connect the blueprint to the platform layer.

Use this order:

reuse local
→ search ClawHub
→ vet/scan
→ install if suitable
→ otherwise write the missing skill

Output:

  • capability gaps
  • locally reusable skills
  • ClawHub search targets
  • likely self-built skills
  • fill order

Recommended final deliverables

By the end of this workshop, aim to produce:

  1. a Scenario Definition,
  2. a Structured SOP,
  3. a Dependency Map,
  4. a Full Agent Blueprint,
  5. a Skill Sourcing Plan.

Success criteria

The workshop is working if the user says things like:

  • “Yes, that's exactly my real value.”
  • “I didn't realize my process was this clear.”
  • “Now I can actually imagine this becoming an agent.”

The workshop is failing if it turns into:

  • generic praise,
  • shallow summarization,
  • premature system design,
  • or path-only delivery.

References

Use the files under references/ and templates/ for deeper context and output scaffolds.

平台分布

OpenClaw

75.09%
按下载量换算1,523

安全审计

VirusTotal

通过

ClawScan

通过

Static analysis

通过

权限和风险

需要联网

该 Skill 可能需要联网访问来源站点、仓库或外部 API;具体网络访问范围需要结合源码和 README 复核。

安装前确认

本站仅展示第三方公开信息,不托管安装包,不提供自动安装或运行环境。安装前应自行审查源码、依赖和命令行为。目前只有一个公开来源,建议同时核对源仓库。

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