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Agent Skill · 研究检索

architect(架构师)

architect 用于查找、检索和筛选相关信息,适合在 Codex、Claude、Cursor、Gemini CLI 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。

architect 是研究检索类 Agent Skill,可用宿主为 Codex、Claude、Cursor、Gemini CLI,通过GitHub 仓库获取,权限为调用外部服务;许可证信息还不明确,第三方扫描有未通过项,按安装量在研究检索类的 73,675 个 Skill 里排第 72,323。

总安装 188周安装 8GitHub Stars 1下载 66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
unknown

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:architect(架构师)
来源仓库:https://github.com/jschulte/claude-plugins
仓库路径:skills/architect
安装命令:
npx skills add https://github.com/jschulte/claude-plugins --skill architect
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 npx skills 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。

skills.shnpx skills
npx skills add https://github.com/jschulte/claude-plugins --skill architect

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。

用于查找、检索和筛选相关信息。architect 属于研究检索类 Skill,可作为该场景下的辅助能力补充。适合根据关键词或任务场景快速定位候选结果。可辅助研究类任务的信息收集环节。适用宿主包括 Codex、Claude、Cursor、Gemini CLI,接入前应确认版本、权限和运行环境要求。

建议结合具体需求验证搜索策略的有效性。需注意来源仓库的维护状态和实际功能边界。

来源仓库内路径:skills/architect

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 Codex、Claude、Cursor、Gemini CLI;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 npx skills add https://github.com/jschulte/claude-plugins --skill architect;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

    它需要调用外部服务,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

architect 怎么安装?

在终端执行 npx skills add https://github.com/jschulte/claude-plugins --skill architect。装完完全退出宿主工具再打开,让它重新扫描本地 Skill。

architect 支持哪些 AI 工具?

公开资料标注支持 Codex、Claude、Cursor、Gemini CLI。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。

architect 需要什么权限?

权限级别是调用外部服务。该 Skill 可能调用第三方服务、云服务或外部模型 API,使用前需要确认账号、额度、数据发送范围和服务条款。

architect 是免费的吗?

公开资料没有标注明确许可证,收费和商用限制都无法确认。正式使用前请到来源仓库核对授权说明。

architect 用的人多吗?

公开数据是累计安装 188 次,近一周安装 8 次,下载 66 次,GitHub 1 星。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。

architect 安全吗?

第三方扫描有未通过项,风险较高。除非你确认过源码,否则不建议直接安装到常用环境。

值得选的地方和要先想清楚的地方

值得选的地方

  • 同时适配 4 种工具,换客户端不用重新找替代品。

先想清楚的地方

  • 许可证没有明确标注,能不能商用、能不能再分发都不确定。
  • 第三方扫描存在提醒项或未通过项,需要人工逐条确认。
  • 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 Codex,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。

不太适合

  • 需要明确授权才能用到公司项目里的场景。
  • 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
architect

架构师 · 本页

1881调用外部服务未明确未通过

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

Architecture Generator

Generate an architecture document from reverse-engineering documents (hereafter "RE docs") and user constraints.

Estimated Time: 10-20 minutes Prerequisites: Gear 2 (Reverse Engineer) completed with RE docs present Output: architecture.md — location determined by mode detection in Step 4

This skill assumes single-session execution. If interrupted, restart from Step 1.


Process

Step 1: Load Context

Read all available RE docs from docs/reverse-engineering/. Read all files in parallel for speed.

Primary architecture sources (5 files):

  • data-architecture.md — Current data models, API contracts, domain boundaries
  • integration-points.md — External services, data flows, auth patterns
  • operations-guide.md — Current deployment, infrastructure, scalability
  • decision-rationale.md — Why current choices were made, trade-offs
  • configuration-reference.md — Configuration landscape

Supporting context (4 files):

  • functional-specification.md — What the system needs to do
  • business-context.md — Business constraints, scale expectations, compliance
  • technical-debt-analysis.md — What needs to change
  • observability-requirements.md — Monitoring and logging needs

Error handling for Step 1:

  1. Use Glob to list all files in docs/reverse-engineering/.
  2. Compare found files against the 9 listed above. Classify each as present or missing.
  3. If any primary architecture source (the first 5) is missing: report the missing files to the user and ask whether to proceed with partial context or stop. Do not silently continue.
  4. If only supporting context files (the last 4) are missing: proceed, but log which files are absent. Record these gaps for the assumptions section of the architecture document.
  5. If docs/reverse-engineering/ does not exist or is empty: stop and tell the user to run Gear 2 (Reverse Engineer) first.

Log after completing Step 1: "Step 1 complete: Loaded [N] of 9 RE docs. [List any missing files.]"

Step 2: Ask Constraint Questions

Present these questions conversationally. Skip a question only if a single unambiguous answer is directly stated in the RE docs. When skipping a question, state the detected answer and ask the user to confirm or override. If multiple options are plausible or the RE docs are silent on a topic, ask the question.

Question 1: Tech Stack Preference

What tech stack do you want for the architecture?

A) Same as current (documented in decision-rationale.md)
   [Show detected stack: e.g., "TypeScript + Next.js + PostgreSQL"]

B) Let me specify
   Ask: "What languages, frameworks, and databases?"
   Examples: "Next.js 15 + TypeScript + Prisma + PostgreSQL"
             "Python + FastAPI + SQLAlchemy + PostgreSQL"
             "Go + Gin + GORM + PostgreSQL"

C) Recommend based on requirements
   Analyze functional-specification.md + business-context.md
   Recommend stack with rationale

Question 2: Deployment Target

Where will this run?

A) AWS (EC2, ECS, Lambda, RDS, etc.)
B) Google Cloud (GKE, Cloud Run, Cloud SQL, etc.)
C) Azure (AKS, App Service, Azure SQL, etc.)
D) Self-hosted / On-premise
E) Hybrid (specify)
F) Recommend based on requirements

Question 3: Scale Expectations

What scale should the architecture support?

A) Startup / MVP
   Single-region, simple deployment, cost-optimized
   100s of users, minimal redundancy

B) Growing Product
   Multi-AZ, auto-scaling, managed services
   1,000s - 10,000s of users

C) Enterprise / High-Scale
   Multi-region, microservices-ready, full redundancy
   100,000s+ users, strict SLAs

D) Specify custom requirements
   Ask for: expected users, requests/sec, data volume, SLA targets

Question 4: Hard Constraints (free text, optional)

Any hard constraints to keep in mind?

Examples:
- "Must be HIPAA compliant"
- "Budget under $500/month"
- "Team of 3 developers, keep it simple"
- "Must support offline mode"
- "No vendor lock-in"
- "Must use Kubernetes"

Enter constraints or press enter to skip.

Question 5: Architecture Style If the architecture style is clear from the RE docs, skip this question: state the detected style and ask the user to confirm or override. Otherwise, ask:

What architecture style fits your needs?

A) Monolith (recommended for small teams / MVPs)
   Single deployable, simpler operations
   Can be modular monolith with clear boundaries

B) Microservices (recommended for larger teams / scale)
   Independent deployments, team autonomy
   Higher operational complexity

C) Serverless (recommended for event-driven / variable load)
   Pay-per-use, auto-scaling
   Cold start considerations

D) Hybrid (specify)

E) Recommend based on team size and requirements

Error handling for Step 2: If the user provides contradictory constraints (e.g., "budget under $100/month" and "multi-region full redundancy"), identify the conflict explicitly, explain why the constraints conflict, and ask the user to resolve before proceeding.

For "Recommend" answers on any question, analyze functional-specification.md + business-context.md + observability-requirements.md to make an informed suggestion. Present the recommendation with rationale and ask the user to confirm.

Log after completing Step 2: "Step 2 complete: Collected constraints for [N] questions. Proceeding to generation."

Step 3: Generate Architecture Document

Using the RE docs and user constraints, generate the architecture document. Follow the template at operations/architecture-template.md (relative to this skill).

Generation approach:

  1. Start from the current architecture as described in the RE docs.
  2. For each architecture decision, check user constraints and select the option that satisfies all hard constraints. Where constraints conflict, prefer the user's explicit choice over inferred preferences.
  3. For each component in the current architecture, determine whether it maps to the target state unchanged, needs modification, or should be replaced. Generate recommendations that bridge current to target state.
  4. Create ADRs justifying each major decision. Generate 3-10 ADRs focusing on consequential decisions. Source from decision-rationale.md where available; generate new ADRs for target-state decisions.
  5. Draw Mermaid diagrams for visual clarity. Use Mermaid C4 notation for system context diagrams.
  6. If the RE docs indicate a brownfield/evolution scenario (existing system being migrated or modernized), generate Section 10: Migration Path using the technical-debt-analysis.md Migration Priority Matrix. If the project is greenfield with no existing system to migrate from, omit Section 10.

Progress signals: Announce each major section as you generate it (e.g., "Generating Section 3: System Architecture..."). This ensures all sections are produced and prevents drift during the lengthy generation.

Step 3.5: Verify Generated Content

Before writing the final document, verify:

  1. All Mermaid diagrams use valid syntax (proper node definitions, valid arrow notation, balanced subgraphs).
  2. ADR decisions are consistent with the stated user constraints. No ADR should contradict a hard constraint from Step 2.
  3. Cost estimates align with the chosen cloud provider and scale tier. Flag all cost estimates as rough approximations.
  4. If Section 10 (Migration Path) is included, confirm it references actual current-state findings from the RE docs.
  5. The technology stack table is fully populated with rationale for each choice.

If any verification check fails, fix the issue before proceeding to Step 4.

Step 4: Detect Mode and Write Output

Mode detection:

  • If the directory _bmad-output/ exists in the project root, operate in BMAD mode.
  • Otherwise, operate in standalone mode.

BMAD mode: Write to _bmad-output/planning-artifacts/architecture.md. If running as part of BMAD Synthesize and RE docs have already been parsed in this session, reuse the parsed context instead of re-reading files.

Standalone mode: Write to docs/architecture.md. If the docs/ directory does not exist, create it.

Error handling for Step 4: If the file write fails, retry once. If it fails again, report the error to the user with the full file path that was attempted.

Log after completing Step 4: "Architecture document written to [full path]. Generation complete."


Verification Checklist

After writing, confirm all of the following before reporting completion:

  • All 10 sections present (or Section 10 intentionally omitted for greenfield)
  • Mermaid diagrams included (context, component, data flow, infrastructure)
  • 3-10 ADRs generated for major decisions
  • User constraints respected throughout
  • Cost estimation included (if cloud deployment)
  • Technology stack justified with rationale
  • Missing RE doc gaps noted in assumptions (if any docs were absent in Step 1)

Integration with Other Skills

BMAD Synthesize: This skill can run as part of /stackshift.bmad-synthesize. Output is compatible with BMAD's architecture.md format.

Reimagine: /stackshift.reimagine may invoke this skill to generate architecture for the reimagined system. Constraint questions are informed by multi-repo capability analysis.

Spec Kit: The architecture document supplements .specify/ structure and can be referenced from feature specs as architectural context.

平台分布

Codex

32.72%
按下载量换算22

Claude

33.46%
按下载量换算22

Cursor

19.98%
按下载量换算13

Gemini CLI

9.91%
按下载量换算7

安全审计

Gen Agent Trust Hub

通过

Socket

未通过

Snyk

通过

权限和风险

调用外部服务

该 Skill 可能调用第三方服务、云服务或外部模型 API,使用前需要确认账号、额度、数据发送范围和服务条款。

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。来源安全扫描存在提醒或未通过项,安装前请自行复核。目前只有一个公开来源,建议同时核对源仓库。

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