Token导航 LogoToken导航

Agent Skill · 效率

bookforge-distributed-feasibility-checker(bookforge 分布式可行性检查器)

bookforge-distributed-feasibility-checker 用于补充效率相关能力,适合在 OpenClaw 中需要让 Agent 承接效率相关任务时使用。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。

bookforge-distributed-feasibility-checker 是效率类 Agent Skill,可用宿主为 OpenClaw,通过ClawHub获取,权限为调用外部服务;许可证为 MIT-0,第三方扫描已通过,按安装量在效率类的 21,003 个 Skill 里排第 17,091。

总安装 2,691周安装 111GitHub Stars 公开资料未说明下载 879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:bookforge-distributed-feasibility-checker(bookforge 分布式可行性检查器)
来源仓库:https://github.com/quochungto/bookforge-distributed-feasibility-checker
安装命令:
openclaw skills install bookforge-distributed-feasibility-checker
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 bookforge-distributed-feasibility-checker

这个 Skill 是做什么的

效率类 Skill 把重复的整理、汇总、转换工作交给助手完成,减少手工复制粘贴。

评估系统是否应采用分布式架构,规避常见设计陷阱。适用于单体应用拆分前的技术决策参考。bookforge-distributed-feasibility-checker 属于效率类 Skill,可作为该场景下的辅助能力补充。系统检查分布式计算的八大谬误及其规避方案。需权衡分布式收益与复杂度增加的成本代价。

输出包含架构建议书和迁移路线图草案。

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 bookforge-distributed-feasibility-checker;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

bookforge-distributed-feasibility-checker 怎么安装?

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

bookforge-distributed-feasibility-checker 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。

bookforge-distributed-feasibility-checker 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。

bookforge-distributed-feasibility-checker 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。

bookforge-distributed-feasibility-checker 用的人多吗?

公开数据是累计安装 2,691 次,近一周安装 111 次,下载 879 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。

bookforge-distributed-feasibility-checker 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。
  • 需要处理效率类任务、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。

效率类 Skill 对比

6 个同类
Skill总安装GitHub 星权限许可证扫描
github

GitHub 代码协作 · OpenClaw

7,632,918545需要联网MIT-0通过
nano-pdf

Nano PDF 文档 · OpenClaw

4,249,476231需要联网MIT-0通过
auto-updater

自动更新程序 · OpenClaw

2,964,063386操作浏览器MIT-0通过
video-frames

视频帧 · OpenClaw

2,621,304112需要联网MIT-0通过
gemini

Gemini 助手 · OpenClaw

2,547,39648需要联网MIT-0有提醒
bookforge-distributed-feasibility-checker

bookforge 分布式可行性检查器 · 本页

2,691—调用外部服务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
distributed-feasibility-checker
description
Evaluate whether a system should adopt distributed architecture by systematically checking against the 8 Fallacies of Distributed Computing and assessing team/operational readiness. Use this skill whenever the user is considering microservices, debating monolith vs distributed, hearing "let's use microservices," evaluating operational readiness for distribution, or experiencing growing pains with a monolith — even if they don't mention "distributed computing fallacies.
version
1.0.0
homepage
https://github.com/bookforge-ai/bookforge-skills/tree/main/books/fundamentals-of-software-architecture/skills/distributed-feasibility-checker
metadata
{"openclaw":{"emoji":"📚","homepage":"https://github.com/bookforge-ai/bookforge-skills"}}
status
draft
depends-on
[]
source-books
title
Fundamentals of Software Architecture
authors
["Mark Richards", "Neal Ford"]
chapters
[9, 17, 18]
tags
[software-architecture, architecture, distributed-systems, microservices, monolith, fallacies, feasibility]
execution
tier
1
mode
full
inputs
description
System description and team context — the skill guides the evaluation
tools-required
[Read, Write]
tools-optional
[Grep, Glob]
mcps-required
[]
environment
Any agent environment. If a codebase exists, can scan for distribution indicators.

Distributed Architecture Feasibility Checker

When to Use

Someone is proposing or considering distributed architecture (microservices, service-based, event-driven) and you need to evaluate whether it's actually justified and feasible. Typical situations:

  • "Let's move to microservices" — but has anyone checked if the team is ready?
  • Growing pains with a monolith — but is distribution the right solution?
  • CTO or tech lead pushing for distribution based on industry hype
  • Pre-requisite sanity check before architecture-style-selector
  • Post-quantum-analysis: you've identified multiple quanta, now check if the team can actually operate distributed

Before starting, verify:

  • Is there a genuine architectural problem to solve? (If the monolith is working fine, distribution adds cost without benefit)
  • Has quantum analysis been done? If not, distribution may not even be needed (use architecture-quantum-analyzer first)

Context & Input Gathering

Input Sufficiency Check

This skill critically depends on TEAM context, not just technical requirements. A system that technically needs distribution may still fail if the team can't operate it.

Required Context (must have — ask if missing)

  • System description: What does the system do? What's the current architecture?

→ Check prompt for: system purpose, current state (monolith/distributed/greenfield) → If missing, ask: "What does your system do, and what's your current architecture? (monolith, some services, greenfield?)"

  • Team size and distributed experience: How many developers? Have they operated distributed systems before?

→ Check prompt for: team size, experience mentions, technology familiarity → If missing, ask: "How many developers do you have, and has your team operated distributed systems (microservices, message queues, service mesh) before?" → WHY this is critical: Team experience is the #1 predictor of distributed architecture success. A team that's never run microservices will struggle regardless of technical merit.

  • Motivation for considering distribution: Why are they thinking about this?

→ Check prompt for: scaling issues, deployment pain, team autonomy needs, hype → If missing, ask: "What specific problem is driving you toward distributed architecture? (a) scaling bottleneck, (b) deployment takes too long, (c) teams stepping on each other, (d) someone said we should, (e) other?"

Observable Context (gather from environment)

  • Current infrastructure: What deployment and monitoring tools exist?

→ Look for: docker-compose, k8s manifests, CI/CD configs, monitoring configs → Reveals: operational maturity level

  • Service communication: Are there already distributed calls?

→ Look for: HTTP client imports, message queue configs, gRPC definitions → Reveals: whether distribution has already started

Default Assumptions

  • If team experience unknown → assume NO distributed experience (safer to overestimate the challenge)
  • If monitoring tools unknown → assume basic logging only (no distributed tracing)
  • If motivation unclear → probe before proceeding — distribution without clear motivation is the biggest risk

Sufficiency Threshold

SUFFICIENT: system description + team size + team experience + motivation are known
MUST ASK: team experience is unknown (this is NEVER safe to default)

Process

Step 1: Understand the Motivation

ACTION: Clarify WHY distribution is being considered. Categorize the motivation.

WHY: The most dangerous path to distributed architecture is "because everyone else is doing it." Valid motivations have specific, measurable problems. Invalid motivations are based on hype, resume-driven development, or "Netflix does it." Categorizing the motivation early prevents wasted analysis.

MotivationValidityNext step
Specific scaling bottleneck in one partValidQuantify the bottleneck
Deployment takes too long (all-or-nothing)ValidCheck if modular monolith solves it first
Teams blocking each other on shared codeValidCheck if code ownership solves it first
"Everyone uses microservices now"InvalidPush back — this isn't a problem statement
"Our CTO read an article"InvalidAsk what specific problem they're trying to solve
Technology exploration / learningPartially validBe honest about the cost of learning in production

Step 2: Evaluate Against the 8 Fallacies

ACTION: Systematically evaluate the project against each of the 8 Fallacies of Distributed Computing. For each, assess: does the team understand this risk? Do they have mitigations?

WHY: The 8 fallacies are assumptions that developers make about distributed systems that are FALSE. Every distributed system must contend with all 8. Teams that haven't thought about them will be surprised — and surprises in distributed systems cause outages. Using these as a checklist transforms abstract knowledge into a concrete readiness assessment.

For each fallacy, evaluate:

#FallacyThe false assumptionReality check question
1The Network Is ReliableNetwork calls always succeedDo you have timeouts and circuit breakers? What happens when Service B is unreachable?
2Latency Is ZeroRemote calls are as fast as localWhat's your average and 95th-percentile latency? How many chained service calls per request?
3Bandwidth Is InfiniteSend as much data as you wantAre you sending entire objects when you only need a few fields? (Stamp coupling)
4The Network Is SecureInternal network is safeDoes distribution multiply your attack surface? How many new network endpoints?
5The Topology Never ChangesNetwork layout is fixedWhat happens when ops upgrades routers on the weekend? Do your services use hardcoded IPs?
6There Is Only One AdministratorOne team controls everythingHow many teams manage infrastructure? Who coordinates deployments?
7Transport Cost Is ZeroNetwork calls are freeWhat's the actual infrastructure cost of service mesh, load balancers, API gateways?
8The Network Is HomogeneousAll network equipment is the sameDo you run multi-cloud? Different hardware vendors?

Step 3: Assess Operational Readiness

ACTION: Evaluate whether the team has the operational maturity to run distributed systems.

WHY: Distribution doesn't just change how you code — it fundamentally changes how you operate. Distributed logging, distributed tracing, distributed transactions, independent deployments, service discovery, contract versioning — these are operational capabilities that don't exist in monolith-land. A team without these capabilities will build a distributed system they can't debug, can't deploy safely, and can't monitor.

CapabilityQuestionReady if...Not ready if...
Distributed loggingCan you correlate logs across services?Have ELK/Datadog with correlation IDsConsole.log to stdout per service
Distributed tracingCan you trace a request across service boundaries?Have Jaeger/Zipkin/Datadog APMNo tracing infrastructure
CI/CD per serviceCan you deploy one service without deploying all?Per-service pipelines with independent versioningSingle pipeline deploying everything
Service discoveryHow do services find each other?Service mesh, DNS-based, or registryHardcoded URLs in config
Contract managementHow do you handle API changes between services?Versioned APIs, consumer-driven contract testsNo versioning strategy
Monitoring & alertingCan you detect when one service is degrading?Per-service health checks, SLO dashboardsAggregate-only monitoring

Step 4: Check for Simpler Alternatives

ACTION: Before recommending distribution, verify that simpler solutions don't solve the problem.

WHY: Distribution is the most expensive solution to almost any problem. A modular monolith with good code boundaries solves many of the same problems (team autonomy, code organization, independent development) without the operational overhead. The book explicitly states that monolith advantages are REAL — simpler deployment, simpler testing, simpler debugging, lower cost. Distribution should be the LAST option, not the first.

ProblemSimpler alternativeWhen it's NOT enough
Deployment takes too longModular monolith with independent module buildsDifferent modules need different deployment frequencies
Teams stepping on each otherCode ownership + branch-by-abstractionTeams need different technology stacks
One part needs to scaleSeparate the hot path only (strangler fig)3+ parts need independent scaling
"It's too complex"Better module boundaries, cleaner interfacesGenuine bounded contexts with different data models

Step 5: Produce the Feasibility Assessment

ACTION: Compile a structured go/no-go assessment with specific recommendations.

WHY: The value of this skill is the structured, honest assessment — not a blanket "yes" or "no" to microservices. Some teams are ready. Some aren't. Some should start with a single service extraction, not full distribution. The assessment should be specific enough to act on.

Inputs

  • System description and current architecture
  • Team size, experience, and operational capabilities
  • Motivation for considering distribution

Outputs

Distributed Architecture Feasibility Assessment

# Feasibility Assessment: {System Name}

## Motivation Analysis
**Stated motivation:** {what the team says}
**Validated motivation:** {Valid / Invalid / Partially valid}
**Underlying problem:** {the real problem, which may differ from stated motivation}

## 8 Fallacies Evaluation

| # | Fallacy | Team awareness | Mitigations in place | Risk level |
|---|---------|:---:|:---:|:---:|
| 1 | Network Is Reliable | Yes/No | {specific mitigations or "none"} | Low/Med/High |
| 2 | Latency Is Zero | Yes/No | {mitigations} | Low/Med/High |
| 3 | Bandwidth Is Infinite | Yes/No | {mitigations} | Low/Med/High |
| 4 | Network Is Secure | Yes/No | {mitigations} | Low/Med/High |
| 5 | Topology Never Changes | Yes/No | {mitigations} | Low/Med/High |
| 6 | Only One Administrator | Yes/No | {mitigations} | Low/Med/High |
| 7 | Transport Cost Is Zero | Yes/No | {mitigations} | Low/Med/High |
| 8 | Network Is Homogeneous | Yes/No | {mitigations} | Low/Med/High |

**Fallacy readiness score:** {X}/8 mitigated

## Operational Readiness

| Capability | Status | Gap |
|-----------|:---:|-----|
| Distributed logging | Ready/Not ready | {what's missing} |
| Distributed tracing | Ready/Not ready | {what's missing} |
| CI/CD per service | Ready/Not ready | {what's missing} |
| Service discovery | Ready/Not ready | {what's missing} |
| Contract management | Ready/Not ready | {what's missing} |
| Monitoring & alerting | Ready/Not ready | {what's missing} |

**Operational readiness score:** {X}/6 capabilities in place

## Simpler Alternatives Considered
| Alternative | Solves the problem? | Why/why not |
|------------|:---:|-------------|
| Modular monolith | Yes/No/Partially | {reasoning} |
| Single service extraction | Yes/No/Partially | {reasoning} |
| Better code boundaries | Yes/No/Partially | {reasoning} |

## Recommendation
**{Go / No-Go / Conditional Go}**
- {Primary reasoning}
- {If conditional: what must be done first}

## If Proceeding: Readiness Roadmap
1. {First capability to build before distributing}
2. {Second capability}
3. {Suggested first service to extract}

Key Principles

  • Distribution is a trade-off, not an upgrade — Distributed architecture gains scalability and team autonomy but pays with operational complexity, debugging difficulty, and infrastructure cost. It's not inherently better than monolith — it's different, with different trade-offs. The 8 fallacies are the price of admission.
  • Team readiness trumps technical need — A technically justified distributed architecture operated by an unprepared team produces worse outcomes than a monolith. Team experience with distributed operations, monitoring, and debugging is the #1 success predictor.
  • Check for simpler solutions first — A modular monolith with clean boundaries solves 80% of the problems people think require microservices, at 20% of the operational cost. Distribution should be the LAST option, not the first.
  • Monolith is not a dirty word — The book explicitly defends monolith advantages: simpler deployment, simpler testing, simpler debugging, lower operational cost. Many successful systems run as monoliths. Don't recommend distribution to be "modern."
  • The distributed monolith is the worst outcome — Adopting microservices but keeping all the coupling of a monolith gives you the operational overhead of distribution with none of the benefits. This is the most common result of premature distribution.
  • Latency is the deal-breaker — Fallacy #2 is the primary factor in whether distribution is feasible. If your request chains 10 service calls at 100ms each, you've added 1 second of latency. Know your numbers before committing.

Examples

Scenario: Startup wanting microservices Trigger: "We're 5 developers building a SaaS. Should we start with microservices?" Process: Asked about motivation — "our CTO says it's best practice." Invalid motivation — no specific problem. Evaluated: team has no distributed experience, no monitoring beyond basic logging, single CI pipeline. Checked simpler alternatives: modular monolith solves all current needs. Fallacy check: 0/8 mitigated. Operational readiness: 0/6. Output: No-Go. Recommended modular monolith with clean domain boundaries. Distribution adds operational cost the 5-person team can't absorb. Revisit when: team hits 15+ developers, or specific parts need independent scaling proven by data.

Scenario: Growing monolith with real pain Trigger: "We have 40 developers, deployments take 2 hours, and the payment module keeps bringing down the whole site during Black Friday." Process: Valid motivation — specific scaling bottleneck + deployment pain. Team has 3 years of monolith experience, basic CI/CD, Datadog for monitoring but no distributed tracing. Fallacy evaluation: aware of #1 and #2, unaware of #3-#8. Operational readiness: 2/6 (monitoring, basic CI/CD). Simpler alternatives: modular monolith partially solves deployment but not the Black Friday scaling. Output: Conditional Go. Extract payment module as first service (strangler fig pattern). Before extracting: implement distributed tracing, per-service CI/CD pipeline, and circuit breakers. Don't attempt full microservices — start with 2-3 services maximum.

Scenario: Already distributed but struggling Trigger: "We went microservices 6 months ago and everything is on fire. Can't trace bugs, deployments are a nightmare, and our latency tripled." Process: Diagnosed against fallacies: Fallacy #2 (latency) — chaining 8 synchronous calls, 95th percentile at 2 seconds. Fallacy #1 — no circuit breakers, cascading failures. Operational readiness: 1/6 (only basic logging). The team fell into the distributed monolith anti-pattern — services share a database and deploy in lockstep. Output: Feasibility assessment showing the team wasn't ready. Recommended: consolidate back to 3-4 larger services (from 12), implement distributed tracing and circuit breakers, establish per-service databases before attempting fine-grained services again.

References

License

This skill is licensed under CC-BY-SA-4.0. Source: BookForge — Fundamentals of Software Architecture by Mark Richards, Neal Ford.

Related BookForge Skills

This skill is standalone. Browse more BookForge skills: bookforge-skills

平台分布

OpenClaw

79.16%
按下载量换算696

安全审计

VirusTotal

通过

ClawScan

通过

Static analysis

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。目前只有一个公开来源,建议同时核对源仓库。

继续浏览同类 Skills