Token导航 LogoToken导航

Agent Skill · 研究检索

bookforge-architecture-risk-assessor(Bookforge 架构风险评估器)

bookforge-architecture-risk-assessor 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。

bookforge-architecture-risk-assessor 是研究检索类 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,按安装量在研究检索类的 73,675 个 Skill 里排第 29,749。

总安装 3,006周安装 124GitHub Stars 公开资料未说明下载 982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-architecture-risk-assessor(Bookforge 架构风险评估器)
来源仓库:https://github.com/quochungto/bookforge-architecture-risk-assessor
安装命令:
openclaw skills install bookforge-architecture-risk-assessor
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-architecture-risk-assessor

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。

bookforge-architecture-risk-assessor 使用二维风险矩阵量化架构风险等级。适用于架构评审会议或项目立项风险评估。bookforge-architecture-risk-assessor 属于研究检索类 Skill,可作为该场景下的辅助能力补充。输出包含影响、可能性评分与应对策略的报告。

评分依赖主观判断,不同专家结果可能存在差异。建议定期重新评估,随系统演化更新风险项。

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-architecture-risk-assessor;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-architecture-risk-assessor 怎么安装?

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

bookforge-architecture-risk-assessor 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-architecture-risk-assessor 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-architecture-risk-assessor 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-architecture-risk-assessor 用的人多吗?

公开数据是累计安装 3,006 次,近一周安装 124 次,下载 982 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-architecture-risk-assessor 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
bookforge-architecture-risk-assessor

Bookforge 架构风险评估器 · 本页

3,006—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
architecture-risk-assessor
description
Quantify architecture risk using a 2D risk matrix (impact x likelihood, scored 1-9) and produce structured risk assessment reports. Use this skill whenever the user asks about architecture risks, wants to evaluate risk across services or components, needs a risk matrix, mentions risk assessment, risk analysis, risk heat map, risk scoring, or asks "what are the risks?" for any architecture — even if they don't explicitly say "risk assessment." Also triggers when the user mentions unproven technology risk, scalability risk, availability concerns, security risk, data integrity risk, or wants to prioritize risks for stakeholder meetings.
version
1.0.0
homepage
https://github.com/bookforge-ai/bookforge-skills/tree/main/books/fundamentals-of-software-architecture/skills/architecture-risk-assessor
metadata
{"openclaw":{"emoji":"📚","homepage":"https://github.com/bookforge-ai/bookforge-skills"}}
status
draft
source-books
title
Fundamentals of Software Architecture
authors
["Mark Richards", "Neal Ford"]
chapters
[20]
tags
[software-architecture, architecture, risk, risk-matrix, risk-assessment, governance]
depends-on
[]
execution
tier
1
mode
full
inputs
description
Architecture context from the user — system description, services, components, and concerns
tools-required
[Read, Write]
tools-optional
[Grep, Glob]
mcps-required
[]
environment
Any agent environment. If a codebase exists, can read it for context.

Architecture Risk Assessor

When to Use

You need to systematically identify and quantify risks in a software architecture. Typical triggers:

  • The user describes a system and asks "what are the risks?"
  • The user is adopting unproven or unfamiliar technologies
  • The user needs to present risk findings to stakeholders or leadership
  • The user is planning a migration, new service, or significant architecture change
  • The user wants to compare risk profiles across services or domains
  • The user is doing sprint/iteration planning and wants to identify high-risk stories

Before starting, verify:

  • Is there an architecture to assess? (At minimum, a description of services/components and their responsibilities)
  • Is there a specific risk dimension to focus on, or should you cover all standard criteria?

Context

Required Context (must have before proceeding)

  • System description: What services, components, or domains exist in the architecture?

-> Check prompt for: service names, component descriptions, architecture diagrams, system overviews -> Check environment for: docker-compose files, k8s manifests, service directories, README files -> If still missing, ask: "Can you describe the services or components in your architecture and their primary responsibilities?"

  • Risk concerns: What is the user worried about? What prompted this risk assessment?

-> Check prompt for: mentions of failures, performance issues, security concerns, scaling problems, technology uncertainty -> If still missing, proceed with all standard risk criteria (scalability, availability, performance, security, data integrity)

Observable Context (gather from environment if available)

  • Technology stack: What technologies are in use?

-> Look for: package.json, requirements.txt, go.mod, Dockerfile, infrastructure configs -> If unavailable: rely on user description

  • Architecture style: Monolith, microservices, event-driven, etc.

-> Look for: service count, communication patterns, deployment configs -> If unavailable: infer from user description

  • Existing risk documentation: Previous risk assessments, incident reports, post-mortems

-> Look for: docs/risks/, incident reports, ADRs mentioning risk -> If unavailable: start fresh

Default Assumptions

  • If no risk criteria specified -> use the standard five: scalability, availability, performance, security, data integrity
  • If no team context -> assume a team with moderate experience in the primary technology
  • If technology maturity unknown -> ask, because unproven tech always gets highest risk (9)
  • If no existing risk assessments found -> treat as first assessment (no direction indicators)

Sufficiency Threshold

SUFFICIENT when ALL of these are true:
- System description with identifiable services/components is known
- At least one risk concern or dimension is identified
- Technology stack is known or can be inferred

PROCEED WITH DEFAULTS when:
- System description is known
- Risk criteria can use standard defaults
- Technology details are partially available

MUST ASK when:
- No system description exists (cannot assess risk without knowing what to assess)
- User mentions "unproven technology" but doesn't specify which one
- The architecture is ambiguous (could be interpreted as monolith or distributed)

Process

Step 1: Identify Architecture Components

ACTION: List all services, components, or domain areas that will be assessed for risk. Name each one clearly.

WHY: Risk assessment maps criteria AGAINST specific areas of the architecture. Without a clear component list, the assessment becomes vague hand-waving. Each component carries different risk profiles — a payment service has different risk exposure than a notification service. Identifying components first creates the columns of your risk assessment table.

IF the user provided a clear service list -> use it directly ELSE IF a codebase is available -> scan for service boundaries (separate deployables, bounded contexts) ELSE -> ask the user to enumerate their primary services or domains

Step 2: Determine Risk Criteria

ACTION: Select the risk criteria (dimensions) to evaluate. Start with the standard five unless the user specifies different ones:

  1. Scalability — Can each component handle increased load without degradation?
  2. Availability — What is the impact and likelihood of each component going down?
  3. Performance — Can each component meet latency and throughput requirements?
  4. Security — What is the exposure to unauthorized access, data breaches, or compliance violations?
  5. Data Integrity — What is the risk of data loss, corruption, or inconsistency?

WHY: Risk criteria form the rows of your assessment table. Using standardized criteria ensures consistency across assessments and makes them comparable over time. Custom criteria can be added for domain-specific concerns (e.g., "regulatory compliance" for fintech, "patient safety" for healthcare).

IF the user mentioned specific concerns -> add those as additional criteria IF the domain has regulatory requirements -> add a compliance criterion

Step 3: Score Each Cell Using the Risk Matrix

ACTION: For each component-criteria pair, assess two dimensions independently:

  • Impact (1-3): How severe would it be if this risk materializes?

- 1 = Low: minor inconvenience, easy recovery - 2 = Medium: significant disruption, recoverable with effort - 3 = High: severe damage, potential data loss, major business impact

  • Likelihood (1-3): How probable is it that this risk materializes?

- 1 = Low: unlikely given current architecture and controls - 2 = Medium: possible under certain conditions (peak load, specific failures) - 3 = High: probable or already occurring

  • Risk Score = Impact x Likelihood (range: 1-9)

Classify the composite score:

  • 1-2: Low risk (green) — acceptable, monitor only
  • 3-4: Medium risk (yellow) — needs attention, plan mitigation
  • 6-9: High risk (red) — requires immediate action or architectural change

WHY: The 2D matrix separates two fundamentally different aspects of risk that people conflate. A risk with high impact but low likelihood (earthquake destroys data center) requires a different response than a risk with low impact but high likelihood (cache miss causing a slightly slower page load). Multiplying them produces a single comparable score, but keeping both dimensions visible enables smarter mitigation — you can reduce impact OR reduce likelihood.

CRITICAL RULE: For any unproven or unknown technology, always assign the highest risk score (9 — impact 3 x likelihood 3). Teams consistently underestimate the risk of technologies they haven't used in production. Unknown unknowns are the most dangerous risks.

For detailed matrix layout and visual reference, see references/risk-matrix-template.md.

Step 4: Build the Risk Assessment Table

ACTION: Construct a comprehensive risk assessment table mapping all criteria (rows) against all components (columns). Include row totals (accumulated risk per criterion) and column totals (accumulated risk per component).

WHY: The table is the primary artifact. Row totals reveal which risk criteria are most concerning across the entire system — a high scalability total means the architecture has a systemic scalability problem, not just one service. Column totals reveal which components carry the most risk — these are the parts that need the most architectural attention. Both views are essential: criteria totals drive architectural strategy, component totals drive prioritization.

Format:

| Risk Criteria    | Service A | Service B | Service C | Total |
|------------------|-----------|-----------|-----------|-------|
| Scalability      | 6 (H)    | 2 (L)    | 4 (M)    | 12    |
| Availability     | 3 (M)    | 9 (H)    | 1 (L)    | 13    |
| Performance      | 2 (L)    | 4 (M)    | 6 (H)    | 12    |
| Security         | 9 (H)    | 3 (M)    | 3 (M)    | 15    |
| Data Integrity   | 6 (H)    | 1 (L)    | 9 (H)    | 16    |
| **Total**        | **26**   | **19**   | **23**   |       |

Step 5: Add Risk Direction Indicators

ACTION: For each cell, add a direction indicator showing whether the risk is improving (+), worsening (-), or stable (=) compared to the previous assessment or recent trends.

WHY: A risk score of 6 that is improving (+) tells a very different story than a risk score of 6 that is worsening (-). Direction matters as much as current state. It shows whether mitigation efforts are working, whether new risks are emerging, and where to focus future attention. For first-time assessments, use observable signals: recent incidents suggest worsening (-), recent infrastructure improvements suggest improving (+).

IF this is the first assessment -> use contextual signals (recent incidents, known issues, recent improvements) to infer direction IF previous assessments exist -> compare directly

Step 6: Create Filtered Views for Stakeholders

ACTION: Produce a filtered version of the risk assessment showing ONLY high-risk cells (scores 6-9). Replace low and medium cells with dots or dashes.

WHY: Stakeholders and leadership don't need to see every cell. Showing only red (high-risk) areas focuses attention on what matters and prevents "risk fatigue" where everything looks concerning. The filtered view is what you present in meetings. The full table is the reference document for the architecture team.

Format:

| Risk Criteria    | Service A | Service B | Service C |
|------------------|-----------|-----------|-----------|
| Scalability      | 6 (H) -  | .         | .         |
| Availability     | .         | 9 (H) -  | .         |
| Security         | 9 (H) =  | .         | .         |
| Data Integrity   | 6 (H) +  | .         | 9 (H) -  |

Step 7: Recommend Mitigations for High-Risk Areas

ACTION: For each high-risk cell (6-9), propose a specific mitigation strategy. Include the estimated risk score AFTER mitigation to show the expected improvement.

WHY: Risk assessment without mitigation is just worry. The value is in the response plan. Including post-mitigation scores makes the business case concrete — "spending $X on database clustering reduces data integrity risk from 9 to 3." This feeds directly into budget negotiations with stakeholders.

IF the user needs Agile story-level risk analysis -> also apply the risk matrix to user stories (Step 8) ELSE -> proceed to output

Step 8 (Optional): Agile Story Risk Analysis

ACTION: Apply the risk matrix to individual user stories during iteration planning:

  • Impact dimension: Overall impact if this story is NOT completed in the iteration
  • Likelihood dimension: Probability that this story will NOT be completed (complexity, dependencies, unknowns)
  • Identify stories scoring 6-9 as high-risk and flag them for priority attention

WHY: The same risk matrix that works for architecture works for sprint planning. High-risk stories — those with high impact if missed AND high likelihood of not completing — should be started early, broken down further, or given to the most experienced developers. This connects architectural risk thinking to daily development practice.

Inputs

  • System description with identifiable services/components (from user or codebase)
  • Risk concerns or dimensions to evaluate (from user, or use defaults)
  • Optionally: previous risk assessments, incident history, technology stack details

Outputs

Architecture Risk Assessment Report

# Architecture Risk Assessment: {System Name}

## Assessment Scope
- **Date:** {date}
- **Assessed by:** {who}
- **Architecture style:** {monolith/microservices/event-driven/etc.}
- **Components assessed:** {count}
- **Risk criteria:** {list}

## Architecture Components
1. **{Component A}** — {responsibility}
2. **{Component B}** — {responsibility}
3. **{Component C}** — {responsibility}

## Full Risk Assessment

| Risk Criteria    | Component A      | Component B      | Component C      | Total |
|------------------|------------------|------------------|------------------|-------|
| Scalability      | {score} ({L/M/H}) {dir} | ... | ... | {sum} |
| Availability     | ... | ... | ... | {sum} |
| Performance      | ... | ... | ... | {sum} |
| Security         | ... | ... | ... | {sum} |
| Data Integrity   | ... | ... | ... | {sum} |
| **Total**        | **{sum}**        | **{sum}**        | **{sum}**        |       |

### Scoring Key
- Score = Impact (1-3) x Likelihood (1-3)
- Low (L): 1-2 | Medium (M): 3-4 | High (H): 6-9
- Direction: + improving, - worsening, = stable

## High-Risk Summary (Filtered View)

{Filtered table showing only 6-9 scores}

## Risk Details and Mitigations

### {Component A} — {Risk Criteria} (Score: {N})
- **Impact ({1-3}):** {why this impact level}
- **Likelihood ({1-3}):** {why this likelihood level}
- **Direction:** {+/-/=} {reason}
- **Mitigation:** {specific recommendation}
- **Post-mitigation estimate:** {expected new score}

{Repeat for each high-risk cell}

## Systemic Risk Observations
- {Pattern observed across multiple components}
- {Risk criteria with highest total — indicates systemic issue}
- {Components with highest totals — indicates architectural attention needed}

## Recommendations Priority
1. {Highest priority mitigation} — addresses {risk}
2. {Second priority} — addresses {risk}
3. {Third priority} — addresses {risk}

Key Principles

  • Separate impact from likelihood — These are fundamentally different dimensions that require different mitigation strategies. High-impact/low-likelihood risks need contingency plans. Low-impact/high-likelihood risks need engineering fixes. Conflating them into a single "risk level" hides the appropriate response.
  • Unknown technology = maximum risk — For any unproven or unfamiliar technology, always assign the highest risk score (9). Teams systematically underestimate the danger of technologies they haven't used in production. Unknown unknowns are the most dangerous class of risk. This isn't pessimism — it's calibration against a well-documented bias.
  • Direction matters as much as magnitude — A risk score of 6 that is improving tells a completely different story than a score of 4 that is worsening. Track direction with every assessment. It reveals whether mitigation efforts are working and where new risks are emerging.
  • Filter for your audience — Show the full risk assessment to the architecture team. Show only high-risk areas (6-9) to stakeholders and leadership. Risk fatigue is real — if everything looks red, nothing gets attention. Filtering focuses the conversation on what actually needs action.
  • Risk assessment is continuous, not one-time — Architecture risk changes as the system evolves, new technologies are adopted, team composition shifts, and business requirements change. A risk assessment is a living document. Treat it like a fitness function — measure regularly, compare to previous results, act on trends.
  • Mitigation has a cost — Every mitigation strategy costs something: money, complexity, development time, or operational burden. Present mitigations alongside their costs so stakeholders can make informed decisions. Sometimes accepting a medium risk is better than the cost of eliminating it.

Examples

Scenario: E-commerce platform risk assessment Trigger: "We have 4 services: customer registration, catalog checkout, order fulfillment, and order shipment. Can you assess the architecture risks?" Process: Listed 4 components. Applied standard 5 risk criteria. Scored each cell using the impact x likelihood matrix. Customer registration scored low across the board. Catalog checkout scored high on performance (6) due to peak-hour load. Order fulfillment scored high on availability (9) and data integrity (6) because lost orders mean lost revenue. Order shipment scored medium across most criteria. Created filtered view showing only the 3 high-risk cells. Recommended: message queue between checkout and fulfillment (reduces availability risk from 9 to 3), database replication for order data (reduces data integrity risk from 6 to 2), auto-scaling for catalog during peak hours (reduces performance risk from 6 to 2). Output: Full risk assessment report with filtered stakeholder view and 3 prioritized mitigations with cost estimates.

Scenario: Unproven technology risk flag Trigger: "We're evaluating using CockroachDB for our new service. Nobody on the team has used it before." Process: Immediately flagged CockroachDB as unproven technology — assigned risk score 9 (impact 3 x likelihood 3) per the unknown-technology rule. Assessed the service across standard criteria. Data integrity risk automatically high (9) due to unfamiliar database behavior under edge cases. Availability risk elevated (6) because the team can't troubleshoot production issues quickly. Recommended mitigations: proof-of-concept with production-like load before committing, dedicated learning sprint, identify rollback strategy to known database, engage vendor support. Output: Risk assessment highlighting the technology risk with specific de-risking steps and a decision gate (proceed only if PoC succeeds).

Scenario: Agile story risk analysis for sprint planning Trigger: "We have 12 stories for the next sprint. Some feel risky. How do we figure out which ones to prioritize?" Process: Applied the risk matrix to each story. Impact = business impact if story not completed this sprint. Likelihood = probability of non-completion (based on complexity, dependencies, unknowns). Identified 3 stories scoring 6-9: a payment integration story (impact 3 x likelihood 2 = 6, depends on external API), a data migration story (impact 3 x likelihood 3 = 9, unknown data quality), and a performance optimization story (impact 2 x likelihood 3 = 6, requires load testing infrastructure). Recommended: start data migration story on day 1 with senior developer, spike the payment integration dependency immediately, defer performance story to next sprint if load testing infra isn't ready. Output: Story risk matrix with all 12 stories scored, 3 flagged as high-risk with specific handling recommendations.

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

82.89%
按下载量换算814

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