Token导航 LogoToken导航

Agent Skill · 开发

decision-frameworks(决策框架)

decision-frameworks 用于辅助前端页面、组件、样式和交互逻辑开发,适合在 OpenClaw 中需要维护前端项目、生成组件或检查界面实现时使用。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。

decision-frameworks 是开发类 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,第三方扫描有提醒项,按安装量在开发类的 21,746 个 Skill 里排第 741。

总安装 59,526周安装 2,408GitHub Stars 公开资料未说明下载 18,686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:decision-frameworks(决策框架)
来源仓库:https://github.com/wpank/decision-frameworks
安装命令:
openclaw skills install decision-frameworks
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 decision-frameworks

这个 Skill 是做什么的

开发类 Skill 面向写代码、改代码和排查问题,一般会读写仓库文件,部分还会执行构建或测试命令。

常见工程选择的结构化决策模式 - 库选择、架构、构建与购买、优先级、可逆性分析和 ADR。在工具、架构或方法之间进行选择时,或者在记录技术决策时使用。

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 decision-frameworks;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

decision-frameworks 怎么安装?

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

decision-frameworks 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。

decision-frameworks 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。

decision-frameworks 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。

decision-frameworks 用的人多吗?

公开数据是累计安装 59,526 次,近一周安装 2,408 次,下载 18,686 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。

decision-frameworks 安全吗?

第三方扫描有提醒项,说明存在需要人工确认的行为。安装前请打开源码看清它读了什么、联网到哪里。

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。

先想清楚的地方

  • 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 OpenClaw,想直接扩展它能力的人。
  • 需要处理开发类任务、又不想每次都手写提示词的人。

不太适合

  • 需要厂商级技术支持和 SLA 的生产系统。

开发类 Skill 对比

6 个同类
Skill总安装GitHub 星权限许可证扫描
skill-vetter

技能审查员 · OpenClaw

8,779,018986操作浏览器MIT-0通过
ontology

本体论 · OpenClaw

6,636,960576只读MIT-0通过
entra-app-registration

内部应用程序注册 · Codex、Claude

6,631,872764接触敏感数据未明确通过
entra-app-registration

内部应用程序注册 · Codex、Claude

3,757,680201接触敏感数据未明确通过
nano-banana-pro

纳米香蕉专业版 · OpenClaw

3,526,898364接触敏感数据MIT-0有提醒
decision-frameworks

决策框架 · 本页

59,526—需要联网MIT-0有提醒

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
decision-frameworks
model
reasoning
description
Structured decision-making patterns for common engineering choices — library selection, architecture, build vs buy, prioritization, reversibility analysis, and ADRs. Use when choosing between tools, architectures, or approaches, or when documenting technical decisions.

Decision Frameworks (Meta-Skill)

Structured approaches for making engineering decisions with confidence and traceability.

Installation

OpenClaw / Moltbot / Clawbot

npx clawhub@latest install decision-frameworks

When to Use

  • Choosing between libraries, frameworks, or tools
  • Facing a build-vs-buy decision
  • Selecting an architecture pattern (monolith vs microservices, SQL vs NoSQL, etc.)
  • Multiple valid options exist and the team needs alignment
  • Prioritizing a backlog or technical roadmap
  • Documenting a significant technical decision for future reference

Decision Matrix Template

Use a weighted scoring matrix when comparing 3+ options across measurable criteria.

CriteriaWeightOption AOption BOption C
Performance54 (20)3 (15)5 (25)
Developer Experience45 (20)4 (16)3 (12)
Community Support35 (15)3 (9)2 (6)
Learning Curve33 (9)4 (12)2 (6)
Cost25 (10)3 (6)4 (8)
Total745857

How to use:

  1. List criteria relevant to the decision
  2. Assign weights (1-5) based on project priorities
  3. Score each option per criterion (1-5)
  4. Multiply score x weight, sum per option
  5. Highest total wins — but sanity-check the result against gut feel

Build vs Buy Framework

Follow this decision tree:

Is it a core differentiator for your product?
├── YES → Build it (own the competitive advantage)
└── NO
    ├── Does a mature, well-maintained solution exist?
    │   ├── YES → Buy / adopt it
    │   └── NO → Build, but keep it minimal
    └── Is the integration cost higher than building?
        ├── YES → Build
        └── NO → Buy / adopt

Factor comparison:

FactorBuildBuy / Adopt
Maintenance costOngoing — your team owns itVendor/community maintains it
CustomizationUnlimited flexibilityLimited to extension points
Time to marketSlower — development requiredFaster — ready-made
Team expertiseMust have or acquire skillsAbstracted away
Long-term costScales with internal capacityLicense/subscription fees
Vendor lock-in riskNoneMedium to high
Security controlFull audit capabilityDependent on vendor transparency

Library / Framework Selection

Evaluate candidate libraries against these criteria before adopting:

CriterionWhat to CheckRed Flag
Maintenance activityCommits in last 90 days, open issues trendNo commits in 6+ months
Community sizeGitHub stars, npm weekly downloads, Discord/forum< 1k weekly downloads for critical lib
Bundle sizeBundlephobia, tree-shaking support> 50 KB gzipped for a utility lib
TypeScript supportBuilt-in types vs DefinitelyTyped, type qualityNo types or outdated @types
Breaking change historyChangelog, semver adherence, migration guidesFrequent majors without guides
LicenseOSI-approved, compatible with your projectAGPL in a SaaS product, no license
Security auditSnyk/Socket score, CVE history, dependency depthKnown unpatched CVEs
Documentation qualityGetting started guide, API reference, examplesREADME-only, no examples

Quick heuristic: If you cannot replace the library within one sprint, treat the decision as a one-way door (see Reversibility Check below).


Architecture Decision Framework

Use these tradeoff tables when choosing between architectural approaches.

Monolith vs Microservices

FactorMonolithMicroservices
ComplexityLow at start, grows over timeHigh from day one
DeploymentSingle artifactIndependent per service
Team scalingHarder beyond 10-15 engineersEnables autonomous teams
Data consistencyACID transactionsEventual consistency, sagas
DebuggingSingle process, easy tracingDistributed tracing required
Best whenEarly-stage, small team, MVPProven domain boundaries, scale needs

SQL vs NoSQL

FactorSQL (Relational)NoSQL (Document/Key-Value)
SchemaStrict, enforcedFlexible, schema-on-read
RelationshipsNative joins, foreign keysDenormalized, application-level joins
ScalingVertical (read replicas help)Horizontal by design
ConsistencyStrong (ACID)Tunable (eventual to strong)
Query flexibilityAd-hoc queries, aggregationsLimited to access patterns
Best whenComplex relations, reportingHigh write volume, flexible schema

REST vs GraphQL

FactorRESTGraphQL
SimplicitySimple, well-understoodSchema definition required
Over/under-fetchingCommon — multiple endpointsClients request exact fields
CachingHTTP caching built-inRequires custom caching layer
ToolingMature ecosystemGrowing — Apollo, Relay, urql
VersioningURL or header versioningSchema evolution, deprecation
Best whenCRUD APIs, public APIsComplex UIs, mobile + web clients

SSR vs CSR vs SSG

FactorSSRCSRSSG
Initial loadFast (HTML from server)Slow (JS bundle parse)Fastest (pre-built HTML)
SEOExcellentPoor without hydrationExcellent
Best whenPersonalized pagesDashboards, SPAsBlogs, docs, marketing

Monorepo vs Polyrepo

FactorMonorepoPolyrepo
Code sharingTrivial — same repoRequires published packages
CI/CD complexityNeeds smart filtering (Turborepo)Simple per-repo pipelines
Best whenShared libs, aligned releasesIndependent teams, different stacks

Priority Matrices — RICE Scoring

Score and rank features/tasks:

RICE Score = (Reach x Impact x Confidence) / Effort
FactorScale
ReachNumber of users/events affected per quarter
Impact3 = massive, 2 = high, 1 = medium, 0.5 = low, 0.25 = minimal
Confidence100% = high, 80% = medium, 50% = low
EffortPerson-weeks (or person-sprints)

MoSCoW Method

CategoryMeaningBudget Target
MustNon-negotiable for this release~60% of effort
ShouldImportant but not critical~20% of effort
CouldDesirable if time permits~15% of effort
Won'tExplicitly out of scope (this time)~5% (planning)

Reversibility Check

Classify every significant decision as a one-way or two-way door.

AspectOne-Way Door (Type 1)Two-Way Door (Type 2)
DefinitionIrreversible or very costly to undoEasily reversed with low cost
ExamplesDatabase engine migration, public API contract, language rewriteUI framework for internal tool, feature flag experiment, library swap behind interface
How to identifyWould reverting require > 1 sprint of rework? Data migration? Customer communication?Can you revert with a config change, flag toggle, or single PR?
ApproachInvest in analysis, prototype, get stakeholder sign-offDecide fast, ship, measure, iterate
Time to decideDays to weeks — thorough evaluationHours — bias toward action

Rule of thumb: Wrap risky choices behind interfaces/abstractions. This converts many one-way doors into two-way doors by isolating the implementation from consumers.


ADR Template

Document significant decisions using a lightweight Architecture Decision Record.

# ADR-NNNN: [Short Title]

## Status
[Proposed | Accepted | Deprecated | Superseded by ADR-XXXX]

## Context
What is the problem or situation that motivates this decision?
Include constraints, requirements, and forces at play.

## Decision
What is the change being proposed or adopted?
State the decision clearly and concisely.

## Consequences

### Positive
- [Benefit 1]
- [Benefit 2]

### Negative
- [Tradeoff 1]
- [Tradeoff 2]

### Risks
- [Risk and mitigation]

Store in docs/adr/ or decisions/. Number sequentially. Never delete — mark superseded. Review during onboarding and quarterly audits.


Anti-Patterns

Anti-PatternDescriptionCounter
Analysis ParalysisEndless evaluation, no decision madeSet a decision deadline; use the matrix
HiPPOHighest Paid Person's Opinion overrides dataRequire data or a scored matrix for all options
Sunk Cost FallacyContinuing because of past investment, not future valueEvaluate options as if starting fresh today
Bandwagon EffectChoosing because "everyone uses it"Score against your actual criteria
Premature OptimizationOptimizing before measuring or validating needProfile first; optimize only proven bottlenecks
Resume-Driven DevelopmentPicking tech to pad a resume, not to solve the problemAlign choices with team skills and project goals
Not Invented HereRejecting external solutions out of prideRun the Build vs Buy framework honestly

NEVER Do

  1. NEVER skip writing down the decision — undocumented decisions get relitigated endlessly
  2. NEVER decide by committee without a single owner — assign a DRI (Directly Responsible Individual)
  3. NEVER treat all decisions as equal weight — classify by reversibility and impact first
  4. NEVER ignore second-order effects — ask "and then what?" at least twice
  5. NEVER lock in without an exit plan — define how you would migrate away before committing
  6. NEVER conflate familiarity with superiority — evaluate on criteria, not comfort
  7. NEVER defer a one-way door decision indefinitely — the cost of delay often exceeds the cost of a wrong choice

平台分布

OpenClaw

92.27%
按下载量换算17,242

安全审计

VirusTotal

可疑

ClawScan

通过

Static analysis

未展示

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。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。

继续浏览同类 Skills