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Agent Skill · 研究检索

prioritization-methods(优先排序方法)

prioritization-methods 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。

prioritization-methods 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,权限为只读;许可证信息还不明确,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 70,176。

总安装 212周安装 9GitHub Stars 80下载 74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:prioritization-methods(优先排序方法)
来源仓库:https://github.com/slgoodrich/agents
仓库路径:skills/prioritization-methods
安装命令:
npx skills add https://github.com/slgoodrich/agents --skill prioritization-methods
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/slgoodrich/agents --skill prioritization-methods

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。

prioritization-methods 用于查找、检索和筛选相关信息。适合在 Codex、Claude、Cursor、Gemini CLI 中根据关键词或任务场景快速定位候选结果。通过 npx skills add 命令从指定仓库安装并使用。安装前需确认权限范围、维护状态,以及是否会触发联网、命令执行或文件读写。

建议结合原始 README 核验具体用法和功能边界。

来源仓库内路径:skills/prioritization-methods

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/slgoodrich/agents --skill prioritization-metho…;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

    它标注为只读,先用只读任务试一次,确认行为符合预期再扩大使用范围。

常见问题

6 条

prioritization-methods 怎么安装?

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

prioritization-methods 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。

prioritization-methods 需要什么权限?

权限级别是只读。该 Skill 主要提供规则、说明或参考内容,本身偏只读;真正读写文件、联网或执行命令仍取决于宿主 Agent 的任务。

prioritization-methods 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。

prioritization-methods 用的人多吗?

公开数据是累计安装 212 次,近一周安装 9 次,下载 74 次,GitHub 80 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。

prioritization-methods 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

  • 同时适配 4 种工具,换客户端不用重新找替代品。
  • 第三方扫描已通过,常见的高风险行为没有命中。
  • 标注为只读权限,试用阶段不容易误改本地文件。

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。
  • 只想先试试效果、不希望它改动本地文件的人。

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
prioritization-methods

优先排序方法 · 本页

21280只读未明确通过

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

Prioritization Methods & Frameworks

Overview

Data-driven frameworks for feature prioritization, backlog ranking, and MVP scoping. Choose the right framework based on your context: data availability, team size, and decision type.

When to Use This Skill

Auto-loaded by agents:

  • feature-prioritizer - For RICE/ICE scoring, MVP scoping, and backlog ranking

Use when you need:

  • Choosing between competing features
  • Building quarterly roadmaps
  • Backlog prioritization
  • Saying "no" with evidence
  • Clear prioritization decisions
  • Resource allocation decisions
  • MVP scoping decisions

Seven Core Frameworks

1. RICE Scoring (Intercom)

Formula: (Reach × Impact × Confidence) / Effort

Best for: Large backlogs (20+ items) with quantitative data

Components:

  • Reach: Users impacted per quarter
  • Impact: 0.25 (minimal) to 3 (massive)
  • Confidence: 50% (low data) to 100% (high data)
  • Effort: Person-months to ship

Example:

Dark Mode: (10,000 × 2.0 × 0.80) / 1.5 = 10,667

When to use: Post-PMF with metrics, need defendable priorities, data-driven culture

Template: assets/rice-scoring-template.md


2. ICE Scoring (Sean Ellis)

Formula: (Impact + Confidence + Ease) / 3

Best for: Quick experiments, early-stage products, limited data

Components (each 1-10):

  • Impact: How much will this move the needle?
  • Confidence: How sure are we?
  • Ease: How simple to implement?

Example:

Email Notifications: (8 + 9 + 7) / 3 = 8.0

When to use: Growth experiments, startups, need speed over rigor

Template: assets/ice-scoring-template.md


3. Value vs Effort Matrix (2×2)

Quadrants:

  • Quick Wins (high value, low effort) - Do first
  • Big Bets (high value, high effort) - Strategic
  • Fill-Ins (low value, low effort) - If capacity
  • Time Sinks (low value, high effort) - Avoid

Best for: Visual presentations, portfolio planning, quick assessments

When to use: Clear communication, strategic planning, need visualization

Template: assets/value-effort-matrix-template.md


4. MoSCoW Method

Categories:

  • Must Have (60%) - Critical for launch
  • Should Have (20%) - Important but not critical
  • Could Have (20%) - Nice-to-have
  • Won't Have - Explicitly out of scope

Best for: MVP scoping, release planning, clear scope decisions

When to use: Fixed timeline, need to cut scope, binary go/no-go decisions

Template: assets/moscow-prioritization-template.md


5. Kano Model

Categories:

  • Basic Needs (Must-Be): Expected, dissatisfiers if absent
  • Performance Needs: More is better, linear satisfaction
  • Excitement Needs (Delighters): Unexpected joy
  • Indifferent: Users don't care
  • Reverse: Users prefer without it

Best for: Understanding user expectations, competitive positioning, roadmap sequencing

When to use: Strategic planning, differentiation strategy, multi-release planning

Template: assets/kano-model-template.md


6. Weighted Scoring

Process:

  1. Define criteria (User Value, Revenue, Strategic Fit, Effort)
  2. Assign weights (must sum to 100%)
  3. Score features (1-10) on each criterion
  4. Calculate weighted score

Example:

Criteria: User Value 40%, Revenue 30%, Strategic 20%, Ease 10%
Feature: (8 × 0.40) + (6 × 0.30) + (9 × 0.20) + (5 × 0.10) = 7.3

Best for: Multiple criteria, complex trade-offs, custom needs

When to use: Balancing priorities, transparent decisions

Template: assets/weighted-scoring-template.md


7. Opportunity Scoring (Jobs-to-be-Done)

Formula: Importance + Max(Importance - Satisfaction, 0)

Process:

  1. Identify customer jobs (outcomes, not features)
  2. Survey: Rate importance (1-5) and satisfaction (1-5)
  3. Calculate opportunity = importance + gap
  4. Prioritize high-opportunity jobs (>7.0)

Best for: Outcome-driven innovation, understanding underserved needs, feature gap analysis

When to use: JTBD methodology, finding innovation opportunities, validation

Template: assets/opportunity-scoring-template.md


Choosing the Right Framework

Need speed? → ICE (fastest)

Have user data? → RICE (most rigorous)

Visual presentation? → Value/Effort (clear visualization)

MVP scoping? → MoSCoW (forces cuts)

User expectations? → Kano (strategic insights)

Complex criteria? → Weighted Scoring (custom)

Outcome-focused? → Opportunity Scoring (JTBD)

Detailed comparison: references/framework-selection-guide.md

Complete decision tree, framework comparison table, combining strategies


Best Practices

1. Be Consistent

  • Use same framework across team
  • Document assumptions explicitly
  • Update scores as you learn

2. Combine Frameworks

  • RICE for ranking + Value/Effort for visualization
  • MoSCoW for release + RICE for roadmap
  • Kano for strategy + ICE for tactics

3. Avoid Common Pitfalls

  • Don't prioritize by HiPPO (Highest Paid Person's Opinion)
  • Don't ignore effort (value alone insufficient)
  • Don't set-and-forget (re-prioritize regularly)
  • Don't game the system (honest scoring)

4. Clear Communication

  • Show your work (transparent criteria)
  • Visualize priorities clearly
  • Explain trade-offs explicitly
  • Document "why not" for rejected items

5. Iterate and Learn

  • Track actual vs estimated impact
  • Refine scoring over time
  • Calibrate team estimates
  • Learn from misses

Templates and References

Assets (Ready-to-Use Templates)

Copy-paste these for immediate use:

  • assets/rice-scoring-template.md - Reach × Impact × Confidence / Effort
  • assets/ice-scoring-template.md - Impact + Confidence + Ease / 3
  • assets/value-effort-matrix-template.md - 2×2 visualization
  • assets/moscow-prioritization-template.md - Must/Should/Could/Won't
  • assets/kano-model-template.md - Expectation analysis
  • assets/weighted-scoring-template.md - Custom criteria scoring
  • assets/opportunity-scoring-template.md - Jobs-to-be-done prioritization

References (Deep Dives)

When you need comprehensive guidance:

  • references/framework-selection-guide.md - Choose the right framework, comparison table, combining strategies, decision tree

Quick Reference

Problem: Too many features, limited resources
Solution: Use prioritization framework

Context-Based Selection:
├─ Lots of data? → RICE
├─ Need speed? → ICE
├─ Visual presentation? → Value/Effort
├─ MVP scoping? → MoSCoW
├─ User expectations? → Kano
├─ Complex criteria? → Weighted Scoring
└─ Outcome-focused? → Opportunity Scoring

Always: Document, communicate, iterate

Resources

Books:

  • "Intercom on Product Management" (RICE framework)
  • "Hacking Growth" by Sean Ellis (ICE scoring)
  • "Jobs to be Done" by Anthony Ulwick (Opportunity scoring)

Tools:

  • Airtable/Notion for scoring
  • ProductPlan for roadmaps
  • Aha!, ProductBoard for frameworks

Articles:

  • "RICE: Simple prioritization for product managers" - Intercom
  • "How to use ICE Scoring" - Sean Ellis
  • "The Kano Model" - UX Magazine

Troubleshooting

"Everything scores the same priority": Your scoring criteria are too coarse. Increase granularity -- use 1-10 instead of 1-5. Or you're not differentiating on Effort enough. Recalibrate by anchoring your highest and lowest items first, then score the rest relative to those.

"Stakeholders disagree on scores": Use the framework as a discussion tool, not a calculator. When scores diverge, the value is in surfacing the disagreement, not resolving it with math. Have stakeholders defend their scores, then converge.

"I don't know which framework to pick": Start with RICE. It's the most widely applicable. Switch to Kano if you need to understand customer delight vs. expectations, or MoSCoW if you need a quick yes/no cut for a deadline.


Related Skills

  • roadmap-frameworks - Turn priorities into roadmaps
  • specification-techniques - Spec prioritized features
  • product-positioning - Strategic positioning and differentiation

Key Principle: Choose one framework, use it consistently, iterate. Don't over-analyze - prioritization should enable decisions, not paralyze them.

平台分布

Codex

34.19%
按下载量换算25

Claude

28.07%
按下载量换算21

Cursor

18.58%
按下载量换算14

Gemini CLI

9.59%
按下载量换算7

安全审计

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权限和风险

只读

该 Skill 主要提供规则、说明或参考内容,本身偏只读;真正读写文件、联网或执行命令仍取决于宿主 Agent 的任务。

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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