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feature-prioritisation功能优先级

Agent Skill

feature-prioritisation 用于处理 GitHub 仓库、Issue、Pull Request 和代码协作信息,适合在 Codex、Claude、Cursor、Gemini CLI 中需要围绕仓库状态、代码变更或协作事项进行整理时使用。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。

总安装

210

周安装

9

GitHub Stars

283

下载量

73
CodexClaudeCursorGemini CLI

安装说明

本站只整理中文说明和来源信息,不托管安装包,也不代用户安装。

GitHub

来源数

2

许可证

unknown

最后核验

2026-05-01

来源状态

来源可访问

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:feature-prioritisation(功能优先级)
来源仓库:https://github.com/mohitagw15856/pm-claude-skills
仓库路径:skills/feature-prioritisation
安装命令:
npx skills add https://github.com/mohitagw15856/pm-claude-skills --skill feature-prioritisation
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/mohitagw15856/pm-claude-skills --skill feature-prioritisation

简介

应用 RICE、MoSCoW 等框架对 backlog 进行客观排序。

  • 根据团队规模与目标推荐合适方法,输出带理由的优先级列表。
  • 需输入功能清单与优先目标,自动选择框架并计算得分。
  • 适用于产品负责人应对多源需求竞争有限资源。
  • feature-prioritisation 属于待分类类 Skill,可作为该场景下的辅助能力补充。

SKILL.md

Feature Prioritisation Skill

Apply the right prioritisation framework to any backlog and produce a clear, defensible ranking with rationale — not just a sorted list.

Required Inputs

Ask the user for these if not provided:

  • List of features or initiatives to prioritise
  • Goal or metric being prioritised against (OKR, launch, sprint)
  • Preferred framework (or recommend based on context below)
  • Team data: reach estimates, effort estimates, velocity (for RICE)

Framework Selection Guide

Ask the user which framework they prefer, or recommend based on context:

SituationRecommended Framework
Need a quick, data-driven scoreRICE
Stakeholder alignment meetingMoSCoW
Understanding customer delight vs expectationsKano
Early-stage startup, fast decisionsICE
Identifying underserved customer needsOpportunity Scoring
Strategic portfolio decisionsValue vs Effort Matrix

RICE Scoring

Formula: (Reach × Impact × Confidence) ÷ Effort

FactorDefinitionScale
ReachUsers impacted per quarterActual number
ImpactEffect on goal per user0.25 / 0.5 / 1 / 2 / 3
ConfidenceHow certain are you?50% / 80% / 100%
EffortPerson-months requiredActual number

Output table:

FeatureReachImpactConfidenceEffortRICE ScorePriority

MoSCoW Method

Categorise each feature as:

  • Must Have — non-negotiable for launch/sprint; product fails without it
  • Should Have — important but not critical; workarounds exist
  • Could Have — nice to have; include only if time allows
  • Won't Have (this time) — explicitly out of scope now; may revisit

Always ask: "Must have for *what*?" — define the scope (launch, sprint, quarter) before categorising.


ICE Scoring (Startup/fast mode)

Formula: Impact + Confidence + Ease (each 1–10)

Quick, subjective — good for early decisions before data exists.


Kano Model

Classify features into:

  • Basic (Must-be): Expected; absence causes dissatisfaction
  • Performance: More = better satisfaction; linear relationship
  • Excitement (Delighters): Unexpected; creates delight; absence is neutral
  • Indifferent: Users don't care either way
  • Reverse: Some users want it, others don't

Recommend building: all Basic features first → Performance features for key use cases → 1–2 Excitement features per release.


Output Format

Feature Prioritisation — [Product/Team] — [Date]

Framework Used: [RICE / MoSCoW / ICE / Kano / Custom] Scope: [Sprint / Quarter / Release] Goal being prioritised against: [Metric or objective]

[Scored table using selected framework]

Recommended Build Order:

  1. [Feature] — [1-line rationale]
  2. [Feature] — [1-line rationale]
  3. ...

Explicitly Deprioritised:

  • [Feature] — Reason: [brief]

Assumptions Made:

  • [Any estimates or judgements used in scoring]

Guidelines

  • Always anchor prioritisation to a specific goal or metric — never prioritise in a vacuum
  • Flag when two features have similar scores but very different risk profiles
  • If stakeholder politics are influencing prioritisation, name it explicitly and suggest separating the framework score from the final decision
  • Recommend revisiting priorities every 2 weeks minimum
  • Never produce a single-column ranked list without rationale — explain the top 3 and bottom 3 decisions

Quality Checks

  • Every item is scored against the same goal or metric (not different goals per item)
  • Deprioritised items are explicitly listed with reasons (not just absent from the ranked list)
  • Assumptions used in scoring are documented
  • Stakeholder politics or personal preferences are separated from framework score
  • Prioritisation is anchored to a specific scope (sprint / quarter / launch)

适合场景

01

用户想查找某类 Agent Skill 时

02

需要根据任务场景推荐可安装能力包时

03

需要对比不同来源的安装命令和来源信息时

能力概览

能力 1

按任务关键词查找相关 Skills

能力 2

展示可复制的安装命令

能力 3

保留来源站点、仓库和原始说明,方便继续核验

能力 4

展示第三方安全扫描或审计结果

安装后应在对应宿主中按原始 README 的触发条件使用;具体调用方式请以来源页面和 README 为准。

平台分布

Codex

38.09%
按下载量换算28

Claude

28.85%
按下载量换算21

Cursor

19.19%
按下载量换算14

Gemini CLI

9.28%
按下载量换算7

安全审计

Gen Agent Trust Hub

通过

Socket

通过

Snyk

通过

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。当前只有一个来源,正式发布前建议补源仓库或其他目录站核验。

来源信息

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