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prioritizationprioritization 搜索

Agent Skill

prioritization 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。

总安装

1,388

周安装

59

GitHub Stars

160

下载量

486
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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:prioritization(prioritization 搜索)
来源仓库:https://github.com/yonatangross/orchestkit
仓库路径:skills/prioritization
安装命令:
npx skills add https://github.com/yonatangross/orchestkit --skill prioritization
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/yonatangross/orchestkit --skill prioritization

简介

prioritization 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 GitHub 仓库安装使用。
  • 安装前需确认权限范围、维护状态,以及是否触发联网或文件读写操作。
  • 建议结合原始 README 核验具体用法和功能边界。

SKILL.md

Prioritization Frameworks

Score, rank, and justify backlog decisions using the right framework for the situation.

Decision Tree: Which Framework to Use

Do you have a hard deadline or regulatory pressure?
  YES → WSJF (Cost of Delay drives sequencing)
  NO  → Do you have reach/usage data?
          YES → RICE (data-driven, accounts for user reach)
          NO  → Are you in a time-boxed planning session?
                  YES → ICE (fast, 1-10 scales, no data required)
                  NO  → Is this a scope negotiation with stakeholders?
                          YES → MoSCoW (bucket features, control scope creep)
                          NO  → Value-Effort Matrix (quick 2x2 triage)
FrameworkBest ForData RequiredTime to Score
RICEData-rich teams, steady-state prioritizationAnalytics, user counts30-60 min
WSJFSAFe orgs, time-sensitive or regulated workRelative estimates only15-30 min
ICEStartup speed, early validation, quick triageNone5-10 min
MoSCoWScope negotiation, release planningStakeholder input1-2 hours
Value-Effort2x2 visual, quick team alignmentNone10-15 min

RICE

RICE Score = (Reach × Impact × Confidence) / Effort
FactorScaleNotes
ReachActual users/quarterUse analytics; do not estimate
Impact0.25 / 0.5 / 1 / 2 / 3Minimal → Massive per user
Confidence0.3 / 0.5 / 0.8 / 1.0Moonshot → Strong data
EffortPerson-monthsInclude design, eng, QA
## RICE Scoring: [Feature Name]

| Feature     | Reach  | Impact | Confidence | Effort | Score  |
|-------------|--------|--------|------------|--------|--------|
| Smart search| 50,000 | 2      | 0.8        | 3      | 26,667 |
| CSV export  | 10,000 | 0.5    | 1.0        | 0.5    | 10,000 |
| Dark mode   | 30,000 | 0.25   | 1.0        | 1      |  7,500 |

See rules/prioritize-rice.md for ICE, Kano, and full scale tables.


WSJF

WSJF = Cost of Delay / Job Size
Cost of Delay = User Value + Time Criticality + Risk Reduction  (1-21 Fibonacci each)

Higher WSJF = do first. Fibonacci scale (1, 2, 3, 5, 8, 13, 21) forces relative sizing.

## WSJF: GDPR Compliance Update

User Value:       8   (required for EU customers)
Time Criticality: 21  (regulatory deadline this quarter)
Risk Reduction:   13  (avoids significant fines)
Job Size:          8  (medium complexity)

Cost of Delay = 8 + 21 + 13 = 42
WSJF = 42 / 8 = 5.25

See rules/prioritize-wsjf.md for MoSCoW buckets and practical tips. See references/wsjf-guide.md for the full scoring guide.


ICE

ICE Score = Impact × Confidence × Ease    (all factors 1-10)

No user data required. Score relative to other backlog items. Useful for early-stage products and rapid triage sessions.


MoSCoW

Bucket features before estimation. Must-Haves alone should ship a viable product.

## Release 1.0 MoSCoW

### Must Have (~60% of effort)
- [ ] User authentication
- [ ] Core CRUD operations

### Should Have (~20%)
- [ ] Search, export, notifications

### Could Have (~20%)
- [ ] Dark mode, keyboard shortcuts

### Won't Have (documented out-of-scope)
- Mobile app (Release 2.0)
- AI features (Release 2.0)

Opportunity Cost & Trade-Off Analysis

When two items compete for the same team capacity, quantify what delaying each item costs per month.

## Trade-Off: AI Search vs Platform Migration (Q2 eng team)

### Option A: AI Search
- Cost of Delay: $25K/month (competitive risk)
- RICE Score: 18,000
- Effort: 6 weeks

### Option B: Platform Migration
- Cost of Delay: $5K/month (tech debt interest)
- RICE Score: 4,000
- Effort: 8 weeks

### Recommendation
Human decides. Key factors:
1. Q2 OKR: Increase trial-to-paid conversion (favors AI Search)
2. Engineering capacity: Only one team, sequential not parallel
3. Customer commitment: No contractual deadline for either

See rules/prioritize-opportunity-cost.md for the Value-Effort Matrix and full trade-off template. See references/rice-scoring-guide.md for detailed RICE calibration.


Common Pitfalls

PitfallMitigation
Gaming scores to justify pre-decided workCalibrate as a team; document assumptions
Mixing frameworks in one tablePick one framework per planning session
Only tracking high-RICE items; ignoring cost of delayCombine RICE with explicit delay cost analysis
MoSCoW Must-Have bloat (>70% of scope)Must-Haves alone must ship a viable product
Comparing RICE scores across different goalsOnly compare within the same objective

Related Skills

  • product-frameworks — Full PM toolkit (value prop, market sizing, competitive analysis, user research, business case)
  • write-prd — Convert prioritized features into product requirements documents
  • product-analytics — Define and instrument the metrics that feed RICE reach/impact scores
  • okr-design — Set the objectives that determine which KPIs drive RICE impact scoring
  • market-sizing — TAM/SAM/SOM analysis that informs strategic priority
  • competitive-analysis — Competitor context that raises or lowers WSJF time criticality scores

Version: 1.0.0

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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

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按下载量换算184

Claude

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按下载量换算161

Cursor

17.32%
按下载量换算84

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9.42%
按下载量换算46

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