Token导航 LogoToken导航

Agent Skill · 研究检索

scoping-cutting(范围切割)

scoping-cutting 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。

scoping-cutting 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 46,597。

总安装 774周安装 31GitHub Stars 3下载 250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:scoping-cutting(范围切割)
来源仓库:https://github.com/oldwinter/skills
仓库路径:skills/scoping-cutting
安装命令:
npx skills add https://github.com/oldwinter/skills --skill scoping-cutting
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/oldwinter/skills --skill scoping-cutting

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。

用于查找、检索和筛选相关信息,支持关键词和任务场景定位。适合在 Codex、Claude 等宿主中快速获取候选结果。可结合来源仓库 README 核验具体用法和权限范围。安装前建议确认是否会触发联网或文件读写操作。scoping-cutting 属于研究检索类 Skill,可作为该场景下的辅助能力补充。

来源仓库内路径:skills/scoping-cutting

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/oldwinter/skills --skill scoping-cutting;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

scoping-cutting 怎么安装?

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

scoping-cutting 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。

scoping-cutting 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。

scoping-cutting 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。

scoping-cutting 用的人多吗?

公开数据是累计安装 774 次,近一周安装 31 次,下载 250 次,GitHub 3 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。

scoping-cutting 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
scoping-cutting

范围切割 · 本页

7743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

Scoping & Cutting

Scope

Covers

  • Converting a fuzzy initiative into a ship-able slice that fits a fixed time budget (“appetite”)
  • Creating a cut list (what to drop/defer) with explicit trade-offs and rationale
  • Defining an MVP as a hypothesis test (what you’re validating, not just “smaller”)
  • Choosing a Minimum Lovable Slice (viable *and* emotionally resonant) instead of a “barely works” release
  • Using Wizard-of-Oz / concierge approaches to validate value before building full automation
  • Preventing scope creep via explicit non-goals + change control

When to use

  • “Cut scope / descope this feature so we can ship by.”
  • “Define an MVP for this initiative (what hypothesis are we testing?).”
  • “We have 2–6 weeks; what can we ship that still matters?”
  • “Scope creep is killing us; define what’s in/out and how changes happen.”
  • “We need a minimum lovable version, not a compromised mess.”

When NOT to use

  • You don’t yet know what problem you’re solving (use problem-definition)
  • You’re choosing between many competing initiatives (use prioritizing-roadmap)
  • You need a decision-ready PRD with requirements (use writing-prds) or a build-ready design/tech spec (use writing-specs-designs)
  • You’re setting long-term product strategy or vision (use defining-product-vision)

Inputs

Minimum required

  • The initiative/feature and the decision (ship vs defer vs stop) + target date or time budget
  • Target user/segment + the core user journey you want to improve
  • Success metric(s) + 2–5 guardrails (trust, quality, cost, latency, support load)
  • Constraints and non-negotiables (legal/privacy, platform, dependencies, team size)
  • Candidate scope items (bullets are fine) + known unknowns

Missing-info strategy

  • Ask up to 5 questions from references/INTAKE.md.
  • If answers aren’t available, proceed with explicit assumptions and list Open questions that would change the cut decisions.

Outputs (deliverables)

Produce a Scoping & Cutting Pack in Markdown (in-chat; or as files if the user requests):

  1. Context snapshot (decision, date/appetite, stakeholders/DRI, constraints)
  2. Outcome + hypothesis (what must be true; what you’ll validate)
  3. Appetite + success bar (time budget, “done means…”, guardrails)
  4. Minimum Lovable Slice spec (core flow, must-haves, non-goals)
  5. Cut list (cut/defer/keep with rationale + impact on risks)
  6. Validation plan (Wizard-of-Oz/concierge/prototype as needed) + success criteria
  7. Delivery plan (milestones within appetite + scope-change rules)
  8. Risks / Open questions / Next steps (always included)

Templates: references/TEMPLATES.md Expanded guidance: references/WORKFLOW.md

Workflow (8 steps)

1) Intake + decision framing

  • Inputs: User request; references/INTAKE.md.
  • Actions: Clarify the decision, date/appetite, DRI, constraints, and what “shipping” means (where it lands, who uses it).
  • Outputs: Context snapshot.
  • Checks: You can state: “We are deciding to ship by with under.”

2) Define the outcome and hypothesis (MVP = test)

  • Inputs: Context snapshot; current evidence/risks.
  • Actions: Write the outcome in user terms; define the key hypothesis (or 2–3). Choose success metric(s) + guardrails.
  • Outputs: Outcome + hypothesis section; metrics/guardrails.
  • Checks: You can answer: “What will we learn/validate by shipping this slice?”

3) Set appetite (time as a budget) + non-negotiables

  • Inputs: Target date/timebox; constraints; team capacity.
  • Actions: Set a hard time budget (e.g., 2/4/6 weeks). List non-negotiables (policy, privacy, reliability, design constraints).
  • Outputs: Appetite + constraints section.
  • Checks: Appetite is explicit and agreed; scope is the variable, not the deadline.

4) Design the Minimum Lovable Slice (MLS)

  • Inputs: Outcome + constraints; candidate scope items.
  • Actions: Define the smallest end-to-end flow that delivers the core value and feels coherent. Add 1–2 “lovability” elements that increase trust/clarity (not random polish).
  • Outputs: MLS spec (core flow, must-haves, non-goals, assumptions).
  • Checks: The slice is end-to-end (not a partial subsystem) and a user could describe why it’s valuable.

5) Build a cut list with explicit trade-offs

  • Inputs: MLS spec + candidate scope items.
  • Actions: Create a table of items to keep / cut / defer, with rationale tied to outcome, risk, and appetite. Convert “nice-to-haves” into “later” with a clear trigger for revisiting.
  • Outputs: Cut list table + short decision rationale.
  • Checks: Every removed item has a reason; non-goals are as clear as goals.

6) Add a validation plan (Wizard-of-Oz / concierge where helpful)

  • Inputs: Riskiest assumptions; cut list.
  • Actions: Choose the fastest validation method to de-risk the top unknown(s) (manual ops, scripted demo, prototype). Define what data/feedback counts as “validated”.
  • Outputs: Validation plan (method, audience, script, success criteria, timeline).
  • Checks: The plan can run without building the full system; success criteria are defined before running it.

7) Delivery plan + scope-change guardrails

  • Inputs: MLS spec; validation plan; appetite.
  • Actions: Break the work into milestones that fit the appetite. Define scope-change rules (how requests are evaluated; what gets traded off; who decides).
  • Outputs: Delivery plan + scope-change policy.
  • Checks: New scope can only enter by removing or shrinking something else (“trade, don’t add”).

8) Quality gate + finalize

  • Inputs: Full draft pack.
  • Actions: Run references/CHECKLISTS.md and score with references/RUBRIC.md. Ensure Risks / Open questions / Next steps are present with owners.
  • Outputs: Final Scoping & Cutting Pack.
  • Checks: A stakeholder can approve the slice async and the team can execute without re-litigating scope.

Quality gate (required)

Examples

Example 1 (B2B SaaS): “Cut scope for ‘bulk CSV import’ so we can ship a useful version in 4 weeks; include a Wizard-of-Oz validation plan.” Expected: an appetite-based MLS, a cut/defer table, and a validation plan that tests value before building every edge case.

Example 2 (Consumer): “Define a minimum lovable first version of ‘saved searches’ for mobile within a 2-week appetite.” Expected: a coherent end-to-end slice, explicit non-goals, and a scope-change policy to prevent creep.

Boundary example: “Decide what our Q2 roadmap should be across 12 initiatives.” Response: use prioritizing-roadmap first; then apply this skill to right-size the chosen initiative.

平台分布

Codex

36.6%
按下载量换算92

Claude

27.9%
按下载量换算70

Cursor

18.69%
按下载量换算47

Gemini CLI

9.51%
按下载量换算24

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。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