Token导航 LogoToken导航TokenDH.com
运维和基础设施需要联网github未标认证来源可访问许可证需确认审计通过

plan-interview计划面试

Agent Skill

plan-interview 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

3,469

周安装

146

GitHub Stars

126

下载量

1,215
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:plan-interview(计划面试)
来源仓库:https://github.com/secondsky/claude-skills
仓库路径:skills/plan-interview
安装命令:
npx skills add https://github.com/secondsky/claude-skills --skill plan-interview
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/secondsky/claude-skills --skill plan-interview

简介

用于处理 GitHub 仓库与协作流程信息。

  • 适合围绕 Issue、PR 和代码变更进行整理与分析。
  • 使用时需提供具体仓库路径或变更上下文。plan-interview 属于运维和基础设施类 Skill,可作为该场景下的辅助能力补充。
  • 安装前应确认是否有网络访问和文件操作权限。
  • 建议结合原始 README 了解支持的命令和操作限制。

SKILL.md

Plan Interview Skill

Transform rough plans into comprehensive, implementation-ready specifications through adaptive, structured interviews.

When to Use

  • Converting a plan or idea into a detailed specification
  • Gathering requirements through structured questioning
  • Transforming rough documentation into implementation-ready specs
  • Ensuring all edge cases, risks, and stakeholders are considered before implementation

Available Components

Command: /plan-interview:interview [plan-file]

Adaptive interview that calibrates depth based on plan complexity:

ComplexitySignalsQuestions
SimpleSingle feature, clear scope10-15
ModerateMulti-component, some integrations18-23
ComplexCross-system, many stakeholders22-28

Usage:

/plan-interview:interview docs/feature-plan.md
# Output: docs/feature-plan-spec.md

Agent: spec-reviewer

Autonomous quality analysis of specifications across 4 dimensions:

  • Completeness (25 pts) - All sections populated?
  • Consistency (25 pts) - No contradictions?
  • Clarity (25 pts) - No ambiguous language?
  • Edge Cases (25 pts) - Error handling defined?

Triggers when you say "review my spec" or "check specification quality".

Interview Phases

  1. Foundations & Scope - Stakeholders, success criteria, constraints, MVP scope
  2. Technical Deep-Dive - Architecture, data models, scalability, security
  3. User Experience - Personas, flows, cognitive load, error recovery
  4. Risks & Tradeoffs - Risk categorization, blast radius, contingency plans
  5. Operationalization - Testing, deployment, monitoring
  6. Wrap-Up (optional) - Only for complex plans with remaining gaps

Interview Philosophy

Core Principle: Depth over breadth. Better to deeply understand critical aspects than superficially cover everything.

Key Techniques:

  • Non-obvious questions - Skip what the plan already answers
  • Edge probing - What happens in unusual cases?
  • Assumption surfacing - Make implicit beliefs explicit
  • Contradiction detection - Flag when answers don't align
  • Adaptive depth - Probe deeper on complex areas, move faster on clear ones

Spec Output Structure

Generated specs include:

  • Overview (problem, solution, success criteria, stakeholders)
  • Functional and non-functional requirements
  • Technical design (architecture, data models, APIs, security)
  • User experience (personas, flows, states, edge cases)
  • Risks and mitigations (risk register, tradeoffs, contingency plans)
  • Implementation notes (key decisions, dependencies, migration)
  • Operationalization (testing, deployment, monitoring)
  • Open questions and out-of-scope items
  • Phasing (MVP vs future)

References

Load these for deeper guidance during interviews:

  • references/phase-1-clarifications.md - Foundations questions and pitfalls
  • references/phase-2-technical.md - Architecture discussion patterns
  • references/phase-3-ux.md - Persona development, UX patterns
  • references/phase-4-risks.md - Risk assessment frameworks
  • references/interview-techniques.md - Cross-cutting interview skills
  • references/example-spec.md - Annotated high-quality spec example

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

35.04%
按下载量换算426

Claude

33.13%
按下载量换算403

Cursor

17.36%
按下载量换算211

Gemini CLI

9.83%
按下载量换算119

安全审计

Gen Agent Trust Hub

通过

Socket

通过

Snyk

通过

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。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

继续浏览同类 Skills