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values-behavioral-interview(价值观行为面试)

values-behavioral-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。

values-behavioral-interview 是待分类类 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,按安装量在待分类类的 11,209 个 Skill 里排第 2,595。

总安装 1,493周安装 61GitHub Stars 98下载 483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。
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安装方式

通过对话安装

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请帮我安装这个 Agent Skill:values-behavioral-interview(价值观行为面试)
来源仓库:https://github.com/erichowens/some_claude_skills
仓库路径:skills/values-behavioral-interview
安装命令:
npx skills add https://github.com/erichowens/some_claude_skills --skill values-behavioral-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/erichowens/some_claude_skills --skill values-behavioral-interview

这个 Skill 是做什么的

这个 Skill 的分类还没最终确定,用法以来源仓库的说明为准。

values-behavioral-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 中围绕仓库状态、代码变更或协作事项进行整理。

通过 npx skills add 命令从指定仓库安装,需结合原始 README 确认具体用法。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。当前暂无更多功能细节,可参考来源仓库进一步了解实现逻辑和使用示例。

来源仓库内路径:skills/values-behavioral-interview

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/erichowens/some_claude_skills --skill values-b…;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

values-behavioral-interview 怎么安装?

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

values-behavioral-interview 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。

values-behavioral-interview 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。

values-behavioral-interview 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。

values-behavioral-interview 用的人多吗?

公开数据是累计安装 1,493 次,近一周安装 61 次,下载 483 次,GitHub 98 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。

values-behavioral-interview 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。
  • 需要处理待分类类任务、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。

待分类类 Skill 对比

6 个同类
Skill总安装GitHub 星权限许可证扫描
infsh-cli

infsh CLI · Codex、Claude

4,374,576382权限未标注未明确未收录
ai-video-generation

AI 视频生成 · Codex、Claude

4,313,376382调用外部服务未明确有提醒
lark-openapi-explorer

云雀 OpenAPI 浏览器 · Codex、Claude

2,064,1209,011需要联网未明确有提醒
lark-workflow-standup-report

Lark 工作流程站立报告 · Codex、Claude

2,041,6328,978需要联网未明确通过
use-my-browser

使用我的浏览器 · Codex、Claude

1,848,49140操作浏览器未明确未通过
values-behavioral-interview

价值观行为面试 · 本页

1,49398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

Values & Behavioral Interview

Preparation system for behavioral and values-fit interview rounds at mission-driven AI companies, with particular depth on Anthropic's approach. These rounds are NOT standard "tell me about a time" STAR interviews. They go deeper: negative framing, 5-6 layers of follow-up, genuine self-awareness testing, and mission alignment probing.

The core insight: interviewers are not listening to your story. They are listening to how you think about your story.


When to Use

Use for:

  • Preparing for culture-fit or values rounds at any company
  • Building a story bank with STAR-L structure (extended with Learning)
  • Practicing negative-frame questions (failures, weaknesses, disagreements)
  • Developing comfort with deep introspective follow-ups
  • Aligning personal narrative with company mission
  • Calibrating authenticity vs. preparation balance

NOT for:

  • Coding interview practice (use senior-coding-interview)
  • System design rounds (use ml-system-design-interview)
  • Resume or CV creation (use cv-creator)
  • Raw career story extraction (use career-biographer)
  • Technical deep dive preparation (use anthropic-technical-deep-dive)

Question Category Map

mindmap
  root((Values Interview))
    Failure & Learning
      Project failures
      Wrong decisions
      Missed signals
      Recovery process
    Conflict & Disagreement
      Manager disagreements
      Peer conflicts
      Technical debates
      Escalation decisions
    Mission & Motivation
      Why this company
      Why AI safety
      Long-term vision
      Personal connection
    Self-Awareness & Growth
      Blind spots
      Feedback received
      Changed opinions
      Working style
    Ethics & Trade-offs
      Competing priorities
      Uncomfortable decisions
      Integrity tests
      Gray areas
    Ambiguity & Uncertainty
      Incomplete information
      Changing requirements
      No right answer
      Comfort with unknown

The Follow-Up Ladder

Every strong values interviewer drills past your prepared surface answer. Expect 5-6 levels of depth on a single story. If your preparation only covers levels 1-3, you will be exposed.

flowchart TD
    S["Surface<br/><i>'Tell me about a failure'</i>"] --> C
    C["Context<br/><i>'What was the situation exactly?'</i>"] --> D
    D["Decision<br/><i>'What did you decide to do and why?'</i>"] --> T
    T["Tradeoff<br/><i>'What did you sacrifice? What was the cost?'</i>"] --> M
    M["Meta-Reflection<br/><i>'What did that teach you about yourself?'</i>"] --> W
    W["Worldview<br/><i>'How did that change how you approach similar situations?'</i>"]

    style S fill:#e8e8e8,stroke:#333,color:#000
    style C fill:#d0d0d0,stroke:#333,color:#000
    style D fill:#b8b8b8,stroke:#333,color:#000
    style T fill:#a0a0a0,stroke:#333,color:#000
    style M fill:#888888,stroke:#333,color:#fff
    style W fill:#505050,stroke:#333,color:#fff

Preparation rule: For every story in your bank, you must have a prepared (but natural) answer at each level. If you can only get to level 3, the story is not ready.

Level-by-Level Preparation

LevelWhat Interviewer ProbesWhat Strong Answers Include
SurfaceCan you identify a relevant experience?Specific, time-bounded story with stakes
ContextDo you understand the forces at play?Multiple stakeholders, constraints, timeline pressure
DecisionDid you act with agency?Clear reasoning, alternatives considered, ownership
TradeoffDo you acknowledge costs?What was lost, who was affected, what you would do differently
Meta-ReflectionDo you know yourself?Genuine insight about a pattern, tendency, or blind spot
WorldviewHas experience shaped your judgment?A principle or heuristic you now carry forward

STAR-L Format

Extend the standard STAR framework with Learning -- the layer that separates good answers from memorable ones.

ComponentStandard STARSTAR-L Extension
SituationWhat happenedSame, but include emotional state and stakes
TaskWhat was your jobSame, but include why it mattered and to whom
ActionWhat you didSame, but include what you considered and rejected
ResultWhat happenedSame, but include costs and unintended consequences
Learning(missing)What changed in how you think, decide, or lead

STAR-L Example Structure

Situation: "In Q3 2024, our team shipped a recommendation model that
           performed well in A/B tests but created filter bubbles we
           didn't measure for..."

Task:      "As the tech lead, I owned the decision to ship or revert,
           with $2M/quarter in projected revenue on the line..."

Action:    "I proposed a middle path -- keep the model but add diversity
           constraints. My manager wanted to ship as-is. I escalated to
           the VP with a one-page analysis of downstream risks..."

Result:    "We shipped with constraints. Revenue impact was 60% of the
           unconstrained model. My manager was frustrated for weeks.
           The VP later cited it as the right call when a competitor
           got press coverage for their filter bubble problem..."

Learning:  "I learned that I default to quantitative arguments when the
           real issue is values-based. The revenue comparison was a
           crutch. The stronger argument was 'this is who we want to
           be as a company.' I now lead with values framing when the
           decision involves user welfare."

Story Bank Requirements

Build a bank of 8-12 stories that cover the full question category spread. Each story should be adaptable to multiple question types.

Required Story Categories

#CategoryExample PromptWhat It Tests
1Genuine project failure"Tell me about something that failed"Accountability, learning from loss
2Manager/leadership disagreement"When did you disagree with your boss?"Courage, judgment, conflict style
3Changed a deeply held opinion"When were you wrong about something important?"Intellectual humility, growth
4Ethical trade-off"When did you face a values conflict at work?"Moral reasoning, integrity
5Mentorship through difficulty"Tell me about helping someone through a hard time"Empathy, patience, investment in others
6Operated in extreme ambiguity"When did you have to act without enough information?"Comfort with uncertainty, judgment
7Someone else was right, you were wrong"When did a teammate's idea prove better than yours?"Ego management, collaborative instinct
8Mission motivation"Why do you want to work on AI safety?"Authenticity, depth of conviction

See references/story-bank-template.md for the full template with adaptation notes and follow-up preparation.


Negative Framing Preparation

Values interviews at mission-driven companies deliberately use negative framing. They ask about failures, weaknesses, and conflicts -- not to trap you, but to see how you metabolize difficulty.

Common Negative-Frame Patterns

Direct negative: "Tell me about a time you failed." Inverted positive: "What's something you're still not great at?" Third-person probe: "What would your harshest critic say about you?" Counterfactual: "If you could redo one decision, which would it be?" Conflict escalation: "Tell me about a time you fundamentally disagreed with leadership."

Response Principles

  1. Name the real thing. Not a weakness that is secretly a strength. A real weakness with real consequences.
  2. Own the timeline. When did you notice? If late, say so. Self-awareness about delayed recognition is itself a signal.
  3. Show the cost. What was lost? Who was affected? Minimizing consequences signals low self-awareness.
  4. Separate learning from damage control. "I learned X" is different from "but it all worked out." Sometimes it did not work out. Say so.
  5. Connect to present behavior. What do you do differently now? The learning must be operationalized, not abstract.

Authenticity Calibration

The goal is prepared but genuine -- you have thought deeply about your stories, but you are not performing them.

Signals of Authentic Preparation

  • Pauses naturally when a follow-up makes you think
  • Can deviate from the prepared narrative when asked a surprising angle
  • Acknowledges complexity ("honestly, I'm still not sure that was the right call")
  • Emotional register varies -- some stories have humor, some have weight
  • Credits specific people by name and contribution

Signals of Rehearsed Performance

  • Every answer is exactly 2-3 minutes
  • Transitions between STAR components feel scripted
  • No genuine hesitation or uncertainty
  • Every failure story has a neat resolution
  • Deflects follow-up questions back to the prepared narrative

Anti-Patterns

Anti-Pattern: Humble Brag

Novice: Reframes every failure as a success. "My biggest weakness is that I care too much" or "The project failed but I was the one who caught it." Every negative story has an immediately positive outcome with no genuine discomfort. Expert: Names a real failure with real consequences, then describes the specific learning without minimizing the damage. Sits with the discomfort of the failure before moving to resolution. Example: "We lost the client. That was on me. It took me three months to understand why my instinct was wrong." Detection: Count the ratio of negative-to-positive beats. If every story follows the pattern [bad thing] -> [but actually good thing], the candidate has not done the real introspective work.

Anti-Pattern: Rehearsed Authenticity

Novice: Stories sound scripted, hitting STAR beats mechanically. Same vocal energy for every question. Cannot deviate from the prepared narrative when asked an unexpected follow-up angle. "As I mentioned..." callbacks to previous structure. Expert: Has prepared structure but delivers with natural variation. Pauses to think when follow-ups go deeper than expected. Acknowledges when a question surfaces something they had not considered: "That's a good question -- I haven't thought about it from that angle." Detection: Ask a follow-up that is 90 degrees off their narrative. A rehearsed candidate will redirect back to their prepared story. A genuine candidate will engage with the new angle, even if it means admitting uncertainty.

Anti-Pattern: Hero Narrative

Novice: Every story features them as the protagonist who saves the day, solves the problem, or has the critical insight. No story features them learning from a peer, being wrong, or changing their mind based on someone else's input. Expert: Credits others specifically ("Sarah's insight about the cache invalidation pattern was better than my original approach"). Describes collaborative problem-solving where the outcome was better because of multiple perspectives. Includes at least 2-3 stories where someone else was the hero. Detection: Map the character roles across all stories. If the candidate is always the protagonist and never the supporting character, learner, or person who was wrong -- the narrative is self-serving.


Anthropic-Specific Preparation

Anthropic's behavioral round has distinctive characteristics. See references/anthropic-values-research.md for detailed research.

Key Differentiators from FAANG Behavioral Rounds

DimensionFAANG PatternAnthropic Pattern
Follow-up depth2-3 levels5-6 levels
FramingBalanced positive/negativeDeliberately negative
What they evaluateLeadership principles checklistGenuine self-awareness
Right answerDemonstrated LP alignmentNo single right answer; authenticity
Ethics questionsRareCentral
"Why here?" weightModerateVery high; mission alignment is load-bearing

Themes That Recur in Anthropic Values Rounds

  1. Intellectual honesty -- Can you say "I don't know" or "I was wrong"?
  2. Comfort with uncertainty -- How do you operate when the right answer is unknowable?
  3. Collaborative rigor -- Can you disagree productively and change your mind?
  4. Mission depth -- Is your interest in AI safety genuine and specific, or generic?
  5. Ethical reasoning -- How do you navigate gray areas without defaulting to rules?

Practice Protocol

Solo Preparation (Week 1-2)

  1. Build story bank using references/story-bank-template.md (8-12 stories)
  2. For each story, write out all 6 levels of the Follow-Up Ladder
  3. Record yourself telling each story. Listen for rehearsed-sounding language
  4. Have a trusted friend read your stories and ask "what's missing?"

Drill Sessions (Week 2-3)

Use references/follow-up-drills.md for structured practice exercises:

  • 5 Whys Drill: Practice being asked "why?" 5 times in succession
  • Alternative Path Drill: "What if you had done X instead?"
  • Critic Drill: "That sounds like it might have been a mistake..."
  • Self-Awareness Drill: "What does this reveal about your decision-making?"
  • Values Conflict Drill: "What if the right technical decision conflicted with the team?"

Mock Interviews (Week 3-4)

Use interview-simulator skill for realistic mock rounds with evaluation.


Reference Files

FileWhen to Consult
references/story-bank-template.mdBuilding or reviewing your bank of 8-12 career stories with STAR-L structure and adaptation notes
references/anthropic-values-research.mdUnderstanding Anthropic-specific values signals, culture, and what differentiates their behavioral round
references/follow-up-drills.mdPracticing deep follow-up handling with structured exercises; the 5 Whys, alternative path, critic, and values conflict drills

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Codex

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Cursor

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Gemini CLI

9.6%
按下载量换算46

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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。

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