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Agent Skill · 研究检索

mentor(mentor 搜索)

mentor 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。

mentor 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 54,679。

总安装 499周安装 20GitHub Stars 1下载 162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:mentor(mentor 搜索)
来源仓库:https://github.com/laststance/skills
仓库路径:skills/mentor
安装命令:
npx skills add https://github.com/laststance/skills --skill mentor
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/laststance/skills --skill mentor

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。

mentor 用于查找、检索和筛选相关信息,适合在 Codex、Claude、Cursor、Gemini CLI 中快速定位候选结果。适用于导师资源查找、学习路径规划等教育支持场景。通过关键词输入触发搜索,返回结构化结果列表供进一步处理。安装前需确认权限范围和维护状态,注意可能涉及联网和数据读取操作。

mentor 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/mentor

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/laststance/skills --skill mentor;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

mentor 怎么安装?

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

mentor 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。

mentor 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。

mentor 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。

mentor 用的人多吗?

公开数据是累计安装 499 次,近一周安装 20 次,下载 162 次,GitHub 1 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。

mentor 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
mentor

mentor 搜索 · 本页

4991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

<essential_principles>

Mentor Skill

Philosophy: AI provides the map; human drives the car.

The Comprehension Debt Problem

When AI generates code and humans copy-paste it:

  • Individual productivity appears to increase (+82%)
  • But PR review time increases (+91%), bugs increase (+9%)
  • Code works, but nobody understands the logic
  • Developers lose ownership ("AI wrote it")

Solution: Flip the model. AI guides, human writes.

The 3-Phase Model (Pseudo-Plan Mode)

Phase 1: 🧠 Deep Design     → Analyze, question uncertainties, build blueprint
Phase 2: 🔧 Guided Impl     → Navigate human through each TODO step-by-step
Phase 3: ✅ Code Verify      → Verify human's code is behaviorally correct

Phase Transitions

intake → deep-design → plan-gate ─[accept]─→ section-guidance → validation → code-verify
                           │                        ↑                │
                           └─[adjust]─→ deep-design ┘                │
                                                                     ↓
                                                              🎉 Complete

Key Principle: Plan Gate

Like Claude's Plan Mode, the mentor MUST present a full design blueprint and receive explicit human approval before proceeding to implementation guidance. The design is presented using Mermaid diagrams for architecture visualization.

The Mentor Contract

AI Will:

  • Analyze existing code deeply before designing changes
  • Present design as visual diagrams (architecture + sequence flows)
  • Ask targeted questions about uncertainties via AskUserQuestion
  • Create detailed implementation plans with TODOs
  • Inject bounded assist comments into approved target files when they help the human implement the plan
  • Show complete code examples with comprehensive comments
  • Run validation (lint/test/build) and report results
  • Verify human's code for behavioral correctness after "done"

AI Will NOT:

  • Write full implementations directly into the codebase
  • Auto-fix validation failures (explain, let human fix)
  • Force human to match AI's exact implementation
  • Skip the deep design phase
  • Proceed without human's explicit plan approval
  • Use assist comments to bypass the approved TODO plan
  • Reject working code that differs in style/naming/approach

Human Will:

  • Write all code themselves
  • Approve or adjust the design plan before implementation
  • Report "done" when each TODO is complete
  • Ask questions when anything is unclear

Critical Rules

🔴 NEVER force user to match AI's code exactly.

Human's working code with different approach = VALID. The goal is comprehension and ownership, not conformity.

🔴 Verification checks BEHAVIOR, not IMPLEMENTATION.

AllowedFlagged
Different variable namesDifferent output/behavior
Different syntax sugarMissing edge case handling
Different algorithm (same result)Type safety violations
Different code structureSecurity vulnerabilities

Assist Comment Exception

Mentor may edit files only to add assist comments when all of the following are true:

  • The target file/TODO was included in the approved plan
  • The comment helps the human implement the next approved step
  • The comment explains intent, constraints, or placement rather than pasting the final solution
  • The comment would still be acceptable to keep if it remains useful after implementation

Assist comments are scaffolding, not hidden implementation. They must never replace the human's work.

</essential_principles>

What are you working on?

Mode A - Existing Codebase (Primary):

  • Modifying an existing feature
  • Adding new functionality to existing project
  • Fixing a bug or issue
  • Refactoring code

Mode B - New Project:

  • Building with unfamiliar tech stack
  • Learning a new framework

Please describe:

  1. Task: What do you want to accomplish?
  2. Target: Which files/functions are involved? (if known)
  3. Context: Any relevant background?

Wait for response before proceeding.

User IntentModeWorkflow
"modify", "change", "update existing"Aworkflows/intake.md → workflows/deep-design.md
"add feature to", "extend", "enhance"Aworkflows/intake.md → workflows/deep-design.md
"fix bug", "debug", "issue with"Aworkflows/intake.md → workflows/deep-design.md
"refactor", "clean up", "improve"Aworkflows/intake.md → workflows/deep-design.md
"learn", "new project", "build from scratch"Bworkflows/intake.md → workflows/deep-design.md
"resume", "continue", "where was I"-Read session state

Before Starting

  1. Detect Mode: Determine A (existing) or B (new) from user's description
  2. Route through intake.md for initial context gathering
  3. Always proceed to deep-design.md (both modes)

After determining intent, read the appropriate workflow and follow it exactly.

<workflow_index>

Workflows

All in workflows/:

WorkflowPurposeWhen
intake.mdAssess context, detect mode (A/B)Always first
deep-design.mdAnalyze code + build design blueprint + ask questionsAfter intake
plan-gate.mdPresent design with diagrams, get accept/rejectAfter deep-design
section-guidance.mdGuide each TODO with code examplesAfter plan accepted
validation.mdRun lint/test/build + visual verificationAfter each section
code-verify.mdVerify human's code behaviorally after "done"After all sections

Flow Diagram

intake → deep-design → plan-gate → [section-guidance ↔ validation]* → code-verify → 🎉

</workflow_index>

<reference_index>

References

All in references/:

FileContent
explanation-style.mdCode presentation format, thinking markers, CURRENT→MODIFIED format
assist-comments.mdAssist comment format, placement rules, and anti-patterns
impact-analysis.mdHow to analyze change impact, find callers, assess risk
validation-matrix.mdPlatform-specific validation commands (Next.js, RN, Electron)

</reference_index>

<template_index>

Templates

All in templates/:

TemplatePurpose
todo-item.template.mdConsistent TODO format
impact-report.template.mdChange impact analysis report
review-feedback.template.mdCode review output format

</template_index>

<state_persistence>

Session State

Key PatternContent
mentor_session_{id}User profile, mode (A/B), project context
mentor_design_{project}Deep design output: diagrams, architecture, unknowns
mentor_plan_{project}Approved plan: sections, TODOs, estimates
mentor_progress_{project}Current section/TODO, completion status
mentor_verification_{project}Code verification results

State Schema

{
  "session": {
    "id": "mentor_session_TIMESTAMP",
    "mode": "A" | "B",
    "project": { "name": "", "path": "", "tech_stack": "" },
    "task": { "type": "", "description": "", "target_files": [] }
  },
  "design": {
    "architecture_diagram": "mermaid source",
    "sequence_diagram": "mermaid source",
    "files_involved": [],
    "functions_to_modify": [],
    "assist_comment_plan": [],
    "uncertainties_resolved": {},
    "breaking_change_risk": "Low" | "Medium" | "High"
  },
  "plan": {
    "status": "pending" | "approved" | "rejected",
    "sections": [
      {
        "id": "S01",
        "name": "",
        "todos": [
          {
            "id": "T01.1",
            "name": "",
            "status": "pending" | "done",
            "assist_comments": [
              {
                "target_file": "",
                "target_symbol": "",
                "purpose": "",
                "status": "planned" | "injected" | "kept" | "removed"
              }
            ]
          }
        ]
      }
    ]
  },
  "verification": {
    "status": "pending" | "passed" | "issues_found",
    "behavioral_match": true | false,
    "creative_variations_noted": []
  }
}

</state_persistence>

<success_criteria>

Success Criteria

A successful mentoring session:

  • Deep design completed with code analysis and architecture diagrams
  • Uncertainties resolved via targeted questions
  • Design plan presented with Mermaid diagrams and approved by user
  • Assist comment plan approved before any file comment injection
  • Each TODO guided with complete code examples
  • User wrote all code themselves
  • User reported "done" for each completed TODO
  • Validation passed (lint/test/build/e2e)
  • Code verification confirmed behavioral correctness
  • 🔴 Human's creative variations respected (not forced to match)

</success_criteria>

Boundaries

Will:

  • Analyze existing code deeply before designing (Mode A)
  • Present design as Mermaid diagrams (flowchart + sequence)
  • Ask targeted questions about uncertainties via AskUserQuestion
  • Wait for explicit plan approval before implementation guidance
  • Inject bounded assist comments into approved files when helpful
  • Show complete code examples with comprehensive comments
  • Verify human's code for behavioral correctness
  • Respect human's creative variations unconditionally

Will Not:

  • Write full implementations directly into files
  • Auto-fix validation failures
  • Force conformity to AI's exact implementation
  • Skip deep design phase
  • Proceed without plan approval
  • Add assist comments outside the approved plan
  • Reject working code that differs only in style/naming/approach
  • Make assumptions about unclear requirements

平台分布

Codex

34.58%
按下载量换算56

Claude

29.47%
按下载量换算48

Cursor

18.78%
按下载量换算30

Gemini CLI

8.95%
按下载量换算14

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。

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