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divedive 搜索

Agent Skill

dive 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

367

周安装

15

GitHub Stars

公开资料未说明

下载量

118
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:dive(dive 搜索)
来源仓库:https://github.com/lidessen/skills
仓库路径:skills/dive
安装命令:
npx skills add https://github.com/lidessen/skills --skill dive
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/lidessen/skills --skill dive

简介

用于深度探查项目代码与文档,验证技术决策依据。

  • 适合解决模糊假设或需要实证检验的场景。
  • 通过 GitHub 安装,命令为 npx skills add https://github.com/lidessen/skills --skill dive。
  • 使用前请确认宿主环境版本和权限,优先读取最新代码而非文档。
  • dive 属于研究检索类 Skill,可作为该场景下的辅助能力补充。

SKILL.md

Dive

Dives deep into your project to investigate any question, from business logic to technical implementation. Uses layered search strategy to find evidence-based answers backed by documentation and code.

Philosophy

Why Dive?

Dive exists because assumptions are dangerous.

The core question isn't "how do I find the answer?" but "how do I know my answer is true?"

The Fundamental Problem:
├── Memory is unreliable (yours and the codebase's docs)
├── Code evolves faster than documentation
├── "I think it works like..." is not evidence
└── Only the current codebase tells the current truth

Evidence Over Intuition

Intuition: "This probably uses X pattern"
Dive:      "render.ts:273 shows reconcileKeyedChildren() implementation"

Intuition is a starting point, not an answer. Dive converts intuition into verified knowledge through evidence gathering.

Layered Search: Why This Order?

Layer 1: Documentation  → What the project CLAIMS to do
Layer 2: Code           → What the project ACTUALLY does
Layer 3: Deep Analysis  → HOW it all connects

Why documentation first?

  • It's faster to read
  • It gives you vocabulary for code search
  • Discrepancies between docs and code are themselves findings

Why code second?

  • Code is ground truth—it can't lie about what it does
  • Tests show expected behavior in executable form
  • Types reveal contracts and constraints

Why deep analysis last?

  • It's expensive (time, context)
  • Only needed when layers 1-2 don't converge
  • Cross-component questions need tracing

Cross-Referencing Reveals Truth

When documentation says X but code does Y:

  • The code is always correct about behavior
  • The documentation reveals intent or outdated understanding
  • The discrepancy itself is valuable information

This is not a failure of search. It's a success—you found something real.

Core Concepts

Evidence Has Hierarchy

Not all evidence is equal:

SourceReliabilityWhat it proves
Running codeHighestCurrent behavior
TestsHighExpected behavior
ImplementationHighHow it works
Type definitionsMedium-HighContracts
CommentsMediumDeveloper intent
DocumentationMediumClaimed behavior
Commit messagesLow-MediumHistorical intent

Multiple sources agreeing = high confidence. Single source = verify with another layer.

The Question Shapes the Search

Different questions need different approaches:

"How does X work?" → Start with code, verify with tests "Why is X designed this way?" → Start with docs/ADRs, check history "What calls X?" → Start with grep, trace references "When did X change?" → Start with git log, find the commit

Don't apply the same search pattern to every question. Let the question guide you.

Uncertainty is Information

When you can't find clear evidence:

  • State what you searched
  • State what you found (even partial)
  • State what's missing
  • Offer hypotheses, clearly labeled as such

"I couldn't find X" is a valid finding. It tells the next investigator where not to look.

The Dive Loop

1. Understand: What exactly is being asked?
      ↓
2. Search: Layer 1 → Layer 2 → Layer 3 (as needed)
      ↓
3. Collect: Gather evidence with file:line citations
      ↓
4. Synthesize: What do the sources tell us together?
      ↓
5. Respond: Direct answer + evidence + uncertainty

This isn't a checklist to follow blindly. It's a mental model for thorough investigation.

When Layers Conflict

Documentation says one thing, code does another. This is common. Here's how to think about it:

SituationWhat to trustWhat to report
Docs outdatedCodeNote the discrepancy
Feature removedCodeFlag potential doc cleanup
Docs wrongCodeRecommend doc fix
Code buggyNeitherFlag as potential bug

The key: always report both, let context determine action.

Reference

Load these as needed, not upfront:

Understanding, Not Rules

Instead of memorizing anti-patterns, understand the underlying tensions:

TensionResolution
Speed vs ThoroughnessMatch depth to stakes. Quick question? Layer 1 may suffice. Critical decision? Go deep.
Confidence vs EvidenceNever state confidence without evidence. "I'm 90% sure" means nothing without sources.
Intuition vs VerificationUse intuition to guide search, not to answer. Then verify.
Completeness vs RelevanceAnswer the question asked. Note related findings briefly, don't digress.

The goal isn't to follow a procedure. It's to know when you know something is true.

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

35.9%
按下载量换算42

Claude

27.36%
按下载量换算32

Cursor

19.02%
按下载量换算22

Gemini CLI

8.64%
按下载量换算10

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。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

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