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Agent Skill · 研究检索

explore(探索)

explore 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。

explore 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,权限为执行命令;许可证为 MIT,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 15,011。

总安装 8,152周安装 333GitHub Stars 3,698下载 2,611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
MIT

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:explore(探索)
来源仓库:https://github.com/parcadei/continuous-claude-v3
仓库路径:skills/explore
安装命令:
npx skills add https://github.com/parcadei/continuous-claude-v3 --skill explore
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。不同来源提供的安装方式可能略有差异;本站展示可直接复制的安装命令,安装前请核对来源页面。

skills.shnpx skills
npx skills add https://github.com/parcadei/continuous-claude-v3 --skill explore

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。

explore 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。适用于文件系统浏览、目录结构理解和项目布局探索等导航场景。通过 GitHub 仓库安装,使用 npx skills add 命令添加指定技能。

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。explore 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/explore

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/parcadei/continuous-claude-v3 --skill explore;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

    它需要执行命令,先在测试目录或测试账号里跑,确认没问题再放到正式项目。

常见问题

6 条

explore 怎么安装?

在终端执行 npx skills add https://github.com/parcadei/continuous-claude-v3 --skill explore。装完完全退出宿主工具再打开,让它重新扫描本地 Skill。

explore 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。

explore 需要什么权限?

权限级别是执行命令。安装流程涉及命令执行,可能通过 npx skills add https://github.com/parcadei/continuous-claude-v3 --skill explore;npx skills add parcadei/continuous-claude-v3 --skill "explore" 联网下载 Skill 或依赖。用户安装前应确认命令来源、仓库内容和执行环境。

explore 是免费的吗?

来源标注的许可证是 MIT。本站不代收任何费用,也不托管安装包;能否商用、要不要署名,以许可证原文为准。

explore 用的人多吗?

公开数据是累计安装 8,152 次,近一周安装 333 次,下载 2,611 次,GitHub 3,698 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。

explore 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。
  • 3 个目录同时收录,说明这个 Skill 流传比较广。
  • 许可证明确为 MIT,商用和分发边界好判断。
  • 第三方扫描已通过,常见的高风险行为没有命中。

先想清楚的地方

  • 需要执行命令,装到常用环境前要先评估影响面。
  • 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。
  • 需要许可证清楚、并且有第三方扫描结果的团队项目。

不太适合

  • 不能接受 Skill 在你机器上执行命令的人。
  • 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
explore

探索 · 本页

8,1523,698执行命令MIT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

Explore - Internal Codebase Exploration

Meta-skill for exploring an internal codebase at varying depths. READ-ONLY workflow - no code changes.

Usage

/explore <depth> [options]

Question Flow (No Arguments)

If the user types just /explore with no or partial arguments, guide them through this question flow. Use AskUserQuestion for each phase.

Phase 0: Workflow Selection

question: "How would you like to explore?"
header: "Explore"
options:
  - label: "Help me choose (Recommended)"
    description: "I'll ask questions to pick the right exploration depth"
  - label: "Quick - fast overview"
    description: "Chain: tldr tree → tldr structure (~1 min)"
  - label: "Deep - comprehensive analysis"
    description: "Chain: onboard → tldr → research → document (~5 min)"
  - label: "Architecture - layers & dependencies"
    description: "Chain: tldr arch → call graph → layer mapping (~3 min)"

Mapping:

  • "Help me choose" → Continue to Phase 1-4 questions
  • "Quick" → Set depth=quick, skip to Phase 2 (scope)
  • "Deep" → Set depth=deep, skip to Phase 2 (scope)
  • "Architecture" → Set depth=architecture, skip to Phase 2 (scope)

If Answer is Unclear (via "Other"):

question: "I want to understand how deep you want to explore. Did you mean..."
header: "Clarify"
options:
  - label: "Help me choose"
    description: "Not sure - guide me through questions"
  - label: "Quick - fast overview"
    description: "Just want to see what's here"
  - label: "Deep - comprehensive analysis"
    description: "Need thorough understanding"
  - label: "Neither - let me explain differently"
    description: "I'll describe what I need"

Phase 1: Exploration Goal

question: "What are you trying to understand?"
header: "Goal"
options:
  - label: "Get oriented in the codebase"
    description: "Quick overview of structure"
  - label: "Understand how something works"
    description: "Deep dive into specific area"
  - label: "Map the architecture"
    description: "Layers, dependencies, patterns"
  - label: "Find where something is"
    description: "Locate specific code/functionality"

Mapping:

  • "Get oriented" → quick depth
  • "Understand how" → deep depth
  • "Map architecture" → architecture depth
  • "Find where" → quick with --focus

Phase 2: Scope

question: "What area should I focus on?"
header: "Focus"
options:
  - label: "Entire codebase"
    description: "Explore everything"
  - label: "Specific directory or module"
    description: "I'll specify the path"
  - label: "Specific concept/feature"
    description: "e.g., 'authentication', 'API routes'"

If "Specific directory" or "Specific concept" → ask follow-up for the path/keyword.

Phase 3: Output Format

question: "What should I produce?"
header: "Output"
options:
  - label: "Just tell me what you find"
    description: "Interactive summary in chat"
  - label: "Create a documentation file"
    description: "Write to thoughts/shared/docs/"
  - label: "Create handoff for implementation"
    description: "Prepare context for coding agent"

Mapping:

  • "Documentation file" → --output doc
  • "Handoff for implementation" → --output handoff

Phase 4: Entry Point (Architecture only)

If architecture depth selected:

question: "Where should I start the analysis?"
header: "Entry point"
options:
  - label: "Auto-detect (main, cli, app)"
    description: "Find common entry points"
  - label: "Specific function/file"
    description: "I'll specify the entry point"

Summary Before Execution

Based on your answers, I'll run:

**Depth:** deep
**Focus:** "authentication"
**Output:** handoff
**Path:** src/

Proceed? [Yes / Adjust settings]

Depths

DepthTimeWhat it does
quick~1 mintldr-explorer only - fast structure overview
deep~5 minonboard + tldr-explorer + research-codebase + write doc
architecture~3 mintldr arch + call graph + layer mapping + circular dep detection

Options

OptionDescriptionExample
--focus "area"Focus on specific area--focus "auth", --focus "api"
--output handoffCreate handoff for next agent--output handoff
--output docCreate documentation file--output doc
--entry "func"Start from specific entry point--entry "main", --entry "process_request"

Examples

# Quick structure overview
/explore quick

# Deep exploration focused on auth
/explore deep --focus "auth" --output doc

# Architecture analysis from specific entry
/explore architecture --entry "cli" --output handoff

# Quick focused exploration
/explore quick --focus "hooks"

Workflow Details

Quick Depth

Fast structure overview using tldr-explorer. Best for:

  • Initial orientation
  • Quick questions about structure
  • Finding where things are

Steps:

  1. Run tldr tree for file structure
  2. Run tldr structure for codemaps
  3. If --focus provided, run tldr search for targeted results
  4. Return summary

Commands:

# 1. File tree
tldr tree ${PATH:-src/} --ext .py

# 2. Code structure
tldr structure ${PATH:-src/} --lang python

# 3. Focused search (if --focus provided)
tldr search "${FOCUS}" ${PATH:-src/}

Deep Depth

Comprehensive exploration with documentation output. Best for:

  • First time in a codebase
  • Preparing for major work
  • Creating reference documentation

Steps:

  1. Check if onboarded (look for .claude/cache/tldr/), if not run onboard
  2. Run tldr-explorer for structure
  3. Spawn research-codebase agent for patterns
  4. Write findings to doc or handoff

Subprocess:

# 1. Onboard check
if [ ! -f .claude/cache/tldr/arch.json ]; then
    # Spawn onboard agent
fi

# 2. Structure analysis
tldr structure src/ --lang python
tldr calls src/

# 3. Research patterns (via scout agent)
Task: research-codebase → "Document existing patterns in ${FOCUS:-codebase}"

# 4. Write output
→ thoughts/shared/research/YYYY-MM-DD-explore-{focus}.md
→ OR thoughts/shared/handoffs/{session}/explore-{focus}.yaml

Architecture Depth

Architecture-focused analysis with layer detection. Best for:

  • Understanding system boundaries
  • Preparing for refactoring
  • Identifying coupling issues

Steps:

  1. Run tldr arch for layer detection
  2. Run tldr calls for cross-file call graph
  3. Analyze entry/middle/leaf layers
  4. Detect circular dependencies
  5. Map architectural boundaries

Commands:

# 1. Architecture detection
tldr arch ${PATH:-src/}
# Returns: entry_layer, middle_layer, leaf_layer, circular_deps

# 2. Call graph
tldr calls ${PATH:-src/}
# Returns: edges, nodes

# 3. Impact analysis from entry point (if --entry provided)
tldr impact ${ENTRY} ${PATH:-src/} --depth 3

Output Structure:

layers:
  entry: [routes.py, cli.py, main.py]  # Controllers/handlers
  middle: [services.py, auth.py]        # Business logic
  leaf: [utils.py, helpers.py]          # Utilities

call_graph:
  total_edges: 142
  hot_paths: [process_request → validate → authorize]

circular_deps:
  - [module_a, module_b]  # A imports B, B imports A

boundaries:
  - name: API layer
    files: [src/api/*]
    calls_to: [src/services/*]

Output Formats

--output doc

Creates: thoughts/shared/research/YYYY-MM-DD-explore-{focus}.md

---
date: {ISO timestamp}
type: exploration
depth: {quick|deep|architecture}
focus: {focus area or "full"}
commit: {git hash}
---

# Codebase Exploration: {focus}

## Summary
{High-level findings}

## Structure
{File tree / codemaps}

## Architecture
{Layer analysis - for architecture depth}

## Key Components
{Important files and their roles}

## Patterns Found
{Existing patterns - for deep depth}

## References
- `path/to/file.py:line` - Description

--output handoff

Creates: thoughts/shared/handoffs/{session}/explore-{focus}.yaml

---
type: exploration
ts: {ISO timestamp}
depth: {quick|deep|architecture}
focus: {focus area}
commit: {git hash}
---

summary: {One-line summary of findings}

structure:
  entry_points: [{main.py}, {cli.py}]
  key_modules: [{auth.py}, {routes.py}]
  test_coverage: [{tests/}]

architecture:
  layers:
    entry: [{files}]
    middle: [{files}]
    leaf: [{files}]
  circular_deps: [{pairs}]

findings:
  - {key finding with file:line}

next_steps:
  - {Recommended action based on exploration}

refs:
  - path: {file.py}
    role: {what it does}

Integration with /build

The explore skill is designed to feed into /build brownfield:

# Step 1: Explore to understand
/explore architecture --output handoff

# Step 2: Build with context from exploration
/build brownfield --from-handoff thoughts/shared/handoffs/session/explore-full.yaml

Implementation

When user invokes /explore <depth> [options]:

Parse Arguments

depth = args[0]  # quick | deep | architecture
focus = extract_option(args, "--focus")
output = extract_option(args, "--output")  # handoff | doc
entry = extract_option(args, "--entry")

Execute Based on Depth

Quick:

# Just tldr commands, no agents
tldr tree ${src_dir} --ext .py
tldr structure ${src_dir} --lang python
if [ -n "$focus" ]; then
    tldr search "$focus" ${src_dir}
fi

Deep:

# 1. Check/run onboard
if [ ! -f .claude/cache/tldr/meta.json ]; then
    # Spawn onboard agent via Task tool
fi

# 2. Structure
tldr structure src/ --lang python

# 3. Research (spawn scout agent)
# Task tool with subagent_type: "scout"
# Prompt: "Research patterns in ${focus:-codebase}"

# 4. Write output
# → doc or handoff based on --output

Architecture:

# 1. Arch detection
arch_output=$(tldr arch ${src_dir})

# 2. Call graph
calls_output=$(tldr calls ${src_dir})

# 3. Impact from entry (if provided)
if [ -n "$entry" ]; then
    impact_output=$(tldr impact $entry ${src_dir} --depth 3)
fi

# 4. Synthesize and write output

Key Principles

  1. READ-ONLY - This skill never modifies code
  2. Uses scout, not Explore - Per project rules, scout (Sonnet) over Explore (Haiku)
  3. Token-efficient - Uses tldr commands (95% savings over raw reads)
  4. Outputs to shared locations - thoughts/shared/research/ or handoff directory
  5. Entry point to /build - Exploration handoffs feed into brownfield builds

Related Skills

SkillWhen to Use
tldr-explorerDirect tldr commands (used internally by explore)
tldr-codeSpecific analysis commands (cfg, dfg, slice)
onboardFirst-time project setup (used by deep depth)
research-codebasePattern documentation (used by deep depth)
create_handoffHandoff format (used by --output handoff)

Troubleshooting

tldr not found:

# Check if installed
which tldr
# Install if missing
uv tool install llm-tldr
# or: pip install llm-tldr

No Python files found:

# Check language, adjust --lang
tldr structure src/ --lang typescript  # or go, rust

Empty architecture output:

# May need to specify src directory
tldr arch ./  # Current directory
tldr arch src/  # Explicit src

平台分布

Claude Code

28.65%
按下载量换算748

OpenCode

24.14%
按下载量换算630

Codex

16.8%
按下载量换算439

Cursor

11.87%
按下载量换算310

Gemini CLI

6.64%
按下载量换算173

Antigravity

3.18%
按下载量换算83

安全审计

Gen Agent Trust Hub

通过

Socket

通过

Snyk

通过

权限和风险

执行命令

安装流程涉及命令执行,可能通过 npx skills add https://github.com/parcadei/continuous-claude-v3 --skill explore;npx skills add parcadei/continuous-claude-v3 --skill "explore" 联网下载 Skill 或依赖。用户安装前应确认命令来源、仓库内容和执行环境。

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。

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