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Agent Skill · 研究检索

discover(discover 搜索)

discover 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。

discover 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,权限为接触敏感数据;许可证信息还不明确,第三方扫描有未通过项,按安装量在研究检索类的 73,675 个 Skill 里排第 71,838。

总安装 192周安装 8GitHub Stars 1下载 64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:discover(discover 搜索)
来源仓库:https://github.com/jschulte/claude-plugins
仓库路径:skills/discover
安装命令:
npx skills add https://github.com/jschulte/claude-plugins --skill discover
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/jschulte/claude-plugins --skill discover

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。

用于查找、检索和筛选相关信息。discover 属于研究检索类 Skill,可作为该场景下的辅助能力补充。适合根据关键词或任务场景快速定位候选结果。可辅助研究类任务的信息收集环节。适用宿主包括 Codex、Claude、Cursor、Gemini CLI,接入前应确认版本、权限和运行环境要求。

建议结合具体需求验证搜索策略的有效性。需注意来源仓库的维护状态和实际功能边界。

来源仓库内路径:skills/discover

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/jschulte/claude-plugins --skill discover;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

    它需要接触敏感数据,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

discover 怎么安装?

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

discover 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。

discover 需要什么权限?

权限级别是接触敏感数据。该 Skill 可能接触密钥、Token、环境变量或敏感配置,应进入高风险复核队列,默认不自动发布。

discover 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。

discover 用的人多吗?

公开数据是累计安装 192 次,近一周安装 8 次,下载 64 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。

discover 安全吗?

第三方扫描有未通过项,风险较高。除非你确认过源码,否则不建议直接安装到常用环境。

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。

先想清楚的地方

  • 需要接触敏感数据,装到常用环境前要先评估影响面。
  • 许可证没有明确标注,能不能商用、能不能再分发都不确定。
  • 第三方扫描存在提醒项或未通过项,需要人工逐条确认。
  • 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。

不太适合

  • 环境里有大量密钥、凭证,不方便给第三方 Skill 读取的人。
  • 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
discover

discover 搜索 · 本页

1921接触敏感数据未明确未通过

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

Ecosystem Discovery

Estimated Time: 10-30 minutes (depending on ecosystem size and GitHub search) Prerequisites: A starting repo with real code (not empty scaffolding) Output: ecosystem-map.md in the starting repo's .stackshift/ directory, .stackshift-batch-session.json in the starting repo directory for handoff

All path variables MUST be double-quoted in shell commands. This skill is single-session with no resume capability -- if interrupted, re-run from Step 1.


When to Use This Skill

Activate when:

  • The user has one repo and wants to find everything it connects to
  • A large-scale reverse-engineering project needs repo enumeration
  • The user wants to map an entire platform before running batch analysis
  • The dependency graph between multiple repos/services is unknown

Trigger Phrases:

  • "Discover the ecosystem for this repo"
  • "What other repos does this project depend on?"
  • "Map all the related services"
  • "Find all the repos in this platform"
  • "What's connected to this service?"

Process

Step 1: Pre-flight

Verify the starting repo exists and detect basic characteristics:

# Verify we're in a repo with code
if [ ! -d ".git" ] && [ ! -f "package.json" ] && [ ! -f "go.mod" ] && [ ! -f "requirements.txt" ]; then
  echo "WARNING: This doesn't look like a code repository"
fi

# Detect if monorepo
MONOREPO="false"
if [ -f "pnpm-workspace.yaml" ] || [ -f "turbo.json" ] || [ -f "nx.json" ] || [ -f "lerna.json" ]; then
  MONOREPO="true"
fi

# Get repo name
REPO_NAME=$(basename "$(pwd)")

# Auto-discover GitHub org from git remote
REMOTE_URL=$(git remote get-url origin 2>/dev/null || echo "")
GITHUB_ORG=""
if [[ "$REMOTE_URL" =~ github\.com[:/]([^/]+)/ ]]; then
  GITHUB_ORG="${BASH_REMATCH[1]}"
  echo "Auto-detected GitHub org: $GITHUB_ORG"
elif [[ "$REMOTE_URL" =~ gitlab\.com[:/]([^/]+)/ ]]; then
  GITHUB_ORG="${BASH_REMATCH[1]}"
  echo "Auto-detected GitLab group: $GITHUB_ORG"
fi

Monorepo handling: If workspace config is detected:

  1. Resolve all workspace globs to actual package directories
  2. Mark every discovered package as CONFIRMED
  3. Still scan each package for outbound signals to find external dependencies
  4. The Mermaid graph shows intra-monorepo dependencies

Step 2: User Input

Show the auto-detected org and ask for confirmation:

I auto-detected the GitHub org from your git remote: {GITHUB_ORG}

Is this correct? (Y/n, or enter a different org)

If no org was detected:

I couldn't detect a GitHub org from the git remote.
What GitHub org should I search? (optional, press enter to skip)

Ask about known repos:

Do you know of any related repos? (optional)

List paths or org/repo names, one per line:
- ~/git/auth-service
- ~/git/shared-libs
- myorg/inventory-api
- (or press enter to skip)

Mark user-provided repos as CONFIRMED confidence.

Step 3: Scan Starting Repo

Run all 10 signal categories on the starting repo. Follow scan-integration-signals.md for detailed instructions.

Signal categories:

  1. Scoped npm packages (@org/* in package.json)
  2. Docker Compose services (docker-compose*.yml)
  3. Environment variables (.env*, config files)
  4. API client calls (source code URLs, gRPC protos)
  5. Shared databases (connection strings, schema refs)
  6. CI/CD triggers (.github/workflows/*.yml)
  7. Workspace configs (pnpm-workspace.yaml, turbo.json, nx.json, lerna.json)
  8. Message queues/events (SQS, SNS, Kafka topic names)
  9. Infrastructure refs (terraform/, cloudformation/, k8s/)
  10. Import paths / go.mod / requirements.txt (language-specific deps)

CHECKPOINT -- Report to user before continuing:

Signal scan complete. Found {N} candidate names across {M} signal categories.
Top signals: {list top 3-5 discovered names with their categories}
Proceeding to scan user repos and search GitHub...

If zero signals found, skip to the "Standalone Repo" edge case (see present-ecosystem-map.md Error Cases).

Step 4: Scan User-Provided Repos

For each repo the user listed:

  1. Verify it exists (local path or clone from GitHub). If the path does not exist, warn the user and skip that repo.
  2. Run the same 10 signal categories
  3. Cross-reference signals with the starting repo to build connections

Step 5: GitHub Search (if org provided)

Follow github-ecosystem-search.md for detailed instructions.

Search the GitHub org for repos matching discovered signal names:

  • Package names (@org/shared-utils -> search for shared-utils repo)
  • Service names from Docker Compose or env vars
  • Repository naming patterns (same prefix, similar conventions)

Error recovery: If a GitHub API call fails with a transient error (5xx, network timeout), retry up to 2 times with 10-second backoff. If all retries fail, skip GitHub search and note it in the ecosystem map. If rate-limited, skip GitHub search entirely and rely on local results.

CHECKPOINT -- Report to user before continuing:

GitHub search complete. Found {N} matching repos ({X} exact name matches, {Y} code references).
Proceeding to local filesystem scan and merge...

If GitHub search was skipped, report:

GitHub search skipped ({reason}). Proceeding with local scan and signal analysis only.

Step 6: Local Filesystem Scan

Search common development directories for matching repos:

# Common locations to check
SEARCH_DIRS=(
  "$(dirname "$(pwd)")"      # Sibling directories
  "$HOME/git"
  "$HOME/code"
  "$HOME/src"
  "$HOME/projects"
  "$HOME/repos"
  "$HOME/dev"
  "$HOME/workspace"
)

# For each discovered package/service name, look for matching directories
for name in "${DISCOVERED_NAMES[@]}"; do
  for dir in "${SEARCH_DIRS[@]}"; do
    if [ -d "$dir/$name" ]; then
      echo "FOUND: $dir/$name"
    fi
  done
done

Step 7: Merge & Deduplicate

Follow merge-and-score.md for detailed instructions on deduplication, confidence scoring formula, and dependency graph construction.

Combine all discovery sources, deduplicate by repo identity, score confidence, and build the dependency graph.

Step 8: Present Ecosystem Map

Follow present-ecosystem-map.md for detailed instructions.

Generate ecosystem-map.md in .stackshift/ directory. Display the map to the user with a summary:

Found X repos (Y confirmed, Z high confidence, W medium, V low)

Step 9: User Confirmation

Ask the user to review and adjust:

Does this ecosystem map look right?

Options:
A) Looks good -- proceed to handoff
B) Add repos -- I'll add more to the list
C) Remove repos -- Take some off the list
D) Rescan -- Run discovery again with adjustments

If the user adds repos, mark as CONFIRMED and re-merge. If the user removes repos, update the map and graph. If the user requests a rescan, return to Step 3 with adjustments.

Step 10: Handoff

Create .stackshift-batch-session.json in the starting repo directory:

{
  "sessionId": "discover-{timestamp}",
  "startedAt": "{iso_date}",
  "batchRootDirectory": "{starting_repo_path}",
  "totalRepos": "{length of discoveredRepos array}",
  "batchSize": 5,
  "answers": {},
  "processedRepos": [],
  "discoveredRepos": [
    {
      "name": "{repo_name}",
      "path": "{local_path}",
      "confidence": "CONFIRMED|HIGH|MEDIUM|LOW",
      "signals": ["{signal1}", "{signal2}"]
    }
  ]
}

totalRepos MUST equal the length of the discoveredRepos array (all confidence levels included).

Present next steps as model actions:

What would you like to do with these {X} repos?

A) Run /stackshift.batch on all repos
B) Run /stackshift.reimagine
C) Export ecosystem map only
D) Analyze a specific subset

On user choice:

  • A) Verify .stackshift-batch-session.json exists in the starting repo directory. Instruct user to run /stackshift.batch.
  • B) Note that reimagine needs reverse-engineering docs. Suggest running batch first (Gears 1-2 minimum), or proceed if docs exist.
  • C) Confirm map is saved to .stackshift/ecosystem-map.md. Session file preserved for later.
  • D) Let user pick repos, update batch session with selected subset, then proceed as A.

10 Signal Categories

#Signal CategoryWhere to LookExample
1Scoped npm packagespackage.json dependencies@myorg/shared-utils
2Docker Compose servicesdocker-compose*.ymldepends_on: [user-api, redis]
3Environment variables.env*, config filesUSER_SERVICE_URL, INVENTORY_API_HOST
4API client callsSource code imports/URLsfetch('/api/v2/users'), gRPC protos
5Shared databasesConnection strings, schema refsSame DB name in multiple configs
6CI/CD triggers.github/workflows/*.ymlpaths:, repository_dispatch, cross-repo triggers
7Workspace configspnpm-workspace.yaml, turbo.json, nx.json, lerna.jsonMonorepo package lists
8Message queues/eventsSource code, configSQS queue names, SNS topics, Kafka topics
9Infrastructure refsterraform/, cloudformation/, k8s/Shared VPCs, service meshes, ALBs
10Import paths / go.mod / requirements.txtLanguage-specific dependency filesreplace github.com/myorg/shared =>../shared

For confidence scoring criteria and formulas, see merge-and-score.md.


Edge Cases

Monorepo as Starting Point

When workspace config is detected:

  • All packages resolved from workspace globs are CONFIRMED automatically
  • Still scan each package for outbound signals (external deps, APIs, databases)
  • The ecosystem map shows both intra-monorepo and external dependencies
  • The Mermaid graph uses subgraph to group monorepo packages together
  • Handoff to batch can process each package as a separate "repo"

Standalone Repo (No Signals Found)

When signal scanning finds zero references to other repos, present options per present-ecosystem-map.md Error Cases. Do not treat this as a failure.

No GitHub Org Detected

Skip GitHub search entirely (Step 5 is skipped). Rely on local filesystem scan and signal analysis only. Report: "GitHub search skipped (no org detected). Results based on local scan only."

GitHub Search Rate Limited or Auth Failed

Fall back to local scan + signal analysis. Note in the ecosystem map: "GitHub search was skipped (rate limited / not authenticated)". For transient errors (5xx, network timeout), retry up to 2 times with 10-second backoff before falling back.

Large Ecosystem (20+ Repos)

  • Mermaid graph: show only CONFIRMED + HIGH repos in the main diagram
  • Group repos by domain using subgraph if clear clusters exist
  • Offer to filter: "Found {N} repos. Analyze all, or filter to HIGH+ confidence?"
  • Batch handoff should suggest a conservative batch size (3 at a time)

Only LOW Confidence Repos

When all discovered repos (beyond the starting point) are LOW confidence, present review options per present-ecosystem-map.md Error Cases.

Mixed Local/Remote Repos

  • Prefer local paths when available (faster to scan)
  • Note GitHub-only repos as "remote only" in the ecosystem map
  • Ask user: "Some repos are only on GitHub. Clone them locally for analysis?"

平台分布

Codex

38.21%
按下载量换算24

Claude

28.04%
按下载量换算18

Cursor

17.85%
按下载量换算11

Gemini CLI

9.92%
按下载量换算6

安全审计

Gen Agent Trust Hub

通过

Socket

未通过

Snyk

未通过

权限和风险

接触敏感数据

该 Skill 可能接触密钥、Token、环境变量或敏感配置,应进入高风险复核队列,默认不自动发布。

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。来源安全扫描存在提醒或未通过项,安装前请自行复核。目前只有一个公开来源,建议同时核对源仓库。

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