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use-the-best-tool使用最好的工具

Agent Skill

use-the-best-tool 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

612

周安装

26

GitHub Stars

公开资料未说明

下载量

214
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

MIT

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:use-the-best-tool(使用最好的工具)
来源仓库:https://github.com/outfitter-dev/agents
仓库路径:skills/use-the-best-tool
安装命令:
npx skills add outfitter-dev/agents --skill "use-the-best-tool"
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。

AgentSkills.tonpx skills
npx skills add outfitter-dev/agents --skill "use-the-best-tool"

简介

智能发现并推荐适合当前任务的 AI 代理技能,优化工具链组合。

  • 适用于多宿主环境(Codex/Claude/Cursor/Gemini CLI)下的技能检索与管理。
  • 通过 npx 从 GitHub 仓库安装,支持动态扩展与版本控制。
  • 需注意第三方技能来源可靠性,建议人工核验后再投入生产流程。
  • use-the-best-tool 属于研究检索类 Skill,可作为该场景下的辅助能力补充。

SKILL.md

Use the Best Tool

Select optimal CLI tools → graceful fallback → research when needed.

<when_to_use>

  • Choosing which tool for file search, content search, JSON processing
  • Tool taking unexpectedly long for task size
  • User expresses frustration with current tool
  • Task could be done more elegantly
  • Need to verify tool availability before recommending

NOT for: tasks where tool choice is predetermined, simple one-line commands

</when_to_use>

Run detection script before selecting tools:

bun /Users/mg/Developer/outfitter/agents/baselayer/skills/use-the-best-tool/scripts/index.ts

Parse output to determine:

  • Available modern tools
  • Missing tools that could enhance workflow
  • System context (OS, package managers)

Cache results per session — no need to re-run unless tool availability changes.

Map task to best available tool:

TaskPreferredFallbackLegacyNotes
Find files by namefd-findfd: faster, better defaults
Search file contentsrg-greprg: respects.gitignore, faster
AST-aware code searchsgrggrepsg: structure-aware queries
Process JSONjq-python/nodejq: domain-specific language
View file with syntaxbat-catbat: syntax highlighting, git diff
List directoryeza-lseza: modern output, icons
View git diffdelta-git diffdelta: side-by-side, syntax highlighting
Navigate directorieszoxide-cdzoxide: frecency-based jumping
Fuzzy selectfzf--fzf: interactive filtering
HTTP requestshttpie-curlhttpie: human-friendly syntax

Selection algorithm:

  1. Check detection results for preferred tool
  2. If available → use with optimal flags
  3. If unavailable → check fallback column
  4. If no fallback → use legacy with best-effort flags
  5. Note gap if preferred tool would significantly improve workflow

When preferred tool unavailable:

Minor improvement (preferred 10–30% better):

  • Use next best option silently
  • Don't interrupt workflow

Significant improvement (preferred 2x+ better):

  • Use fallback
  • Surface suggestion: ◇ Alternative: {TOOL} would be {BENEFIT} — install with {COMMAND}
  • Continue without blocking

Critical gap (task extremely tedious with fallback):

  • Surface suggestion: ◆ Caution: {TOOL} recommended for this task — {FALLBACK} will be slow/limited
  • Offer choice: install now, proceed anyway, defer task

Never block on missing tools — graceful degradation always.

Trigger research when:

  • Tool taking 3x+ longer than expected for task size
  • User explicitly asks for better approach
  • Task seems like it should have specialized tool
  • Current tool missing critical feature
  • New tool category needed (not in selection table)

Research workflow:

  1. Search for {TASK} CLI tool 2025 or {TASK} CLI tool 2024
  2. Check GitHub trending in relevant category
  3. Evaluate candidates:

- Speed: benchmarks vs existing tools - Ergonomics: default behavior, output format - Maintenance: last commit, issue response time - Install: complexity, dependencies - Compatibility: OS support, integration

Present findings:

  • Tool name + one-line description
  • Key advantages over current approach
  • Installation command
  • Usage example for current task
  • Trade-offs or caveats

If research yields strong candidate → add to selection table for future reference.

Standard flow:

  1. Receive task → categorize task type (find files, search content, process data)
  2. Check detection → run script if not yet run this session
  3. Select tool → use selection table + detection results
  4. Execute → run command with optimal flags
  5. Evaluate → if slow/frustrating → trigger research

Research flow:

  1. Trigger identified → surface to user with △ This seems slow — research alternatives?
  2. User confirms → web search for modern tools
  3. Evaluate candidates → speed, ergonomics, maintenance
  4. Present findings → tool + advantages + install + example
  5. Update knowledge → add to selection table if strong fit

Scenario: Search for authentication code

Task: Find all files containing "authentication" Detection: rg available Selection: Use rg over grep

rg "authentication" --type ts --type js

Scenario: Find config files

Task: Find all YAML files in project Detection: fd available Selection: Use fd over find

fd -e yaml -e yml

Scenario: Process API response

Task: Extract specific fields from JSON Detection: jq unavailable Fallback: Use node/python Suggestion: ◇ Alternative: jq would simplify this — install with brew install jq

node -e "console.log(JSON.parse(require('fs').readFileSync(0, 'utf-8')).field)"

ALWAYS:

  • Run detection script before recommending specific tools
  • Use selection table to map task to best available tool
  • Provide fallback when suggesting tools that might not be installed
  • Surface suggestions for significant improvements (2x+ better)
  • Trigger research when tool underperforms expectations

NEVER:

  • Assume a tool is installed without checking detection results
  • Block workflow on missing non-essential tools
  • Recommend abandonware or unmaintained tools
  • Use legacy tools when modern alternatives are available
  • Skip fallback strategy when preferred tool missing

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

04

需要参考平台分布和安装热度时

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

补充不同宿主或平台的使用分布数据

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

Claude Code

28.43%
按下载量换算61

windsurf

23.74%
按下载量换算51

OpenCode

17.94%
按下载量换算38

Cursor

14.86%
按下载量换算32

Codex

8.77%
按下载量换算19

Antigravity

3.81%
按下载量换算8

安全审计

暂无安全审计结果可展示。

权限和风险

需要联网

该 Skill 可能需要联网访问来源站点、仓库或外部 API;具体网络访问范围需要结合源码和 README 复核。

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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