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Agent Skill · 研究检索

nimble-web-expert(敏捷的网络专家)

nimble-web-expert 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。

nimble-web-expert 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,第三方扫描有提醒项,按安装量在研究检索类的 73,675 个 Skill 里排第 49,433。

总安装 652周安装 28GitHub Stars 45下载 228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:nimble-web-expert(敏捷的网络专家)
来源仓库:https://github.com/nimbleway/agent-skills
仓库路径:skills/nimble-web-expert
安装命令:
npx skills add https://github.com/nimbleway/agent-skills --skill nimble-web-expert
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/nimbleway/agent-skills --skill nimble-web-expert

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。

用于查找网络技术和 Web 开发相关的解决方案。适合在 Codex、Claude、Cursor、Gemini CLI 中根据场景快速定位资料。可结合原始 README 验证具体功能,但需注意权限范围。安装方式:通过 npx 从 GitHub 仓库添加,建议先评估维护状态。

注意:搜索结果可能包含未经验证的方法,使用时应谨慎评估。

来源仓库内路径:skills/nimble-web-expert

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/nimbleway/agent-skills --skill nimble-web-expe…;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

nimble-web-expert 怎么安装?

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

nimble-web-expert 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。

nimble-web-expert 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。

nimble-web-expert 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。

nimble-web-expert 用的人多吗?

公开数据是累计安装 652 次,近一周安装 28 次,下载 228 次,GitHub 45 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。

nimble-web-expert 安全吗?

第三方扫描有提醒项,说明存在需要人工确认的行为。安装前请打开源码看清它读了什么、联网到哪里。

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
nimble-web-expert

敏捷的网络专家 · 本页

65245接触敏感数据未明确有提醒

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

Nimble Web Expert

Web extraction, search, and URL discovery using the Nimble CLI. Returns clean structured data from any website.

User request: $ARGUMENTS

Core principles

  • Route by intent first. Named site/domain → check for pre-built agent first (announce it out loud). Direct URL → nimble extract. Research/topic → nimble search. Discover/crawl URLs → nimble map or nimble crawl.
  • One command → present results → done. Run once with --transform "data.parsing" for agents. Show the data immediately as a table. Do NOT experiment, loop, or write Python to parse output.
  • Multiple inputs → always parallel. 2+ URLs/keywords/ASINs → &+wait. 6–20 → xargs -P. 20+ → Python asyncio script. See references/batch-patterns.md.
  • Escalate render tiers silently. Tier 1 → 2 → 3 → … without asking. Surface a decision only when all tiers fail and investigation tools are needed.
  • Never answer from training data. Live prices, current news, today's listings → always fetch via Nimble. If unavailable, say so.
  • AskUserQuestion at every meaningful choice. Header ≤12 chars, 2–4 options, label 1–5 words, recommended option first. Never present choices as numbered prose.
  • Save all outputs to .nimble/. Never leave extraction results in memory only.
  • If bash is denied, stop immediately. Show the command as text and wait. Never retry with dangerouslyDisableSandbox.

Skill ecosystem

SkillBest forKey commands
nimble-web-expert (this skill)Real-time data — fetch any URL, search, map, crawl, run existing agentsextract, search, map, crawl, agent run
nimble-agent-builderBuild reusable agents — create, refine, publish named extraction templatesCLI: generate, get-generation, publish

Hand off to nimble-agent-builder only when all of these are true: the user has signalled a recurring/scheduled need, the pattern is repetitive (same site, same fields), and they've seen and approved the results. Don't ask after every extract — only when language clearly signals a recurring workflow ("I want to do this every day", "build me a pipeline", "make this reusable").

For agent refinement: *"Agent updates are handled by nimble-agent-builder — it can refine the existing agent without rebuilding from scratch."*

Interactive UX

  • Use AskUserQuestion at every meaningful choice — never guess, never ask in prose.
  • Ambiguous request (no URL, vague topic): ask before running — "What would you like to do?" → Search / Fetch URL / Discover URLs / Call API
  • Before running a search (if task maps to a specific focus mode): offer focus mode — General / News / Coding / Shopping / Academic / Social
  • After all tiers fail: check investigation tools (which browser-use, python3 -c "from playwright.sync_api...") and ask whether to investigate with browser-use, Playwright, or skip.
  • After presenting results, always close with: "Were these results what you needed?" → Looks great! / Mostly good / Not quite / Skip feedback

Prerequisites

Quick check:

nimble --version && echo "${NIMBLE_API_KEY:+API key: set}"

If CLI version and API key: set both print → proceed to Step 0.

If anything is missing, load rules/setup.md for one-time setup instructions (CLI install, API key, Docs MCP).

If bash is denied: Stop. Show the command as text. Do not substitute WebFetch for Nimble tasks.


Analyze & Route

User signalCommandNotes
Names a specific site or domainnimble agent → nimble extract if no agentAlways check for agent first — announce it
Provides a direct URLnimble extractSkip agent check
Research, topic, or vertical querynimble searchUse focus modes for news, jobs, shopping, etc.
"Find URLs / sitemap / all pages"nimble mapReturns URL list + metadata
"Crawl / archive a whole section"nimble crawlAsync bulk extraction

Step 0 — Agent check (when a domain is named)

Pre-built agents return clean structured data with zero selector work. Always check first.

Always verbalize — never silently:

  1. Announce: *"Let me check if there's a pre-built Nimble agent for [site]..."*
  2. Report: *"Found <agent_name> — using it now."* or *"No pre-built agent — falling back to extraction."*

Lookup order:

  1. ~/.claude/skills/nimble-web-expert/learned/examples.json → agents[] array
  2. references/nimble-agents/SKILL.md → baked-in table (50+ sites)
  3. nimble agent list --limit 100 --search "<domain or vertical>" → show table, confirm with user
  4. No match → proceed to extract/search

Run with --transform "data.parsing" — always:

nimble --transform "data.parsing" agent run --agent <name> --params '{"keyword": "..."}'

Do NOT run without --transform "data.parsing" and then parse raw output. The raw response contains html (useless), headers, and parsing (what you want). The transform flag extracts parsing in one shot.

For the full agent list (50+ sites), see references/nimble-agents/SKILL.md.

⚠️ google_search is for SEO/SERP rank analysis only — not general information retrieval. For finding information, use nimble search.


Workflow

SituationCommandReference
Site/domain → check agent firstnimble agent list → nimble agent runreferences/nimble-agents/SKILL.md
Direct URLnimble extractreferences/nimble-extract/SKILL.md
Search the live webnimble searchreferences/nimble-search/SKILL.md
Discover URLs on a sitenimble mapreferences/nimble-map/SKILL.md
Bulk crawl a sectionnimble crawl runreferences/nimble-crawl/SKILL.md
Batch agents (up to 1,000)nimble agent run-batchreferences/nimble-agents/SKILL.md
Batch extract (up to 1,000)nimble extract-batchreferences/nimble-extract/SKILL.md
Poll tasks / batches / resultsnimble tasks / nimble batchesreferences/nimble-tasks/SKILL.md
Unknown selectors or XHR pathbrowser-use or Playwright investigationreferences/nimble-extract/browser-investigation.md
Proven site patternscopy a recipereferences/recipes.md
2+ inputsparallel bash &+wait or generated scriptreferences/batch-patterns.md

For the full extract waterfall (tiers, flags, browser actions, network capture), see references/nimble-extract/SKILL.md.


Response shapes

CommandOutput
nimble agentStructured data in data.parsing — array (SERP/list) or dict (PDP/product)
nimble extractHTML, Markdown, or parsed JSON — depends on --format and --parse
nimble searchStructured results array (title, URL, description)
nimble mapURL list + metadata
nimble crawlAsync job — poll with nimble crawl status <job_id>

Agent runs always need --transform "data.parsing". If the agent name suggests a list (serp, search, plp), expect an array. If it suggests a single item (pdp, product, profile), expect a dict.

Output & Organization

mkdir -p .nimble   # save all outputs here

Naming: .nimble/<site>-<task>.md (e.g. .nimble/amazon-airpods.md, .nimble/yelp-sf-italian.json)

Working with saved files:

wc -l .nimble/page.md && head -100 .nimble/page.md
grep -n "price\|rating" .nimble/page.md | head -30

End every response with: Source: [URL] — fetched live via Nimble CLI


Self-Improvement

The skill maintains ~/.claude/skills/nimble-web-expert/learned/examples.json.

  • At task start: read the file, scan good[] for url_pattern matches → use documented command/tier as starting point. Scan bad[] → avoid documented pitfalls.
  • After presenting results: ask "Were these results what you needed?" → on positive feedback, append to good[] with url_pattern, task, command, tier, notes. On negative feedback, ask "What went wrong?" and append to bad[] with url_pattern, task, issue, avoid, better.
  • Keep entries concise — 5–10 per site. Only write on real feedback, never speculatively.

Guardrails

  • NEVER answer from training data for live prices, current news, or real-time data. If Nimble is unavailable, say so.
  • NEVER skip Step 0 silently. Even if certain there's no agent, announce the check before running extract/search/map.
  • NEVER retry the same render tier. If a tier returns empty or blocked, escalate — do not re-run.
  • NEVER substitute WebFetch for nimble CLI tasks. WebFetch is a fallback for fetching Nimble docs only.
  • NEVER load reference files speculatively. Only read a reference when the current task explicitly needs it.
  • Task agents MUST use run_in_background=False. See nimble-agent-builder delegation model for the why.
  • Hard retry limit. On error (not empty content): retry at most 2 times with different flags. After 2 errors, report and stop.
  • Hard 429 rule. On rate-limit error: stop immediately. Do not retry or switch tiers.

Reference files

Load only when needed:

FileLoad when
references/recipes.mdNeed a proven command for a common site (Amazon, Yelp, LinkedIn…)
references/nimble-agents/SKILL.mdStep 0 lookup — full agent table (50+ sites)
references/nimble-extract/SKILL.mdExtract flags, render tiers, browser actions, network capture, parser schemas
references/nimble-search/SKILL.mdSearch flags, all 8 focus modes
references/nimble-map/SKILL.mdMap flags, response structure
references/nimble-crawl/SKILL.mdFull async crawl workflow
references/nimble-tasks/SKILL.mdPoll tasks/batches, fetch results — for async, batch, and crawl operations
references/nimble-extract/browser-investigation.mdTier 6 — CSS selector/XHR discovery with browser-use or Playwright
references/nimble-extract/parsing-schema.mdParser types, selectors, extractors, post-processors
references/nimble-extract/browser-actions.mdFull browser action types and parameters
references/nimble-extract/network-capture.mdFilter syntax, XHR mode, capture+parse patterns
references/nimble-search/search-focus-modes.mdDecision tree, mode details, combination strategies
references/batch-patterns.mdParallel bash patterns for 2–5, 6–20, and 20+ inputs
references/error-handling.mdError codes, known site issues, troubleshooting

平台分布

Codex

35.6%
按下载量换算81

Claude

32.86%
按下载量换算75

Cursor

19.51%
按下载量换算44

Gemini CLI

9.75%
按下载量换算22

安全审计

Gen Agent Trust Hub

通过

Socket

通过

Snyk

可疑

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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