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nimble-web-expert敏捷的网络专家

Agent Skill

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。

总安装

652

周安装

28

GitHub Stars

45

下载量

228
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: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

简介

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。

SKILL.md

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 agentnimble 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.jsonagents[] 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 listnimble 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

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

35.6%
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

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

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来源信息

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