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Agent Skill · 研究检索

healthcare-providers-extract(医疗保健提供者提取物)

healthcare-providers-extract 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。

healthcare-providers-extract 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 73,674 个 Skill 里排第 65,896。

总安装 272周安装 11GitHub Stars 45下载 85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:healthcare-providers-extract(医疗保健提供者提取物)
来源仓库:https://github.com/nimbleway/agent-skills
仓库路径:skills/healthcare-providers-extract
安装命令:
npx skills add https://github.com/nimbleway/agent-skills --skill healthcare-providers-extract
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 healthcare-providers-extract

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、检索和筛选医疗保健提供者相关信息。适合从多源数据中提取结构化信息。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。可结合关键词进行定向检索和结果筛选。使用前应核实数据来源的合法性与合规性。

healthcare-providers-extract 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/healthcare-providers-extract

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 healthcare-prov…;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

healthcare-providers-extract 怎么安装?

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

healthcare-providers-extract 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。

healthcare-providers-extract 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。

healthcare-providers-extract 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。

healthcare-providers-extract 用的人多吗?

公开数据是累计安装 272 次,近一周安装 11 次,下载 85 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。

healthcare-providers-extract 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
healthcare-providers-extract

医疗保健提供者提取物 · 本页

27245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

Healthcare Providers Extract

Structured practitioner extraction from healthcare practice websites, powered by Nimble's web data APIs.

User request: $ARGUMENTS

Before running any commands, read references/nimble-playbook.md for Claude Code constraints (no shell state, no &/wait, sub-agent permissions, communication style).


Instructions

Step 0: Preflight + WSA Discovery

Run the preflight pattern from references/nimble-playbook.md (5 simultaneous Bash calls: date calc, today, CLI check, profile load, index.md load).

Also simultaneously — run WSA discovery and setup:

  • mkdir -p ~/.nimble/memory/{reports,healthcare-providers-extract/checkpoints}
  • ls ~/.nimble/memory/healthcare-providers-extract/checkpoints/ 2>/dev/null
  • Run Layer 1 (vertical) and Layer 3 (general tools) WSA discovery from references/wsa-reference.md. Layer 2 (session-specific) runs after Step 1 when you know the user's specialty.

Classify discovered agents into phases and validate with nimble agent get per references/wsa-reference.md.

From the preflight results:

  • CLI missing or API key unset -> references/profile-and-onboarding.md, stop
  • Profile exists -> note it for context. Determine mode using smart date windowing from references/nimble-playbook.md:

- Full mode: first run OR last run > 14 days ago - Quick refresh: last run < 14 days ago (re-extract only new/changed pages) - Same-day repeat: if last_runs.healthcare-providers-extract is today, check for existing report at ~/.nimble/memory/reports/healthcare-providers-extract-*[today].md. If found, ask: "Already ran today. Run again for fresh data?"

  • No profile -> that's fine. This skill doesn't require onboarding. Proceed to Step 1.

Step 1: Parse Input & Starting Questions

Parse $ARGUMENTS for input type using the Input Parsing Pattern from references/nimble-playbook.md. Key routing:

  • URLs detected -> proceed to Step 3
  • Specialty + location (no URLs) -> proceed to Step 2 (practice discovery)
  • Unclear -> ask (counts as 1 of max 2 prompts)

If input is clear, confirm and ask one shaping question (plain text, not AskUserQuestion):

"Extracting providers from N practice sites. Quick questions: 1. Healthcare vertical? (ophthalmology, dental, dermatology, general, or other) 2. Quick scan (names + credentials only) or full extraction (all 5 fields)?"

If input is ambiguous, use AskUserQuestion (counts as 1 of max 2 prompts):

What practice sites should I extract providers from? - Paste URLs directly (one per line) - Provide a CSV file path or Google Sheet URL with practice URLs - Or describe what you're looking for (e.g., "ophthalmologists in Austin, TX") and I'll find practices first

Skip questions the user already answered in their initial message.

Step 2: Practice Discovery (Optional)

Only if the user provided a specialty + location instead of URLs.

Two input paths into discovery:

Path A — Fresh discovery. User gave specialty + location. Run Layer 2 WSA discovery for session-specific agents:

nimble agent list --limit 50 --search "[specialty]"
nimble agent list --limit 50 --search "[directory-user-mentioned]"

See references/wsa-reference.md for the full discovery strategy, agent evaluation criteria, and healthcare discovery prioritization.

Run all discovery-phase agents simultaneously. Validate params with nimble agent get first.

Path B — Market-finder handoff. User ran market-finder first and wants to extract providers from those results. Read the market-finder output:

cat ~/.nimble/memory/market-finder/{slug}/entities.json 2>/dev/null

Extract practice records. Note: Google Maps results contain place_url (a Maps link) but not the practice's actual website URL. Proceed to Step 2b to resolve real website URLs before site mapping.

After either path: Deduplicate by domain. Present discovered practices:

"Found N practices for [specialty] in [location] across [M] data sources. Proceeding to extract providers from these sites..."

Fallback — if no discovery WSAs were found, or results are sparse (< 3):

nimble search --query "[specialty] in [location]" --max-results 20 --search-depth lite

Step 2b: Resolve Practice Website URLs

Discovery sources (Google Maps, Yelp, BBB) return listing URLs, not practice website URLs. Before site mapping, resolve the actual website for each practice:

  1. Check structured data first — Google Maps results often include a website field in the structured output. Use it if present.
  2. Extract from listing page — if no website field, extract the Maps listing to find the practice website link: nimble extract --url "[maps-listing-url]" --format markdown
  3. Search fallback — if extraction fails: nimble search --query "[practice-name] [city] official website" --max-results 3 --search-depth lite

Skip practices where no website URL can be resolved — note them in the "Data Quality Summary" output section.

Step 3: Site Mapping

Follow the Site Mapping Pattern from references/nimble-playbook.md for each practice URL. Skill-specific settings:

  • Keyword weight table: references/provider-extraction-patterns.md
  • Page cap: 15 per site
  • Fallback query: site:[domain] doctors OR providers OR team

For 6+ practices, use sub-agents (see Sub-Agent Strategy below).

Save checkpoint: ~/.nimble/memory/healthcare-providers-extract/checkpoints/{slug}/mapping.json

Step 4: Page Extraction

WSA shortcuts first: If WSA discovery found agents that extract provider data from healthcare directories, use those for matching practices — structured WSA output is higher quality than parsed markdown.

For all other practices, follow the Page Extraction with Retry pattern from references/nimble-playbook.md. Scale using the Scaled Execution pattern from the same reference.

Save checkpoint: ~/.nimble/memory/healthcare-providers-extract/checkpoints/{slug}/extraction.json

Step 5: Structured Parsing

Parse extracted markdown to identify providers and their fields. Read references/provider-extraction-patterns.md for the 5 core fields, credential regex patterns, and specialty keywords.

For each extracted page:

  1. Scan for provider name patterns (Dr. prefix, heading patterns, bold text near credential suffixes)
  2. Match credentials using the regex patterns from references/provider-extraction-patterns.md
  3. Match specialty using keywords for the detected healthcare vertical
  4. Extract contact info (phone regex, appointment URLs, email)
  5. Extract education/training mentions

Build structured records:

{
  "name": "Dr. Jane Smith",
  "credentials": "MD, FACS",
  "specialty": "Retinal Surgery",
  "contact": {"phone": "(555) 123-4567", "scheduling_url": "..."},
  "education": "Fellowship: Bascom Palmer Eye Institute",
  "source_url": "https://practice.com/our-doctors",
  "practice_name": "Shore Center for Eye Care",
  "practice_url": "https://practice.com",
  "confidence": "High"
}

Step 6: Deduplication & Confidence Scoring

Follow the Entity Deduplication and Entity Confidence Scoring patterns from references/nimble-playbook.md. Skill-specific dedup rules and the 5-field confidence criteria are in references/provider-extraction-patterns.md.

Step 7: Output

Present results grouped by practice, sorted by confidence within each practice.

# Provider Extraction: [N] Providers from [M] Practices
*[Date] | [H] High, [M] Medium, [L] Low confidence*

## TL;DR
Extracted [N] providers from [M] practice websites. [H] with complete profiles,
[L] with partial data. [Key finding: e.g., "12 of 15 providers are board-certified"].

## [Practice Name] ([domain])

| # | Name | Credentials | Specialty | Contact | Education | Confidence |
|---|------|------------|-----------|---------|-----------|------------|
| 1 | Dr. Jane Smith | MD, FACS | Retinal Surgery | (555) 123-4567 | Fellowship: Bascom Palmer | High |
| 2 | Dr. John Doe | OD | General Ophthalmology | [Book](url) | Residency: Wills Eye | Medium |

[Repeat per practice]

## Data Quality Summary
- **Complete profiles (High):** [N] providers
- **Partial profiles (Medium):** [N] providers — missing: [list common gaps]
- **Minimal profiles (Low):** [N] providers — missing: [list common gaps]

## Sources
[Clickable URL for every page extracted, grouped by practice]

Source links are mandatory. Every provider record must trace back to a source URL.

Step 8: Save to Memory

Make all Write calls simultaneously:

  • Report -> ~/.nimble/memory/reports/healthcare-providers-extract-{slug}-{date}.md
  • Provider data -> ~/.nimble/memory/healthcare-providers-extract/{slug}/providers.json
  • Profile -> update last_runs.healthcare-providers-extract in ~/.nimble/business-profile.json (only if profile exists)
  • Follow the wiki update pattern from references/memory-and-distribution.md: update index.md rows for all affected entity files, append a log.md entry for this run.
  • Clean up checkpoint (complete run) or keep (partial run)

Step 9: Share & Distribute

Always offer distribution -- do not skip. Follow references/memory-and-distribution.md for connector detection and sharing flow.

Notion: full provider table as a dated subpage. Slack: TL;DR with provider count and confidence breakdown only.

Step 10: Follow-ups

  • "Tell me more about Dr. X" -> show full extracted profile
  • "Export as CSV" -> generate CSV from providers.json
  • "Run on more sites" -> append new practice URLs, extract and merge
  • "What's missing?" -> detail the data gaps per provider

Enrichment from discovered WSAs: If Step 0 found enrichment-phase agents (reviews, regulatory, practice details), offer them as immediate follow-ups:

"I also found [N] WSAs that could enrich this data: [brief list]. Want me to run reputation checks or regulatory lookups on these providers/practices?"

See references/wsa-reference.md for enrichment phase mapping and fallback chains.

Sibling skill suggestions:

Next steps: - Run healthcare-providers-enrich to fill data gaps (NPI lookup, board certification verification, additional contact info) - Run healthcare-providers-verify to validate credentials and license status - Run market-finder to discover more practice URLs in this area

Sub-Agent Strategy

For batch extraction (6+ practices), use nimble-researcher agents (agents/nimble-researcher.md) to parallelize site mapping and extraction.

Follow the sub-agent spawning rules from references/nimble-playbook.md (bypassPermissions, batch max 4, explicit Bash instruction, fallback on failure).

Spawn pattern: One agent per practice (or per batch of 3 practices for large jobs). Each agent runs Steps 3-5 for its assigned practices and returns structured provider records.

Single-practice optimization: If only 1-2 practices, run directly from the main context instead of spawning agents.

Fallback: If any agent fails, run those extractions directly from the main context. Never leave gaps in the output.


Error Handling

See references/nimble-playbook.md for the standard error table (missing API key, 429, 401, empty results, extraction garbage). Skill-specific errors:

  • No provider pages found: "Couldn't find provider/team pages on [domain]. The site may list staff differently. Want me to try extracting from the homepage or search for this practice on healthcare directories?"
  • All extractions returned garbage: "The practice sites appear to be heavily JavaScript-rendered. Retrying with browser rendering..." (auto-retry with --render per the shared pattern)
  • Ambiguous practice name: If a URL fails and the user provided a name instead, search for the practice: nimble search --query "[practice name] [location] doctors" --max-results 5 --search-depth lite
  • CSV/Sheet parse error: "Couldn't parse the input file. Expected a column with practice URLs. Can you paste the URLs directly instead?"

平台分布

Codex

37.5%
按下载量换算32

Claude

29.69%
按下载量换算25

Cursor

19.19%
按下载量换算16

Gemini CLI

9.41%
按下载量换算8

安全审计

Gen Agent Trust Hub

通过

Socket

可疑

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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