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Agent Skill · 研究检索

healthcare-providers-enrich(医疗保健提供者丰富)

healthcare-providers-enrich 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-enrich 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 66,577。

总安装 261周安装 11GitHub Stars 45下载 92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-enrich(医疗保健提供者丰富)
来源仓库:https://github.com/nimbleway/agent-skills
仓库路径:skills/healthcare-providers-enrich
安装命令:
npx skills add https://github.com/nimbleway/agent-skills --skill healthcare-providers-enrich
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-enrich

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。适合在机构管理、合作对接等场景中快速定位目标。可结合关键词和业务需求进行定向检索。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。使用前应核实信息来源的准确性和更新频率。

healthcare-providers-enrich 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-enrich

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-enrich 怎么安装?

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

healthcare-providers-enrich 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-enrich 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-enrich 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-enrich 用的人多吗?

公开数据是累计安装 261 次,近一周安装 11 次,下载 92 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-enrich 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-enrich

医疗保健提供者丰富 · 本页

26145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 Enrich

Fill gaps in existing practitioner lists with verified web data, 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

Sibling handoff check: Before running full preflight, check if healthcare-providers-extract ran earlier in this session by following the Sibling Handoff pattern from references/nimble-playbook.md. If same-day extract output exists, skip CLI check and profile load, and reuse WSA Layer 1/3 inventory. Only re-run Layer 2 if the specialty changed.

Otherwise, run full preflight 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-enrich/checkpoints}
  • ls ~/.nimble/memory/healthcare-providers-enrich/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-enrich only records with gaps) - Same-day repeat: if last_runs.healthcare-providers-enrich is today, check for existing report at ~/.nimble/memory/reports/healthcare-providers-enrich-*[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

Chained-from-extract shortcut: Check for a same-day extract report:

ls ~/.nimble/memory/reports/healthcare-providers-extract-*$(date +%Y-%m-%d).md 2>/dev/null

If a same-day report exists, parse the {slug} from the filename and load ~/.nimble/memory/healthcare-providers-extract/{slug}/providers.json. The practice domains and page URL patterns are already known — construct individual bio page URLs from the site's URL convention and skip Step 3 entirely. This avoids N unnecessary web searches. If no same-day report exists, do not reuse old providers.json files.

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

  • Extract output detected (providers.json) -> proceed to Step 2, mark Step 3 skip
  • CSV/Sheet/pasted data detected -> proceed to Step 2
  • Unclear -> ask (counts as 1 of max 2 prompts)

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

"Found N providers in your list. Quick questions: 1. Which fields need filling? (contact info, credentials, specialty, reviews, regulatory — or all gaps) 2. Healthcare vertical? (ophthalmology, dental, dermatology, general, or other)"

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

What provider list should I enrich? - Paste provider data directly (name + any known info, one per line) - Provide a CSV file path or Google Sheet URL - Or describe what you have (e.g., "a list of 50 ophthalmologists with just names and states")

Skip questions the user already answered in their initial message.

Step 2: Analyze Existing Data

Parse the input into structured records. For each provider, identify:

  • Known fields — what the user already has (name, state, specialty, etc.)
  • Missing fields — gaps against the 5 core fields from references/provider-extraction-patterns.md (name, credentials, specialty, contact, education)
  • Enrichment targets — additional fields the user requested (reviews, regulatory, accreditation)

Early exit — no gaps: If all providers are already High confidence (5/5 fields), skip to Step 5 (WSA enrichment) or report: "All providers already have complete profiles. Want me to add supplementary data (reviews, clinical trials, accreditation) instead?"

Build a gap analysis summary:

"Analyzing N providers: - Names: N/N present - Credentials: N/N present (N missing) - Specialty: N/N present (N missing) - Contact info: N/N present (N missing) - Education: N/N present (N missing) Starting enrichment for N providers with gaps..."

Run Layer 2 WSA discovery now that you know the specialty:

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

See references/wsa-reference.md for session-specific discovery.

Step 3: Web Search for Provider Identity

For each provider with gaps, find their practice website and bio page:

nimble search --query "[provider name] [credentials] [location] [specialty]" --max-results 5 --search-depth lite

Search strategy:

  • Include all known fields in the query to disambiguate common names
  • Prioritize results from practice websites over directory listings
  • If the provider has a known practice name, add it to the query
  • For providers with only name + state, broaden: "[name] [state] doctor"

Result selection: Pick the most relevant result — practice bio page > healthcare directory profile > LinkedIn. Save the selected URL for extraction.

For 10+ providers, use sub-agents (see Sub-Agent Strategy below).

Checkpoint (mandatory): You MUST write the checkpoint file before proceeding. Interrupted runs with 20+ providers waste significant API credits without resume.

echo '{...}' > ~/.nimble/memory/healthcare-providers-enrich/checkpoints/{slug}/search.json

Step 4: Extract Missing Fields

Choose extraction strategy based on provider count. Follow the Scaled Execution pattern from references/nimble-playbook.md — it covers individual calls (1-10), extract-batch (11-100), and the confirmation gate for larger jobs. Use the Page Extraction with Retry pattern from the same reference for garbage detection and retry logic.

Parse extracted content for missing fields using the detection patterns from references/provider-extraction-patterns.md (credential regex, specialty keywords, contact patterns, education mentions).

Merge rules:

  • Only fill fields that are actually missing — never overwrite existing data
  • Track which fields were added and their source URL
  • If extracted data conflicts with existing data, keep the existing value and flag the conflict for user review

Checkpoint (mandatory): You MUST write the checkpoint file before proceeding.

echo '{...}' > ~/.nimble/memory/healthcare-providers-enrich/checkpoints/{slug}/extraction.json

Step 5: WSA Enrichment (Optional)

If the user requested reviews, regulatory data, or accreditation — or if the gap analysis shows most core fields are already filled and enrichment adds more value:

Run enrichment-phase WSAs discovered in Step 0. See references/wsa-reference.md for the enrichment phase mapping, agent evaluation, and fallback chains.

For each practice or provider, run relevant enrichment agents simultaneously. Follow the Scaled Execution pattern from references/nimble-playbook.md for batching.

Merge enrichment data into provider records:

  • Reviews/ratings -> add as supplementary fields (not part of core 5)
  • Clinical trial activity -> add as supplementary field
  • Accreditation status -> add as supplementary field

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.

Enrichment-specific confidence: Score only the newly added fields:

  • High — field found and confirmed by 2+ sources
  • Medium — field found from 1 source
  • Low — field inferred or partially matched

Step 7: Output

Present results as an enrichment diff — showing what was added to each provider. Group by practice, sort by confidence within each group, and include a "What This Means" section at the end with actionable next steps.

# Provider Enrichment: [N] Providers Updated
*[Date] | [A] fields added across [P] providers | [H] High, [M] Medium, [L] Low confidence*

## TL;DR
Enriched [P] of [T] providers. Added [A] total fields: [breakdown by field type].
[Key finding: e.g., "Found contact info for 18 of 20 providers, 3 have clinical trials"].

## Enrichment Results

| # | Name | Added Fields | Confidence | Source |
|---|------|-------------|------------|--------|
| 1 | Dr. Jane Smith | +credentials (MD, FACS), +contact ((555) 123-4567) | High | [source](url) |
| 2 | Dr. John Doe | +specialty (General Ophthalmology), +education (Wills Eye) | Medium | [source](url) |
| 3 | Dr. Alex Chen | +contact ((555) 987-6543) | Low | [source](url) |

## Detailed Records

### Dr. Jane Smith
**Existing:** Name, State (TX)
**Added:**
- Credentials: MD, FACS — [source](url)
- Contact: (555) 123-4567 — [source](url)
- Education: Fellowship, Bascom Palmer Eye Institute — [source](url)
**Confidence:** High (3 fields added, 2 sources)

[Repeat per provider with additions]

## Providers Not Enriched
[List providers where no additional data was found, with attempted searches]

## Data Quality Summary
- **Fully enriched (5/5 fields):** [N] providers
- **Partially enriched:** [N] providers — common gaps: [list]
- **No new data found:** [N] providers

## Sources
[Clickable URL for every page used, grouped by provider]

## What This Means
[Actionable interpretation: which providers are ready to contact, which need more
data, what the enrichment coverage tells you about this list's quality]

Source links are mandatory. Every added field must trace back to a source URL.

Step 8: Save to Memory

Make all Write calls simultaneously:

  • Report -> ~/.nimble/memory/reports/healthcare-providers-enrich-{slug}-{date}.md
  • Enriched data -> ~/.nimble/memory/healthcare-providers-enrich/{slug}/enriched.json
  • Profile -> update last_runs.healthcare-providers-enrich 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 enrichment report as a dated subpage. Slack: TL;DR with enrichment summary and field counts only.

Step 10: Follow-ups

  • "Tell me more about Dr. X" -> show full enriched profile
  • "Export as CSV" -> generate CSV with original + enriched fields
  • "Enrich more fields" -> re-run with expanded field targets
  • "Which providers still have gaps?" -> filter to incomplete records

Sibling skill suggestions:

Next steps: - Run healthcare-providers-verify to validate the enriched credentials and license status - Run healthcare-providers-extract to discover more providers from practice websites - Run market-finder to find additional practices in this area

Sub-Agent Strategy

For batch enrichment (10+ providers), use nimble-researcher agents (agents/nimble-researcher.md) to parallelize search 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 batch of 5 providers. Each agent runs Steps 3-4 for its assigned providers and returns enriched records. Tell each agent to use nimble extract-batch for its assigned URLs rather than individual nimble extract calls — one batch call per agent is faster and more reliable than sequential calls.

Small batch optimization: If fewer than 10 providers, run directly from the main context instead of spawning agents.

Fallback: If any agent fails, run those enrichments 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 search results for provider: "Couldn't find a web presence for [name] in [state]. The name may be too common or the provider may not have an online presence. Want me to try with additional context (practice name, specialty)?"
  • Ambiguous provider match: "Found multiple providers named [name] in [state]. Can you confirm which one? [list top 3 with practice names]"
  • All extractions returned garbage: "The provider websites appear to be heavily JavaScript-rendered. Retrying with browser rendering..." (auto-retry with --render per the shared pattern)
  • CSV/Sheet parse error: "Couldn't parse the input file. Expected columns with provider names and at least one identifier (state, specialty, or practice). Can you paste the data directly instead?"
  • No gaps detected: Handled in Step 2 (early exit to WSA enrichment or report).

平台分布

Codex

35.07%
按下载量换算32

Claude

29.88%
按下载量换算27

Cursor

20.71%
按下载量换算19

Gemini CLI

8.84%
按下载量换算8

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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