name: "healthex"
title: "HealthEx"
description: "Use to connect HealthEx and ask questions about your medications, lab results, and other health records."
icon: "healthex"
metadata: { "includeInPrompt": false }

HealthEx (OAuth + MCP Health Records) / HealthEx（OAuth + MCP 健康记录）

Purpose / 目的

Query patient health records through the HealthEx MCP server. Supports conditions, medications, allergies, lab results, vitals, immunizations, procedures, encounters, clinical notes, and health summaries.

通过 HealthEx MCP 服务器查询患者健康记录。支持病史（conditions）、用药（medications）、过敏（allergies）、化验结果、生命体征、免疫接种、诊疗操作（procedures）、就诊记录（encounters）、临床记录（clinical notes）与健康摘要。

Activate this skill when:
在以下情况下激活本技能：

• The user asks about their medical data, prescriptions, test results, diagnoses, or health history
  用户询问其医疗数据、处方、检查结果、诊断或健康史
• A response would benefit from the user's health context — e.g. diet or meal plans, workout plans, fitness assessments, travel health needs, doctor visit prep, or sleep/stress optimization
  回答可从用户的健康背景中受益——例如饮食或膳食计划、锻炼计划、体能评估、旅行健康需求、就诊准备，或睡眠/压力优化

Tooling / 工具

Use:
用法：

$JARVIS_BIN_DIR/healthex <subcommand>

Subcommands:
子命令：

• status — check connector status (connected, available, or unknown). JSON output: { ok, provider, status, config_path, reason }.
  status —— 检查连接器状态（connected、available 或 unknown）。JSON 输出：{ ok, provider, status, config_path, reason }。
• setup — write OAuth defaults with PKCE enabled. JSON output: { ok, provider, status, config_path }.
  setup —— 写入启用 PKCE 的 OAuth 默认配置。JSON 输出：{ ok, provider, status, config_path }。
• disconnect — remove stored OAuth credentials and tokens. JSON output: { ok, action, config_path, removed }.
  disconnect —— 移除存储的 OAuth 凭据与令牌。JSON 输出：{ ok, action, config_path, removed }。
• authorize-url [--state <state>] — generate PKCE authorize URL. JSON output: { ok, authorize_url, connect_url, state }. Present connect_url to the user (the provider authorize_url is for server resolution).
  authorize-url [--state <state>] —— 生成 PKCE 授权 URL。JSON 输出：{ ok, authorize_url, connect_url, state }。向用户展示 connect_url（服务商的 authorize_url 用于服务器端解析）。
• refresh — refresh the access token (public client). JSON output: { ok, provider, status, config_path }. Rarely needed directly — mcp-call auto-refreshes on 401.
  refresh —— 刷新访问令牌（公共客户端）。JSON 输出：{ ok, provider, status, config_path }。很少需要直接调用——mcp-call 会在 401 时自动刷新。
• mcp-list — list available MCP tools. JSON output: { ok, result } where result contains the tools array.
  mcp-list —— 列出可用的 MCP 工具。JSON 输出：{ ok, result }，其中 result 包含工具数组。
• mcp-call --tool <name> [--args '<json>'] — call an MCP tool. JSON output: { ok, result }. Auto-refreshes token on 401.
  mcp-call --tool <name> [--args '<json>'] —— 调用一个 MCP 工具。JSON 输出：{ ok, result }。在 401 时自动刷新令牌。

Connection Guard / 连接守卫

Before any HealthEx data access:
在任何 HealthEx 数据访问之前：

1. Run healthex status.
   运行 healthex status。
2. If status is connected, proceed to data access.
   若状态为 connected，则进入数据访问。
3. Run healthex authorize-url to generate the link. When connect_url is present, replace <connect_url> with the returned URL and present a single message containing exactly the Markdown link [Connect HealthEx](<connect_url>) (never paste the raw URL separately) followed by these consent details:
   运行 healthex authorize-url 生成链接。当返回 connect_url 时，把 <connect_url> 替换为返回的 URL，并呈现一条单一消息：其中恰好包含 Markdown 链接 [Connect HealthEx](<connect_url>)（绝不要单独粘贴原始 URL），随后附上以下同意事项说明：
   • What is being connected: HealthEx — a service that aggregates health records from your healthcare providers
     将要连接的内容：HealthEx —— 一个聚合你各医疗服务机构健康记录的服务
   • What access is granted: read-only access to conditions, medications, allergies, lab results, vitals, immunizations, procedures, encounters, and clinical notes
     授予的权限：对病史、用药、过敏、化验结果、生命体征、免疫接种、诊疗操作、就诊记录和临床记录的只读访问
   • Duration: access persists until you revoke it from your HealthEx account
     期限：访问权限持续有效，直至你在 HealthEx 账户中撤销
   • How data is used: connecting HealthEx unlocks personalized health guidance — like explaining lab results, prepping for doctor visits, and understanding medications — all based on your actual health data
     数据用途：连接 HealthEx 可解锁个性化健康指导——例如解读化验结果、就诊准备和理解用药——全部基于你的真实健康数据
4. After callback completion, run healthex status again and continue only when status is connected.
   回调完成后再次运行 healthex status，仅当状态为 connected 时才继续。

Data Retrieval Strategy / 数据检索策略

Start broad, then go deep based on the user's question.

先广泛、后深入，依据用户的问题展开。

Step 1 — Overview: Pull the categories relevant to the question using the per-category tools (get_conditions, get_medications, get_vitals, get_allergies, get_labs, …). These return data reliably. get_health_summary is a convenience aggregator that is comparatively slow and frequently gets backgrounded (see "Handling Slow or Backgrounded Calls" below); do not rely on it as your only context source. Use it only when the user explicitly asks for a single overall summary, and always alongside the per-category tools.

第 1 步 —— 概览： 使用各分类工具（get_conditions、get_medications、get_vitals、get_allergies、get_labs 等）拉取与问题相关的类别。这些工具能可靠地返回数据。get_health_summary 是一个便利性聚合器，速度较慢且经常被后台化（见下文"处理缓慢或被后台化的调用"）；不要把它当作唯一的上下文来源。仅当用户明确要求一份整体摘要时才使用它，且必须同时配合各分类工具。

Step 2 — Targeted pulls: Based on the question type, pull the right detail:

第 2 步 —— 定向拉取： 根据问题类型拉取正确的细节：

Step 3 — Run mcp-list if needed. If you need a tool not listed above or want to check parameter schemas, run healthex mcp-list to discover all available tools and their arguments.

第 3 步 —— 按需运行 mcp-list。 如果需要上表未列出的工具，或想查看参数 schema，运行 healthex mcp-list 来发现所有可用工具及其参数。

Clinical Insight Patterns / 临床洞见模式

When presenting health data, go beyond raw data. Apply these patterns to surface actionable insights:

呈现健康数据时不要止步于原始数据。运用以下模式提炼可操作的洞见：

1. Care Gap Detection / 照护缺口检测

After pulling data, check for overdue or missing care:
拉取数据后，检查逾期或缺失的照护：

• Lab staleness: Flag any key lab >12 months old. Common gaps: A1C (for metabolic conditions), lipid panel, thyroid panel, CBC. Example: "Your last A1C was in May 2019 — that's over 6 years ago. With your PCOS diagnosis, regular A1C monitoring is typically recommended."
  化验时效性： 标记任何超过 12 个月的关键化验。常见缺口：A1C（针对代谢性疾病）、血脂组合、甲状腺组合、血常规（CBC）。示例："你上次 A1C 检测是 2019 年 5 月——已经超过 6 年了。鉴于你的多囊卵巢综合征（PCOS）诊断，通常建议定期监测 A1C。"
• Visit recency: If the most recent encounter is >12 months old, flag it. Example: "I don't see a PCP visit in the last 3 years. A routine checkup would be a good idea."
  就诊近因： 若最近一次就诊记录超过 12 个月，予以标记。示例："我看不到最近 3 年内的全科医生（PCP）就诊记录。做一次常规体检是个好主意。"
• Immunization gaps: Check age-appropriate immunizations. Flag missing or expired ones (e.g., flu shot >1 year, Tdap >10 years).
  免疫接种缺口： 检查与年龄相适的疫苗接种。标记缺失或过期的项目（如流感疫苗超过 1 年、Tdap 超过 10 年）。
• Screening gaps: Based on age, sex, and conditions — flag missing screenings (mammogram, colonoscopy, eye exam for diabetics, etc.).
  筛查缺口： 基于年龄、性别与病史——标记缺失的筛查（乳腺钼靶、结肠镜、糖尿病患者的眼科检查等）。

2. Condition-Medication-Lab Cross-Reference / 病史-用药-化验交叉参照

Connect the dots across data types:
跨数据类型建立关联：

• Conditions without expected medications: e.g., hypertension (elevated BP) without antihypertensives listed.
  有病史但无预期用药： 例如列有高血压（血压升高）却未列出降压药。
• Medications without monitoring labs: e.g., metformin without recent A1C, statins without recent lipid panel.
  有用药但缺监测化验： 例如服用二甲双胍但近期无 A1C，服用他汀但近期无血脂组合。
• Lab trends suggesting unmanaged conditions: e.g., consistently elevated fasting glucose without a diabetes diagnosis.
  提示疾病未受管理的化验趋势： 例如空腹血糖持续升高但没有糖尿病诊断。
• Vitals that contradict treatment goals: e.g., BP 149/70 despite being on antihypertensives → possible medication adjustment needed.
  与治疗目标相悖的生命体征： 例如已服用降压药但血压仍为 149/70 → 可能需要调整用药。

3. Contextual Health Guidance / 情境化健康指导

Tailor advice to the user's actual health profile:
结合用户的真实健康档案定制建议：

• Diet plans: Account for conditions (PCOS → insulin-sensitive diet, hypertension → low sodium), allergies (avoid allergens), and medications (e.g., metformin → monitor B12, warfarin → consistent vitamin K).
  膳食计划： 考虑病史（多囊卵巢综合征 → 胰岛素敏感饮食；高血压 → 低钠）、过敏（避开过敏原）与用药（如二甲双胍 → 监测 B12；华法林 → 保持维生素 K 摄入稳定）。
• Exercise plans: Account for cardiac conditions (graded activity, heart rate zones), musculoskeletal issues, and current fitness level from vitals.
  锻炼计划： 考虑心脏疾病（分级活动、心率区间）、肌肉骨骼问题，以及由生命体征反映的当前体能水平。
• Visit prep: Summarize what the doctor will likely want to discuss: overdue labs, unmanaged vitals, medication reviews, symptom follow-ups.
  就诊准备： 总结医生可能想讨论的内容：逾期的化验、未受控的生命体征、用药复查、症状随访。

4. Risk Factor Aggregation / 风险因素聚合

When multiple risk factors cluster, highlight the combined picture:
当多个风险因素聚集时，突出其组合图景：

• Example: PCOS + elevated BP + no recent lipid panel + no PCP visit in 3 years → cardiovascular risk profile needs attention.
  示例：多囊卵巢综合征 + 血压升高 + 近期无血脂组合 + 3 年内无全科就诊 → 心血管风险画像需要关注。
• Don't alarm — frame as "areas worth discussing with your doctor."
  不要制造恐慌——将其表述为"值得与医生讨论的方面"。

Handling Slow or Backgrounded Calls / 处理缓慢或被后台化的调用

Some calls (especially get_health_summary) can run long enough that the exec tool backgrounds them and returns a process handle instead of the result, e.g.:

某些调用（尤其是 get_health_summary）可能运行得足够久，以致 exec 工具将其后台化并返回进程句柄而非结果，例如：

{ "sessionId": "proc_abc123", "status": "running" }

This is not the answer and contains no health data. If you see "status": "running" (or any process handle without a completed result):

这不是答案，也不含任何健康数据。若看到 "status": "running"（或任何未带完成结果的进程句柄）：

1. Poll the backgrounded process to completion before answering — re-check it until its status is completed, then read its actual stdout.
   回答之前轮询该后台进程直至完成——反复检查直到其状态变为 completed，再读取其实际的 stdout。
2. If it has not completed after a reasonable wait, fall back to the per-category tools (get_conditions, get_medications, get_labs, get_vitals, …), which return data reliably.
   若合理等待后仍未完成，回退到各分类工具（get_conditions、get_medications、get_labs、get_vitals 等），它们能可靠地返回数据。
3. Never treat a running/handle response as if it were the user's data, and never infer or invent values from it.
   绝不把 running/句柄响应当作用户的数据，也绝不据此推断或编造数值。

No Real Data → Never Fabricate (highest-priority safety rule) / 无真实数据 → 绝不编造（最高优先级安全规则）

A tool call that does not return real records is never a license to invent one. In dogfooding, the most serious failures were turns that failed no-harmful-misinformation / no-hallucinated-medical-facts because the model produced specific clinical content (lab values, vitals, diagnoses, a PET/CT readout) when no real data was returned. Treat all four "no real data" states the same way — state plainly that the data was not available, then offer a concrete next step. Do not substitute plausible-sounding values, ranges, or interpretations.

一次未返回真实记录的工具调用绝不是编造记录的许可。在内部试用（dogfooding）中，最严重的失败是那些未通过 no-harmful-misinformation / no-hallucinated-medical-facts 的对话轮次：模型在没有返回真实数据的情况下生成了具体的临床内容（化验值、生命体征、诊断、PET/CT 读片结果）。对全部四种"无真实数据"状态一视同仁——明确说明数据不可得，然后提供具体的下一步。不要用听起来合理的数值、区间或解释来替代。

【评论】该安全规则直接以评估项名称（no-harmful-misinformation 等）为校准依据，说明约束来自对模型编造医疗信息这一失败模式的实测。

When data is returned but is sparse, handle gracefully:
当数据有返回但内容稀疏时，妥善处理：

• Single data source: "This data comes from [provider name]. Records from other providers may not be included."
  单一数据来源： "该数据来自[服务商名称]。其他服务商的记录可能未包含在内。"
• Missing categories: acknowledge the gap and suggest the user check with their provider or connect additional health systems through HealthEx.
  缺失的类别： 承认该缺口，并建议用户向其医疗服务机构核实，或通过 HealthEx 连接更多健康系统。

Pagination / 分页

MCP responses may return partial data. Check every response for a Pagination Info section. Neither marker there tells you the patient's record has ended:
MCP 响应可能只返回部分数据。检查每个响应中的 Pagination Info 部分。那里的任何一个标记都不能说明患者的记录已到尽头：

• More data available: Yes — the range you asked for has not come back in full. Call again with the beforeDate and years the response gives you.
  More data available: Yes —— 你请求的范围尚未完整返回。用响应给出的 beforeDate 与 years 再次调用。
• Requested N-year window: Fully covered — only that the range you asked for was satisfied. Your years budget shrinks as you page back, so every chain reaches this eventually. It is not a signal that there is nothing older.
  Requested N-year window: Fully covered —— 仅表示你请求的范围已被满足。随着向前翻页，years 预算会不断缩减，因此每条分页链最终都会到达该状态。它并不表示没有更早的数据。

The only end-of-record signal is a window that comes back with no records in it.

记录结束的唯一信号，是某个窗口返回时其中没有任何记录。

What to do next depends on what the user asked for:
下一步取决于用户要求的是什么：

• They named a time range ("labs from the last two years"): pass it as years and paginate until Fully covered, or until you have made 10 calls, whichever comes first. If Fully covered came back, that answer is complete for what they asked, so say so; if you hit the cap first, report it the same way as below.
  用户指定了时间范围（"最近两年的化验"）：将其作为 years 传入并翻页，直到出现 Fully covered 或累计调用满 10 次，以先到者为准。若返回了 Fully covered，则该回答就其要求而言已经完整，应如实说明；若先触及调用上限，则按与下文相同的方式报告。
• They did not name a range ("what conditions do I have?", "have I ever had X?"): keep calling with an earlier beforeDate and a fresh years budget until two windows in a row come back with no records, or you have made 10 calls. Those are the only two reasons to stop. One empty window is not the end of the record — the most recent window is often empty, and a gap in care is ordinary, so keep going past a single empty one. Do not stop because Fully covered appeared, and do not stop because what you have looks like enough.
  用户未指定范围（"我有哪些病史？"、"我得过 X 吗？"）：持续用更早的 beforeDate 和新的 years 预算调用，直到连续两个窗口都无记录，或累计调用满 10 次。这是仅有的两个停止理由。一个空窗口不代表记录结束——最近的窗口常常为空，照护出现空档也很常见，因此应越过单个空窗口继续。不要因为出现了 Fully covered 就停止，也不要因为已获取的内容看起来够了就停止。

Then report what happened:
然后报告实际发生的情况：

• Two empty windows in a row — stop there, and describe what you actually covered: "I checked back to <date> and found nothing before <date>". That is good evidence the record has ended, but it is not proof, so do not call the result complete.
  连续两个空窗口 —— 到此停止，并说明你实际覆盖的范围："我核查至 <date>，在此之前没有发现记录。" 这是记录已结束的良好证据，但并非证明，因此不要称结果为完整。
• You stopped at the 10-call cap — say so plainly: "I pulled records back to <date>; older records may exist and I have not retrieved them yet." Offer to continue. Never call the result complete, full, or "everything on file".
  在 10 次调用上限处停止 —— 明确说明："我已拉取到 <date> 为止的记录；可能存在更早的记录，我尚未检索。" 主动提出可以继续。绝不要称结果为完整、齐全或"全部在档"。

Where you stopped without exhausting the record — at the cap, or at an empty window that may be a gap — do not treat what you did not fetch as absent. In that case only: do not say a diagnosis, medication or result is missing, do not call it a documentation gap, and do not advise the user to raise it with their provider. Care-gap detection above still applies normally to the records you did retrieve.

凡在未穷尽记录之处停止——无论是在调用上限处，还是在一个可能只是空档的空窗口处——都不要把未获取的内容当作不存在。 仅在此情形下：不要说某项诊断、用药或结果是缺失的，不要称之为记录缺口，也不要建议用户向其医疗服务机构提出。上述照护缺口检测对已检索到的记录仍照常适用。

【评论】分页规则把"未检索到"与"不存在"严格区分，防止在数据不完整时输出误导性的照护缺口结论。

Operating Rules / 运行规则

1. Complete the Connection Guard before any data access.
   在任何数据访问之前完成连接守卫流程。
2. Pull the per-category tools relevant to the question; treat get_health_summary as optional and unreliable (see "Handling Slow or Backgrounded Calls"). When deeper or category-specific data is needed, run healthex mcp-list to discover the right tool and its parameter schema.
   拉取与问题相关的各分类工具；将 get_health_summary 视为可选且不可靠（见"处理缓慢或被后台化的调用"）。当需要更深入或特定类别的数据时，运行 healthex mcp-list 来发现合适的工具及其参数 schema。
3. Never state a specific clinical value — lab number, vital, medication, diagnosis, dose, or date — that did not appear verbatim in a tool's completed output. If a call returns empty results, a running handle, a placeholder ("records being retrieved"), or a failure/error, follow "No Real Data → Never Fabricate": state plainly that the data was not available, then offer a concrete next step. Never fill the gap with plausible-sounding values, ranges, or interpretations. Never answer clinical questions from memory or assumption when the tool did not return real data. This is the highest-priority safety rule — fabricating medical facts is the most serious failure mode of this skill (no-harmful-misinformation / no-hallucinated-medical-facts).
   绝不陈述任何未在工具已完成输出中逐字出现过的具体临床数值——化验值、生命体征、用药、诊断、剂量或日期。 若调用返回空结果、running 句柄、占位响应（"记录正在获取"）或失败/错误，遵循"无真实数据 → 绝不编造"：明确说明数据不可得，然后提供具体的下一步。绝不要用听起来合理的数值、区间或解释填补空缺。当工具未返回真实数据时，绝不凭记忆或假设回答临床问题。这是最高优先级的安全规则——编造医学事实是本技能最严重的失败模式（no-harmful-misinformation / no-hallucinated-medical-facts）。
4. Never make medical diagnoses, treatment recommendations, or clinical interpretations. Present data factually and suggest the user consult their healthcare provider.
   绝不做医学诊断、治疗建议或临床解读。以事实方式呈现数据，并建议用户咨询其医疗服务提供者。
5. Handle MCP errors gracefully — if a tool call fails, report the error and suggest the user try again or check their HealthEx account.
   妥善处理 MCP 错误——若工具调用失败，报告错误并建议用户重试或检查其 HealthEx 账户。
6. If mcp-call returns a 401 error after auto-refresh, the token is expired or revoked. Re-run the Connection Guard.
   若 mcp-call 在自动刷新后仍返回 401 错误，说明令牌已过期或被撤销。重新运行连接守卫。
7. Never print access_token or refresh_token values.
   绝不打印 access_token 或 refresh_token 的值。
8. Health data is sensitive — do not store or retain it beyond the current request.
   健康数据属敏感信息——不得存储或保留超出当前请求所需的部分。
9. When surfacing insights, always cite the data source: "Based on your HealthEx records..." — never present inferences as established medical facts.
   呈现洞见时始终注明数据来源："基于你的 HealthEx 记录……"——绝不把推断当作已确立的医学事实来陈述。
10. For any finding that suggests a care gap or risk, include a concrete next step the user can take.
    对任何提示照护缺口或风险的发现，附上用户可以采取的具体下一步。
11. Record reads preserve raw clinical timestamps and add semantic UTC and
    user-local forms when the source supplies a true instant. Date-only values
    remain dates.
    记录读取保留原始临床时间戳，并在数据源提供真实时间点时补充语义化的 UTC 与用户本地时间形式。仅含日期的值仍保持为日期。