health-qa

name	health-qa
description	Answer health questions by routing to the most relevant specialist subagent(s) from the 10-agent roster, grounded in the user's own data.
user-invocable	false

Health Q&A

Use this skill when:

• the user asks a health-related question about their own data (e.g. "how's my HRV?", "am I eating enough protein?", "should I train today?")
• the user asks for health advice that can be answered by one or more specialist agents
• the user references sleep, recovery, strain, nutrition, supplements, experiments, or body metrics

This is the REQUIRED path for health data questions. Do not skip this skill and answer directly by calling raw tools (health_profile, nutrition, etc.) yourself. The specialist agents have calibrated decision logic, flag thresholds, and domain expertise that the main agent does not replicate. Always route through this skill — fetch the data, spawn the specialists, return their answers.

Do NOT use this skill when:

• the user wants to log a meal (use snap)
• the user wants to update their health profile (use health)
• the user wants to start/manage an experiment (use insights)
• the question is general knowledge with no connection to the user's data

Step 1: Classify the question

Map the user's question to 1-3 relevant specialist agents using this routing table:

Domain	Agent File	When to Route
Overall priority / "what should I focus on?"	imperial-physician.md	General health questions, "how am I doing?", priority questions
Nutrition, meals, macros, calories, diet	diet-physician.md	Food, eating, protein, calories, macros, meal timing
Exercise, training, strain, workout	movement-master.md	Training advice, workout planning, strain, exercise
HRV, heart rate, SpO2, recovery score, body metrics	pulse-reader.md	Vital signs, cardiovascular, Whoop metrics
Cross-domain patterns, correlations	formula-tester.md	"Why is my X affecting Y?", pattern questions
Supplements, micronutrients, vitamins	herbalist.md	Supplement questions, vitamin/mineral gaps
Experiment status, check-ins, compliance	trial-monitor.md	"How's my experiment going?", check-in reminders
Experiment design, "should I test X?"	court-magistrate.md	Trial design, hypothesis questions
Safety, overtraining, warning signs	medical-censor.md	"Am I overtraining?", safety concerns, red flags
Research, studies, news	court-scribe.md	"Any research on X?", literature questions

Routing rules:

• Always include imperial-physician.md if the question is broad or ambiguous
• Always include medical-censor.md if there's any safety concern in the question
• For narrow questions (e.g. "how's my HRV?"), route to just 1 agent
• Maximum 3 agents per question — pick the most relevant
• When in doubt between 2 agents, include both

Step 2: Gather data for the agents

Call the raw tools to fetch the data each selected agent will need. Only fetch what's relevant:

Agent Needs	Tool Call
Nutrition data	nutrition with command: "weekly_summary" and/or command: "lookup"
Health profile / Whoop metrics	health_profile with command: "show"
Experiment status	experiments with command: "status"
News / research	news_digest with command: "show"

Fetch in parallel when multiple tools are needed.

Step 3: Spawn specialist agents

For each selected agent:

1. Read the agent prompt: read("{baseDir}/../../agents/{file}")
2. Construct the task:

{contents of the agent .md file}

---

IMPORTANT: You are answering a specific user question, not giving a daily briefing.
- Answer the user's question directly using your domain expertise and the data below.
- Your response MUST start with your role tag (e.g. [Pulse Reader 💓]) on its own line.
- Keep it to 2-3 sentences, grounded in the data.

USER'S QUESTION:
{the user's original question}

AVAILABLE DATA:
{paste the relevant data fetched in Step 2}

3. Spawn: sessions_spawn(task=<constructed task>, label=<role name>)

Spawn all selected agents in parallel.

Step 4: Collect and respond

Wait for all spawned agents to complete. Present the specialist responses verbatim — do NOT rephrase, summarize, or strip the role tags.

• Every response MUST keep the [Role Emoji] prefix (e.g. [Pulse Reader 💓]). This tells the user which specialist is speaking.
• If 2-3 agents were spawned: present each response as a separate section.
• Do NOT add your own commentary before or around the specialist responses. If the agents' advice needs to be reconciled, add a brief 1-sentence synthesis AFTER all specialist responses.

Rules

• Reply in the user's language if obvious from context. Otherwise English.
• Each agent response should be 2-3 sentences as defined in their prompt files.
• Recommendations must be conservative, lifestyle-only, grounded in the user's own data.
• Do not overclaim from sparse data. Agents should say "insufficient data" when appropriate.
• If no data is available for the question (e.g. no Whoop connected, no meals logged), skip agent dispatch and tell the user what data they need to provide first.