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Symptoms

get_symptoms

Read-onlyIdempotent

Retrieve decrypted HealthKit symptom data locally, grouped by owner, with severity and coverage to understand data history extent.

Instructions

Decrypt recent HealthKit symptom days locally, grouped by data owner.

SENSITIVE: symptom data (cramps, headache, fatigue, coughing…) only reaches this server when a user explicitly opted in on iOS — their own AI toggle for their own data, or the partner-AI toggle for a partner's data. Both partners can track symptoms, so each entry in owners carries owner_user_id plus per-type counts and day-by-day samples with severity (mild/moderate/severe/present/…). Stays on-device, never re-exported.

Carries a coverage block: quote coverage.days_covered (distinct days, not the row count) and coverage.span_days beside any average or trend, and read coverage.window_satisfied: false as a shorter history than asked, not as a missing kind. 🔴 Before saying how far back someone's data goes, read coverage.more_available: true means this server can decrypt days OLDER than first_day that your limit left behind — re-read with a larger limit, or quote coverage.oldest_available as the real start of their history. Never report a limit-shaped window as the extent of their data.

Input Schema

TableJSON Schema

Name	Required	Description	Default
`fresh`	No
`limit`	No

Output Schema

TableJSON Schema

Name	Required	Description	Default
No arguments

Schema Changelog

Changes observed during successful MCP inspections.

First observedv0.8.1Sep 23, 2026

TDQS

A4.1/5.0

Behavior5/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

Annotations already mark the tool read-only, idempotent, and non-destructive, and the description adds substantial beyond-that context: local decryption, on-device-only handling with no re-export, per-owner grouping, severity values, and detailed coverage semantics for days_covered, span_days, window_satisfied, more_available, and oldest_available. It also warns against reporting a limit-shaped window as the full history.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness4/5

Is the description appropriately sized, front-loaded, and free of redundancy?

Front-loaded with a clear one-sentence purpose, then organized into SENSITIVE and coverage blocks. It is long, but nearly every sentence carries necessary caveats for sensitive health data; minor redundancy like 'Decrypt... locally' versus 'Stays on-device' keeps it from a perfect score.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness4/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given the rich output schema and read-only annotations, the description thoroughly covers return structure, owner grouping, privacy constraints, and coverage edge cases. The main gap is the undocumented 'fresh' parameter, which an agent cannot resolve from either the schema or the description.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters3/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

With 0% schema description coverage, the description must compensate for both parameters. It meaningfully explains limit's role in truncation and re-reading older data, but it never defines limit's units or scope, and 'fresh' is not mentioned at all. This is partial compensation for one of two parameters.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose5/5

Does the description clearly state what the tool does and how it differs from similar tools?

Opens with a specific verb and resource: 'Decrypt recent HealthKit symptom days locally, grouped by data owner.' This clearly states what the tool does and distinguishes it from sibling health getters by naming HealthKit symptoms and the owner-grouped output shape.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines3/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description does not explicitly say 'use this when...' or name alternatives/exclusions, so routing is mostly implied by the tool name and symptom subject. It does provide useful context about opt-in availability and coverage caveats, but an agent comparing it to sibling tools like get_menstrual_cycle or get_wrist_temp gets no direct guidance.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.