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Log a workout session

log_workout_session

Record detailed workout sessions—activity, timing, intensity, and heart rate—so analytics can explain exactly what you did, not just total minutes.

Instructions

Record one workout as a structured event — activity, timing, intensity, and heart-rate response — rather than folding it into the day's workout_minutes total. Use this alongside (not instead of) log_daily_metric/log_measurement for workout_minutes: this is what lets explain_metric_change say what the workout was, not just how long it ran. A day can have more than one session; each call adds a new row.

Use this tool when:

the user describes an actual workout/exercise session (e.g. "I went running for 40 minutes", "log today's strength workout").

Do not use this tool when:

the user only wants to record the day's total exercise minutes as a single number, with no activity type/timing/intensity -> use log_daily_metric (workout_minutes) or log_measurement instead.

Privacy note: this server and its SQLite file are entirely local, but the data returned by this tool becomes part of the conversation sent to whatever model the calling client is configured with. If that model runs in the cloud rather than on your machine, treat this the same as pasting the data into a chat with that provider.

Input Schema

TableJSON Schema

Name	Required	Description
`date`	Yes	The day the workout happened, YYYY-MM-DD.
`notes`	No	Free-text notes, e.g. route or how it felt. Optional.
`source`	No	Where this came from, e.g. "Apple Watch", "manual". Optional.
`intensity`	No	One of "low", "moderate", "high". Optional.
`start_time`	No	When it started, HH:MM (24-hour) or a full ISO timestamp. Optional.
`activity_type`	Yes	What kind of workout, e.g. "running", "cycling", "strength". Free-form.
`avg_heart_rate`	No	Average heart rate during the workout, bpm. Optional.
`max_heart_rate`	No	Peak heart rate during the workout, bpm. Optional.
`duration_minutes`	Yes	How long it lasted, in minutes.

Output Schema

TableJSON Schema

Name	Required	Description	Default
`session`	Yes

Schema Changelog

Changes observed during successful MCP inspections.

Addedv1.0.16Sep 15, 2026
Removedv1.0.15Sep 15, 2026
Addedv0.3.0Sep 13, 2026

TDQS

A4.6/5.0

Behavior5/5

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

Annotations already indicate readOnlyHint=false, idempotentHint=false, etc., but the description adds important behavior: 'each call adds a new row' clarifies non-idempotence specifics, and the privacy note about data becoming part of the conversation sent to the model is unique contextual disclosure. No contradictions with annotations.

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?

The description is front-loaded with a strong first sentence, followed by structured usage guidance and a privacy note. It is longer than the minimal two-sentence example, but every section contributes value given the tool's complexity and need to disambiguate from siblings. The explicitly labeled sections compensate for length.

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

Completeness5/5

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

The description is complete enough for a 9-parameter tool with 100% schema coverage and an output schema. It covers when to use, when not, privacy implications, and multi-session behavior. No significant context is missing for an agent to invoke the tool correctly.

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?

Input schema coverage is 100%, so the schema fully documents each of the 9 parameters. The description adds a high-level grouping ('activity, timing, intensity, heart-rate response') but does not provide parameter-level semantics beyond the schema. Baseline of 3 applies since schema does the heavy lifting.

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?

The description states a specific action and resource: 'Record one workout as a structured event — activity, timing, intensity, and heart-rate response.' It explicitly contrasts with log_daily_metric/log_measurement for workout_minutes and explains the relationship to explain_metric_change, distinguishing it from siblings without the need to open schemas.

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

Usage Guidelines5/5

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

Provides explicit 'Use this tool when' and 'Do not use this tool when' sections with concrete examples ('I went running for 40 minutes') and names the exact alternatives (log_daily_metric / log_measurement) for the excluded cases. This goes beyond mere context to actionable selection criteria.

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

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