Skip to main content
Glama
turnnoblindeye

Wellness Project MCP

get_workout

Read-onlyIdempotent

Retrieve full workout session details—exercises, sets, reps, weights, supersets, notes, and NSI scores—for reviewing past training or comparing strength standards.

Instructions

Retrieve full detail of a workout session: exercises, sets, reps, weights, superset groupings, heart points, notes, and NSI scoring at every grain. Use for detailed questions about a past workout, reviewing training before recommendations, confirming what was logged, or comparing a session to population strength standards.

NSI: session NSI/rating in the header; per-exercise NSI (max set NSI), rating, est. 1RM, and the population_1rm_lb/population_reps benchmark it was measured against; per-set NSI and est. 1RM to see which set drove the exercise score.

EQUIPMENT: shown per exercise when every set shares a tag, else per set; missing means untagged. A wrong or missing tag on a dumbbell exercise silently halves or doubles its NSI score — fix it via update_workout's set_updates or add_exercises equipment field.

REQUIRED WORKFLOW: call list_workouts first to find the session ID — never guess it.

SAVED WORKOUTS: pass saved_workout_id to read a reusable Saved Workout prescription. Do not combine it with session_id/session_date.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
session_idYesSession ID from list_workouts. Required.
saved_workout_idNoSaved Workout ID from list_workouts(saved_workouts=true). When present, returns the reusable prescription instead of a completed workout session.

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYesHuman-readable result text returned by the tool.

Schema Changelog

Changes observed during successful MCP inspections. Dates show when Glama detected each change.

  1. First observedv1.2.1

TDQS

A4.9/5.0
Behavior5/5

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

Annotations already signal read-only and idempotent behavior, and the description goes far beyond them by disclosing a non-obvious accuracy quirk: a wrong or missing equipment tag on a dumbbell exercise 'silently halves or doubles its NSI score.' It also explains when equipment is shown per exercise vs per set and what 'missing' means, which is highly useful behavioral detail not present in annotations.

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

Conciseness5/5

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

The description is long but densely informative, with clear section headers (NSI, EQUIPMENT, REQUIRED WORKFLOW, SAVED WORKOUTS) that make scanning easy. Every sentence adds operational knowledge; there is no filler or repetition of schema definitions.

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?

Despite having an output schema, the tool has complex behavior (nested NSI scoring at session/exercise/set grains, equipment-tag sensitivity, two distinct input modes). The description covers all of these, plus the required lookup workflow and a correctness caveat. Together with the annotations and schema, an agent has everything needed to invoke the tool correctly and interpret its unusual scoring behavior.

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

Parameters4/5

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

Schema description coverage is 100%, so the baseline is 3. The description adds value beyond the schema: it explains that session_id comes from list_workouts and is required, clarifies saved_workout_id returns a 'reusable prescription instead of a completed workout session,' and warns against combining saved_workout_id with session_id/session_date. These semantic clarifications exceed the schema's basic field descriptions.

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 opens with a specific verb and resource: 'Retrieve full detail of a workout session' and enumerates the exact contents (exercises, sets, reps, weights, superset groupings, heart points, notes, NSI scoring). It clearly differentiates from siblings like list_workouts (list vs full detail) and show_workout (which may focus on summary/display), and also explains the separate saved_workout_id mode.

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?

Explicitly states when to use: 'Use for detailed questions about a past workout, reviewing training before recommendations, confirming what was logged, or comparing a session to population strength standards.' It also mandates the preceding workflow step ('call list_workouts first to find the session ID — never guess it') and gives a clear exclusion/alternative for saved workouts ('Do not combine it with session_id/session_date').

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

Latest Blog Posts

MCP directory API

We provide all the information about MCP servers via our MCP API.

curl -X GET 'https://glama.ai/api/mcp/v1/servers/turnnoblindeye/wellness-project-mcp'

If you have feedback or need assistance with the MCP directory API, please join our Discord server