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turnnoblindeye

Wellness Project MCP

list_workouts

Read-onlyIdempotent

Review workout sessions in a date range with ID, date, focus, location, and NSI rating. Use it to locate a session ID or answer training frequency and NSI trend questions.

Instructions

List workout sessions in a date range: ID, date, focus type, location, and session-level NSI with rating. Use before get_workout to find a session ID, or to answer "how many times did I train this week?", "when was my last leg day?", "did I work out yesterday?", "how is my NSI trending?".

Each row's NSI is the mean of per-exercise NSIs (after dropping anything below 50% of the user's median for that exercise), with a rating band (Below Average, Novice, Average, Intermediate, Advanced, Elite). 100 = the population intermediate standard for the user's bodyweight, age, and sex. Use the rolling average across rows for trend questions.

Maximum range: 90 days per call. For longer periods (PR lookups, "have I ever done X", "when was the last time I did Y"), make multiple sequential calls walking backwards (days 0-89, then 90-179, then 180-269...) until you find what you need. Don't give up after one call.

INFER — default start_date to 7 days ago, end_date to today. Widen up to 90 days for trend questions. Chain calls for anything older.

SAVED WORKOUTS: set saved_workouts=true to list the user's reusable Saved Workouts library instead of completed workout history. Saved workout IDs are separate from workout session IDs.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
end_dateNoEnd of date range. Format: YYYY-MM-DD. Optional — defaults to today.
start_dateNoStart of date range. Format: YYYY-MM-DD. Optional — defaults to 7 days ago.
saved_workoutsNoWhen true, list reusable Saved Workouts instead of completed workout sessions. Defaults to false.

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?

Beyond the readOnlyHint and idempotentHint annotations, the description reveals important runtime behaviors: default date range, 90-day maximum range, the need to chain calls for older periods, and the effect of the saved_workouts flag. This adds meaningful context that annotations alone do not provide.

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 slightly long but well-organized with labeled sections (SAVED WORKOUTS, INFER) and each sentence adds value. It front-loads the core function and usage examples before diving into edge cases, though a bit of trimming could improve conciseness.

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?

Given the three optional parameters and the tool's role in a broad ecosystem, the description covers all necessary aspects: default dates, range limitations, chaining strategy, saved workout mode, and the output fields. Users have enough context to call it correctly without referencing external docs.

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

Parameters5/5

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

Schema descriptions cover all three parameters, but the tool description enriches them further by specifying defaults (start_date = 7 days ago, end_date = today), the meaning of saved_workouts, and instructions to widen the range up to 90 days. This goes well beyond the schema's basic 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 clearly states the tool's function: listing workout sessions with specific attributes (ID, date, focus, location, NSI rating). It also gives concrete usage examples and distinguishes between completed workouts and saved workouts, making its purpose unambiguous.

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?

It provides explicit guidance on when to use it: before get_workout to find a session ID, for answering trend questions, and how to handle older data via chaining. It also clarifies the saved_workouts flag to switch modes, which helps select the right tool among siblings.

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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