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Report a workout

report_workout

A user's verdict on a workout from these tools: a mistake (wrong equipment, a weight, a dose that cannot fit), or a workout they found bad or good. Stores the user's words for Goblin Gains, nothing else about the user.

Input Schema

NameRequiredDescriptionDefault
noteYesWhat the user said about the workout, in their words. Example: "Farmers carry needs two dumbbells; I said I have one."
verdictYesOne of mistake, bad, good: "mistake" (something in it is wrong), "bad" (it works but is a poor workout), "good". Example: "mistake".
workoutNoThe workout's save link from suggest_workouts, vary_workout or generate_workouts, or its id; omitted for the tools as a whole. Example: "https://app.goblingains.com/w/<id>".

Output Schema

NameRequiredDescriptionDefault
resultYes

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

B3.4/5.0
Behavior3/5

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

Annotations already declare this is a non-read-only, non-destructive, non-idempotent, closed-world write. The description adds a useful privacy scope note ('nothing else about the user'), which is real value beyond the annotations. However, it does not disclose what happens on repeated calls (relevant given idempotentHint=false) or whether a report is attached to a specific workout versus the toolset as a whole.

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?

Two sentences with no filler, and the core purpose plus the storage/privacy scope are front-loaded. The first sentence's phrasing ('from these tools: a mistake...') is slightly convoluted but still compact and informative.

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

Completeness3/5

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

With an output schema present and full parameter documentation, the description needn't explain return values. It covers purpose and privacy scope, but leaves gaps on repeat-call behavior and the workout-vs-toolset scoping that the non-idempotent annotation makes relevant.

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?

Schema description coverage is 100%, so the schema already documents note, verdict, and workout with examples. The description adds no parameter-level detail beyond what the schema provides, so the baseline of 3 applies.

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

Purpose4/5

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

The description states the resource (a user's verdict on a workout) and enumerates the verdict kinds (mistake, bad, good), and the second sentence clarifies that it stores the user's words. It is clear what is being recorded, though the verb 'report/store' is only implied rather than stated up front, and it does not explicitly contrast itself with siblings like suggest_workouts or vary_workout.

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 parenthetical examples ('wrong equipment, a weight, a dose that cannot fit') and the bad/good framing imply when to call it, but there is no explicit when-to-use/when-not statement or named alternative. An agent must infer that this is the tool for capturing user feedback rather than generating workouts.

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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