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formtrace-mcp

formtrace-mcp

by arciomdavydau
OverviewSchemaSourceRelated ServersDiscussionsAdmin
Python
Local

Get Hevy Workout Count

get_hevy_workout_count
Read-only

Retrieve the total number of workouts recorded in a Hevy account to track training volume and verify workout history.

Instructions

Get the total number of recorded workouts in the Hevy account.

Tool call template

This tool declares no required parameters. Add optional parameters from the input schema as needed.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {},
    "name": "get_hevy_workout_count"
  }
}

Input Schema

NameRequiredDescriptionDefault

No arguments

Output Schema

NameRequiredDescriptionDefault
dataYes
sourceYes

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.1.0

TDQS

B3.3/5.0
Behavior2/5

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

Annotations already declare readOnlyHint=true, destructiveHint=false and openWorldHint=true, so the safety profile is covered. The description adds no behavior beyond that: it doesn't say what the count covers (all-time vs. filtered), whether deleted or in-progress workouts are included, or anything about auth or freshness.

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?

A single front-loaded sentence with no filler. Nothing is wasted and the core meaning lands immediately.

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?

For a zero-parameter aggregate with annotations and an output schema, the description is nearly sufficient; return values needn't be explained. The only real omission is the scope of the count (all-time vs. something narrower), which an agent would otherwise have to guess.

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?

The tool takes zero parameters, so the baseline is 4 and there is no parameter meaning for the description to supply. The schema is closed and fully described.

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 a specific verb and resource: 'Get the total number of recorded workouts in the Hevy account.' That makes it clearly a count/aggregate, not a listing, which implicitly separates it from siblings like list_hevy_workouts. It does not, however, name any sibling explicitly.

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

Usage Guidelines2/5

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

There is no when-to-use or when-not guidance and no mention of alternatives. An agent must infer from the noun 'count' that this is the aggregate option versus list_hevy_workouts or get_hevy_workout, and nothing in the text confirms that inference.

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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