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TrainRec

by app.trainrec
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Import a Strong or Hevy export

trainrec_import_file

Imports a CSV exported from Strong (workouts or measurements) or Hevy, as text exactly as the file has it; the server parses it. A large file can be sent in pieces split on whole workouts, each with the header line and the same batch id. Strong exports omit their unit. Workouts already imported are skipped. Only Strong and Hevy formats.

Tool call template

Replace each placeholder with a value matching the input schema. Only required parameters are included; add optional parameters as needed.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {
      "text": "<text>"
    },
    "name": "trainrec_import_file"
  }
}

Input Schema

NameRequiredDescriptionDefault
textYesThe CSV text, header line first.
unitNoUnit for every weight in this call. Defaults to the person's own unit.
batchNoReturned by the first call; pass it on later pieces of the same file.
formatNoDetected from the header when omitted.

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

A3.9/5.0
Behavior4/5

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

Annotations only declare the generic write profile (readOnlyHint false, destructiveHint false, openWorldHint false). The description adds real behavioral detail beyond that: parsing happens server-side, the caller must not pre-transform the CSV, duplicate workouts are skipped, and multi-piece uploads are joined via a batch id. It doesn't say what the call returns or how partial-batch failures behave.

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?

Five short clauses, front-loaded with what the tool accepts and followed by the operational constraints (chunking, header reuse, dedupe, format limit). No filler or restatement of the title.

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?

Covers formats, chunking protocol, dedupe behavior, and the unit gap in Strong exports — everything needed to call it correctly for a one-required-param import. Minor gap: with no output schema, nothing tells the agent what an import result or batch id looks like on return.

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 coverage is 100%, so baseline is 3, but the description adds meaning: 'text exactly as the file has it' clarifies that no normalization is expected, and 'Strong exports omit their unit' explains why the unit parameter exists and when to supply it. Batch semantics ('same batch id') are reinforced rather than restated.

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?

States a specific verb and resource ('Imports a CSV exported from Strong ... or Hevy') and names the two accepted source formats plus the data kinds (workouts or measurements). It is distinguishable from generic import siblings without opening the schema, though it does not explicitly name the alternatives it supersedes.

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?

Gives useful procedural guidance — send text exactly as-is, split large files on whole workouts with the header line and a shared batch id, and a hard exclusion ('Only Strong and Hevy formats'). However, it never says when to pick this over the sibling import tools such as trainrec_import_workouts or trainrec_import_measurements, leaving format-vs-tool routing implicit.

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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