Skip to main content
Glama

log_subjective

Record how a day or training session felt with 1-10 ratings for perceived effort (RPE), soreness, or mood. Capture the subjective experience that Garmin metrics miss, adding personal context to your training data.

Instructions

Records how a day or session actually felt, rated 1-10: perceived effort (rpe), soreness, or mood. Garmin has no equivalent.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
dateNoISO date the rating is for
kindYesWhich rating this is
noteNoOptional free-text detail
valueYesA rating from 1 to 10

Schema Changelog

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

  1. First observedv0.5.2

TDQS

A4.2/5.0
Behavior3/5

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

With no annotations provided, the description carries the full behavioral burden. It communicates the core behavior—recording a rated subjective feeling—and clarifies the scale and categories, but it does not disclose whether entries overwrite or append, whether authorization is needed, or what response is returned. For a simple logging tool, this is adequate but not richly transparent.

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 two sentences with no filler. It front-loads the action and scope, lists the distinct rating types, and the 'Garmin has no equivalent' note is a useful differentiator rather than unnecessary detail.

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?

The tool is simple: four parameters, two required, an enum, and no output schema. The description covers what is being logged, which values are valid, and why this tool exists separately from Garmin-derived siblings. It stops short of describing expected return/confirmation behavior or date defaulting, but these are minor for a basic logging call.

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, but the description adds value by mapping 'rpe' to perceived effort, explaining that values range 1-10, and tying the rating to a day or session. This gives the enumerated 'kind' and numeric 'value' parameters practical meaning beyond the schema.

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 uses a specific verb ('Records') and resource ('how a day or session actually felt'), and enumerates the exact rating kinds and scale. This clearly distinguishes it from the sibling get_* tools, which all retrieve Garmin data.

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

Usage Guidelines4/5

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

The description provides clear context: this is for subjective self-reported ratings, not objective Garmin measurements, and explicitly notes Garmin has no equivalent. It does not spell out 'when not to use' or name alternative logging tools, but among the provided siblings there is no direct alternative, so the context is sufficient.

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/Zsadigzade/trainbud'

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