garmin-trainer

garmin-trainer is a skill for Claude Code, Codex from bpauli/gccli. It costs 85 tokens per session (4,088 once invoked), scanned A, original, MIT.

A training-plan skill that uses Garmin Connect data to create and schedule a structured 12-week plan. Garmin Connect is Garmin’s platform for recording workouts, fitness data, recovery, and events.

In plain words
What is it for?
Use it for race preparation, workout planning, training-calendar updates, and plans that account for recent training load, fitness, recovery, and multiple sports.
Why use it?
It bases the plan on current training information and upcoming events instead of relying only on a generic schedule.

Skill for Claude CodeCodex

Written for no agent in particular: nothing here depends on one.

Good fit Use it for race preparation, workout planning, training-calendar updates, and plans that account for recent training load, fitness, recovery, and multiple sports.

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Install with agentmods
npx agentmods add skills/bpauli/gccli/garmin-trainer
View source ↗ bpauli/gccli
Install

Getting it into your agent

One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.

Any agent
npx skills add bpauli/gccli --skill garmin-trainer
Clone the repo
git clone --depth 1 https://github.com/bpauli/gccli

Made for: Claude Code, Codex.

Wrote this? Show the measurements

A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.

agentmods badge for garmin-trainer

README.md
[![agentmods](https://agentmods.dev/badge/skills/bpauli/gccli/garmin-trainer/github.svg)](https://agentmods.dev/skills/bpauli/gccli/garmin-trainer)
Your own site
<a href="https://agentmods.dev/skills/bpauli/gccli/garmin-trainer"><img src="https://agentmods.dev/badge/skills/bpauli/gccli/garmin-trainer/github.svg" alt="Measured on agentmods" height="20"></a>

Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.

agentmods 80×15 button for garmin-trainer

Your own site · 80×15
<a href="https://agentmods.dev/skills/bpauli/gccli/garmin-trainer"><img src="https://agentmods.dev/badge/skills/bpauli/gccli/garmin-trainer.svg" alt="Reviewed on agentmods" width="80" height="20"></a>
Per session 85 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 4,088 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. A grade says what 26 rules found in the file — not that it is safe. Third-party audits
  • NVIDIA SkillSpector warn 7 Sept 2026
SkillSpector: 1 finding, up to medium

These are SkillSpector’s own severities. On a checked sample its high-severity flags on skills were ~96% false positives — a documented command, a public API, a “never do X” rule — so we show them as a caution to read, not a verdict. Why →

  • medium Excessive Agency · line 222
    Skill enables autonomous high-impact decisions without human-in-the-loop verification. Critical operations (destructive commands, financial transactions, data deletion) should require explicit user confirmation.
    Fix: Add human-in-the-loop confirmation for destructive, irreversible, or high-impact operations. Never auto-execute commands that modify files, send data, or alter system state.
How audits are shown
Origin original No closer match found in the catalogue.
Token cost

What it costs to keep this loaded

Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.

ModelPer sessionOnce invoked
Fable 5.1 $0.00085 $0.04088
Opus 5 $0.00043 $0.02044
Sonnet 5 $0.00017 $0.00818
Haiku 4.5 $0.00009 $0.00409

Measured 9d ago against content hash c959623ab303, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-09, from the pricing page.

Security

Grade A, and why

garmin-trainer scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 9d ago.

A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.

Nothing flagged

None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.

skills/garmin-trainer/SKILL.md · 234 lines

How it starts

The opening of the file, as written. The whole thing — 234 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Garmin Trainer

Generate an adaptive 12-week training plan based on real Garmin Connect data. The plan accounts for all upcoming events (races across different sports), current fitness level, recent training load, and recovery status. Each run of this skill pulls fresh data so the plan stays current.

For all gccli command examples (data gathering, workout creation, scheduling), read references/gccli-commands.md.

Step 0: Choose a Training Philosophy

Before building the plan, ask the user which coaching philosophy to follow. Present these six options — each shapes how the plan balances intensity, volume, strength work, and recovery:

1. Joe Friel — Periodization Bible

Based on "The Triathlete's Training Bible". Classic structured periodization with distinct phases (base → build → peak → race). Strength training is integral, progressing from anatomical adaptation (high rep, low weight) through max strength to explosive power as the season advances. Includes year-round mobility work. Best for athletes who like structure and measurable progression.

  • Intensity split: ~75% easy / 5% tempo / 20% high intensity (shifts across phases)
  • Strength: 2-3x/week in base phase (full-body compound lifts), tapering to 1x/week maintenance closer to events
  • Mobility: dynamic stretching before sessions, 10-15min flexibility routine post-workout

2. Matt Fitzgerald — 80/20 Polarized

From "80/20 Triathlon". Strictly 80% of training time at low intensity (zones 1-2), 20% at moderate-to-high intensity (zones 3-5). No junk miles in between. Research-backed approach that builds a massive aerobic engine while keeping the hard sessions truly hard. Supplemental strength focused on injury prevention rather than performance.

  • Intensity split: 80% easy (strictly enforced) / 20% moderate-to-hard
  • Strength: 2x/week functional strength and injury prevention (single-leg work, hip stability, core)
  • Mobility: foam rolling and dynamic mobility as part of warmup/cooldown routines

Read the full file on GitHub · 234 lines

Files

What ships with it

1 file beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.

Changes

What this file has done since we first saw it

Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.

  1. 9d ago First seen · 234 lines · 85 tokens per session scan A c959623ab303

Subscribe to this mod's changes

garmin-trainer is a skill published in the GitHub repository bpauli/gccli (27 stars, last pushed 9d ago), licensed MIT. It adds 85 tokens to every session and 4,088 once invoked, about $0.0004 per session on Opus 5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-30.