SKILLEMALL.ai

BB garmin-analysis-skill

Bilingual Chinese-English cycling-health workflows using the public cycling-health CLI. Use when an assistant needs to sync Garmin China Wellness data to Intervals.icu; analyze Garmin sleep, recovery, training ability, activities, events, courses, workouts, plans, trends, or FIT/GPX data; query and compare Intervals.icu Wellness, activities, power, fitness, statistics, settings, sport settings, or calendar events; analyze personal iGPSPORT rides and FIT streams; query personal Strava athlete, zones, cycling activities, laps, streams, routes, gear, or rate limits; query or download Xingzhe route books; sync Garmin China activities to Garmin Global; or report cycling-health issues. The only supported personal activity-sync topology is Garmin CN -> Garmin Global -> the user's native Intervals.icu connection; never substitute direct FIT upload, Strava, iGPSPORT, or Xingzhe. Garmin CN Wellness -> Intervals.icu is separate; iGPSPORT and Strava are read-only analysis sources, and Xingzhe is route/GPX only. Also use for Chinese requests about 骑行健康、睡眠恢复、佳明国服与国际服同步、Intervals.icu、iGPSPORT、Strava、行者路书、FIT/GPX 分析或 cycling-health 故障。

ClawHub Agent Skills author: baijian v0.2.3 MIT-0 8 files body ≈ 6 934 tokens Open the sourceclawhub.ai analyzed 11 h ago

Bilingual Chinese-English cycling-health workflows using the public cycling-health CLI.

As a process B 67/100 · Nearly there — weak spots: result and completion, progress reporting

ProcedureData and analyticsCustomer supportPersonal productivitytype and topics are labelled automatically from the skill text
JSON
Technical rating
B
79/100
safety, quality, tests
Safety 60%
100
Quality 40%
48
Run on models
none yet
Process rating
B
67/100
Nearly there
Result and completion w 14
0
Progress reporting w 2
0
When it triggers w 12
50
the three weakest of ten parameters · all ten

How to improve

  1. Shorten the description to 1024 characters.
  2. The SKILL.md body is over 5,000 tokens: move reference detail into references/ and load it when needed.
For the model run — optional
  • Your own cases (evals/evals.json, 4–6 real requests with expected answers): the full check would then run those instead of a model-drafted suite.
  • A spec.yaml with trigger phrases and assertions — a behaviour contract for CI; `skilltest init` writes a template.

Guard findings · 0

✓ No critical or high findings

Files scanned: 8. Evidence is masked. Grey chips explain why severity was lowered.

Against the Agent Skills spec

  • error description-long description is 1137 chars, limit 1024
  • warning body-long SKILL.md body ≈ 6934 tokens (recommended < 5000); move details to references/
  • note frontmatter-key unknown frontmatter key "slug"
  • note frontmatter-key unknown frontmatter key "displayName"
  • note frontmatter-key unknown frontmatter key "summary"

Process rating: all ten parameters 67/100

  • 0Result and completion. Does not say what the result is
  • 0Progress reporting. Says nothing while it works
  • 50When it triggers. No condition that starts the skill
  • 60Tools and files. Uses tools (bash, web) that frontmatter does not declare
  • 70Execution cost. Instruction body is 6934 tokens
  • 85Steps. 107 steps, 3 vague phrases
  • 100Inputs and preconditions. Inputs and preconditions are listed
  • 100Failures and branches. 1 branches, has a failure section
  • 100Consistency. Name and required fields are in place
  • 100Running it twice. Mutating operations check current state
  • medium Safety rules and hard prohibitions inside a skill: they belong in the system prompt, here they protect nothing

Everything here is measured from the skill text rather than judged by a model, so the numbers are checkable. A parameter weighs more when it is a more common reason for the process to stall.

Quality signals

  • +5Description has no quoted example phrases that should trigger the skill
  • +4Description does not say when NOT to use the skill (false activations)
  • +3Description length 1137: 120–800 characters recommended
  • +3Output format is not stated: the model decides each time
  • +2Single-language instructions
  • +4Structure: 28 headings
  • +3Step-by-step instructions: 107 items
  • +4Has examples (9 code blocks)
  • +4Reference files are cited in the instructions (5 of 5)
  • +1License stated

Quality base 70; lint remarks subtract, signals add up to 100. Result: 48.

External checks

ClawHub: clean
This skill is a disclosed workflow guide for a cycling-health CLI, with sensitive account access and sync actions gated by previews, local credential handling, and explicit user authorization.
LLM: benign (high) · VirusTotal: · 28 Jul 2026