BC fitconverter
运动健康转换工具。华为、Zepp、小米、vivo、三星、Keep、悦跑圈、RQrun、动动、行者运动记录导出后，可通过运动健康转换工具转换成fit、tcx、gpx、kml格式文件同步导入高驰、佳明、RQrun、Strava等主流运动平。 运动记录转换工具、运动记忆、运动数据转换、fitconverter、华为运动数据、小米运动数据、Zepp跑步记录、Keep数据导出、转换fit、转换tcx
As a process C 53/100 · Has gaps — weak spots: result and completion, when it triggers, inputs and preconditions
How to improve
- Say in the description WHEN to use the skill ("use when…", example requests): that is the agent's main cue.
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: 3. Evidence is masked. Grey chips explain why severity was lowered.
Against the Agent Skills spec
- warning
description-no-whendescription does not say WHEN to use the skill (no "use when") - note
frontmatter-keyunknown frontmatter key "homepage"
Process rating: all ten parameters 53/100
- 0Result and completion. Does not say what the result is
- 0Inputs and preconditions. Does not say what the process needs to start
- 0Failures and branches. Linear process with no failure handling
- 0Progress reporting. Says nothing while it works
- 20When it triggers. No condition that starts the skill
- 100Tools and files. No external tools needed
- 100Steps. 7 steps
- 100Consistency. Name and required fields are in place
- 100Execution cost. Instruction body is 1165 tokens
- 100Running it twice. No mutating operations
- low 12 top-level sections: this looks like several domains in one skill
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)
- +3Output format is not stated: the model decides each time
- +1No license
- +2Single-language instructions
- +3Description length 196: enough signal without eating the budget
- +4Structure: 22 headings
- +3Step-by-step instructions: 7 items
- +4Has examples (10 code blocks)
Quality base 70; lint remarks subtract, signals add up to 100. Result: 71.
External checks
ClawHub: suspicious
This fitness data converter is mostly coherent, but it asks users to share API keys, emails, workout archives, payment QR flows, and sometimes platform passwords without enough privacy or security guardrails.
LLM: suspicious (high) · VirusTotal: · 29 May 2026