BD brush-step
华米运动(Zepp/小米运动)自动刷步数技能，支持多账号管理。当用户提到刷步数、修改运动步数、华米运动、小米运动、手环步数时触发。
As a process D 49/100 · Unfinished process — 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 · 2
✓ No critical or high findings
Medium and low: 2
-
low Obfuscation
obf-base64-blobscripts/huami.py:163Long base64-looking blob (quoted — discussed, not commanded)data_json = '%5B%7B%22data_hr%22%3A%22%5C%2F%5C%2F%5C%2F%5C%2F%5C%2F%5C%2F9L%5C%2F%5C%2F%5C%2F%5C%2F%5C%2F%5C%2F%5C%2F%5C%2F%5C%2F%5C%2F%5C%2F%5C%2FVv%5C%2F%5C%2F%5C%2F%5C%2F%5C%2F%5C%2F%5C%2F%5C%2F%5
quoted -
low Obfuscation
obf-hex-escape-chainscripts/huami.py:163Escaped/char-code string obfuscation (quoted — discussed, not commanded)data_json = '%5B%7B%22data_hr%22%3A%22%5C%2F%5C%2F%5C%2F%5C%2F%5C%2F%5C%2F9L%5C%2F%5C%2F%5C%2F%5C%2F%5C%2F%5C%2F%5C%2F%5C%2F%5C%2F%5C%2F%5C%2F%5C%2FVv%5C%2F%5C%2F%5C%2F%5C%2F%5C%2F%5C%2F%5C%2F%5C%2F%5
quoted
Files scanned: 7. 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 "displayName"
Process rating: all ten parameters 49/100
- 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
- 40Consistency. Frontmatter name (brush-step) differs from the folder (xiaomi-brush-steps)
- 100Tools and files. No external tools needed
- 100Steps. 27 steps
- 100Execution cost. Instruction body is 603 tokens
- 100Running it twice. No mutating operations
- low 11 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)
- +3Description length 65: 120–800 characters recommended
- +3Output format is not stated: the model decides each time
- -33 of 4 scripts are never mentioned in SKILL.md
- +2Single-language instructions
- +4Structure: 15 headings
- +3Step-by-step instructions: 27 items
- +4Has examples (6 code blocks)
- +1License stated
Quality base 70; lint remarks subtract, signals add up to 100. Result: 66.
External checks
ClawHub: suspicious
This skill openly changes Zepp/Xiaomi fitness step records, but it asks for passwords, can automate recurring changes, and includes optional fake-IP behavior that users should review carefully.
LLM: suspicious (high) · VirusTotal: · 29 May 2026