BD tutu-smart-control
图图智控（TUTU Smart Control）— 远程控制 Android 手机，执行 GUI 自动化、系统管理和日常任务。当用户提到以下任何内容时使用此 skill： - 控制手机、操作手机、手机上做某事 - 打开手机上的 App（微信、抖音、支付宝、淘宝等） - 手机截图、查看手机屏幕 - 在手机上点击、输入、滑动 - 手机自动化、GUI 自动化 - 查看手机状态（电量、网络、内存等） - 发短信、打电话、读短信、通讯相关 - 手机定位、获取位置 - 查看手机通知 - 手机震动、语音播报（TTS） - 手机文件管理（列目录、读写删文件、存储分析，仅限 /sdcard/ 用户存储） - 按文字/ID 点击 UI 元素、查找界面元素 - 搜索手机媒体文件（图片、视频、音乐） - 微信自动回复、社交应用自动化 - 手机定时任务、批量操作 - 手机健康检查、系统巡检
As a process D 42/100 · 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.
- The SKILL.md body is over 5,000 tokens: move reference detail into references/ and load it when needed.
- 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: 4. 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") - warning
body-longSKILL.md body ≈ 6362 tokens (recommended < 5000); move details to references/ - note
frontmatter-keyunknown frontmatter key "triggers"
Process rating: all ten parameters 42/100
- 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
- 30Running it twice. 2 mutating operations with no state check
- 60Tools and files. Uses tools (bash) that frontmatter does not declare
- 70Execution cost. Instruction body is 6362 tokens
- 100Steps. 64 steps
- 100Consistency. Name and required fields are in place
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 387: enough signal without eating the budget
- +4Structure: 127 headings
- +3Step-by-step instructions: 64 items
- +4Has examples (89 code blocks)
Quality base 70; lint remarks subtract, signals add up to 100. Result: 61.