AF smyx-child-focus-analysis-analysis
Using the camera built into a smart desk lamp or a tabletop camera, the system analyzes video of the child's study area in real time, detecting behavioral indicators such as face orientation (whether it deviates from the book/screen), eye gaze direction, and fidgeting hand actions (playing with a pen, touching the face, fiddling with objects), and computes a per-minute focus score (0-100) while recording distraction periods. The skill helps parents and teachers understand the child's learning state and optimize study habits. Application scenarios: smart study lamps, home study rooms, classrooms. The system monitors in real time, generates focus reports, and pushes alerts when focus stays persistently low. Skill features: improve learning efficiency. | 通过智能台灯内置摄像头或桌面摄像头，实时分析儿童学习区域的视频，检测面部朝向（是否偏离书本/屏幕）、眼部注视方向、手部小动作（玩笔、摸脸、摆弄物品）等行为指标，计算每分钟专注得分（0-100分），并记录走神时段。该技能可帮助家长和教师了解儿童学习状态，优化学习习惯。应用场景：智能学习台灯、家庭书房、教室。系统实时监测，生成专注度报告，当专注度持续偏低时推送提醒。技能特点：提升学习效率。
As a process F 32/100 · Will not run — weak spots: steps, result and completion, when it triggers
How to improve
- 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: 30. Evidence is masked. Grey chips explain why severity was lowered.
Against the Agent Skills spec
✓ No remarks against the Agent Skills spec
Process rating: all ten parameters 32/100
- 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
- 25Steps. 1 steps
- 30Running it twice. 1 mutating operations with no state check
- 60Tools and files. Uses tools (python) that frontmatter does not declare
- 100Consistency. Name and required fields are in place
- 100Execution cost. Instruction body is 1444 tokens
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 956: 120–800 characters recommended
- +3No numbered steps or checklist
- +3Output format is not stated: the model decides each time
- -255 emoji in the instructions: noise for the model
- -32 of 4 scripts are never mentioned in SKILL.md
- +2Single-language instructions
- +4Structure: 19 headings
- +4Has examples (3 code blocks)
- +4Reference files are cited in the instructions (1 of 1)
- +1License stated
Quality base 70; lint remarks subtract, signals add up to 100. Result: 78.