BD smyx-rehab-motivation-encouragement-analysis
Through fixed cameras in rehabilitation centers or home rehab areas, the system analyzes video of patients during rehabilitation training to detect frustration / giving-up tendency behaviors: sighing (rapid chest-abdomen rise-fall with exhalation), training interruption (actively stopping before reaching preset reps or duration), head-down silence (head lowered, avoiding eye contact, long-term silence), sluggish or. | 通过康复中心或家庭康复区的固定摄像头，分析患者在进行康复训练时的视频，检测沮丧/放弃倾向行为：叹气（胸腹快速起伏伴呼气声）、中断训练（在未达到预设次数或时间前主动停止动作）、低头不语（头部低垂，避免眼神接触，长时间无言语）、动作迟缓或敷衍（关节活动范围明显小于前期），以及长时间无进展（连续多日同一训练项目的表现停滞或下降）。
Through fixed cameras in rehabilitation centers or home rehab areas, the system analyzes video of patients during rehabilitation training to detect…
As a process D 35/100 · Unfinished process — weak spots: steps, result and completion, when it triggers
How to improve
- Say in the description WHEN to use the skill ("use when…", example requests): that is the agent's main cue.
- 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
- warning
description-no-whendescription does not say WHEN to use the skill (no "use when")
Process rating: all ten parameters 35/100
- 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
- 60Tools and files. Uses tools (python) that frontmatter does not declare
- 100Consistency. Name and required fields are in place
- 100Execution cost. Instruction body is 2166 tokens
- 100Running it twice. No mutating operations
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)
- +3No numbered steps or checklist
- +3Output format is not stated: the model decides each time
- -266 emoji in the instructions: noise for the model
- -32 of 4 scripts are never mentioned in SKILL.md
- +2Single-language instructions
- +3Description length 585: enough signal without eating the budget
- +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: 69.