SKILLEMALL.ai

BF smyx-elderly-medication-compliance-analysis

Using a fixed camera installed above or beside the home medication area, the system monitors the elderly person's full medication process in real time. With pose estimation and object detection, it recognizes three key steps: (1) picking up — hand takes a tablet/capsule out of the pill box; (2) to-mouth — hand brings the medication to the lips; (3) swallowing — throat/jaw movement indicating a swallow. | 通过家庭药箱区域上方或侧方的固定摄像头,实时监测老年人取药、服药的全过程,利用姿态估计和目标检测技术识别以下三个关键步骤:①取药(手从药盒中取出药片/胶囊)、②送入口中(手部将药物送至嘴边)、③吞咽(喉部运动或颈部吞咽动作)。当系统检测到缺步骤(例如取药后未送入口中,或送入口中后无吞咽)时,记录为'未完成服药',并向家属或护理人员推送提醒。

ClawHub Agent Skills author: smyx-skills v1.0.10 MIT-0 30 files body ≈ 1 659 tokens Open the sourceclawhub.ai analyzed 4 d ago

As a process F 32/100 · Will not run — weak spots: steps, result and completion, when it triggers

AnalyzerInfrastructureSecuritytype and topics are labelled automatically from the skill text
JSON
Technical rating
B
88/100
safety, quality, tests
Safety 60%
100
Quality 40%
69
Run on models
none yet
Process rating
F
32/100
Will not run
Result and completion w 14
0
Inputs and preconditions w 11
0
Failures and branches w 10
0
the three weakest of ten parameters · all ten

How to improve

  1. 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: 30. Evidence is masked. Grey chips explain why severity was lowered.

Against the Agent Skills spec

  • warning description-no-when description does not say WHEN to use the skill (no "use when")

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 1659 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)
  • +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
  • +3Description length 579: 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.

External checks

ClawHub: suspicious
This skill is for medication-compliance video analysis, but it silently creates or reuses an account identity, uploads sensitive home medication footage to remote services, and stores service tokens locally.
LLM: suspicious (high) · 28 Aug 2026