SKILLEMALL.ai

BF incontinence_alert_analysis

Automatically identifies wet clothing and abnormal excretion via visual AI. Instantly notifies caregivers to improve care for incontinent elderly, bedridden patients, and infants, reducing skin issues and complications. | 智能失禁状态提醒技能,基于视觉AI自动识别衣物潮湿、排泄异常等状况,第一时间推送通知给看护人员,提升失能老人、卧床病人、婴幼儿的护理质量,减少皮肤问题和并发症

ClawHub Agent Skills author: smyx-sunjinhui v1.0.13 MIT-0 29 files body ≈ 1 368 tokens Open the sourceclawhub.ai analyzed 3 d ago

As a process F 27/100 · Will not run — weak spots: steps, result and completion, when it triggers

ProcedureInfrastructuretype and topics are labelled automatically from the skill text
JSON
Technical rating
B
86/100
safety, quality, tests
Safety 60%
100
Quality 40%
64
Run on models
none yet
Process rating
F
27/100
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: 29. Evidence is masked. Grey chips explain why severity was lowered.

Against the Agent Skills spec

  • warning name-format name should be kebab-case (lowercase letters, digits, hyphens)
  • warning description-no-when description does not say WHEN to use the skill (no "use when")

Process rating: all ten parameters 27/100

  • 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
  • 40Consistency. Frontmatter name (incontinence_alert_analysis) differs from the folder (smyx-incontinence-alert-analysis)
  • 60Tools and files. Uses tools (python) that frontmatter does not declare
  • 100Execution cost. Instruction body is 1368 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
  • -254 emoji in the instructions: noise for the model
  • -31 of 3 scripts are never mentioned in SKILL.md
  • +2Single-language instructions
  • +3Description length 301: enough signal without eating the budget
  • +4Structure: 18 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: 64.

External checks

ClawHub: suspicious
This skill has a coherent caregiving purpose, but it silently creates and reuses identity state, stores tokens locally, and can send sensitive care media and credentials over broad or plaintext network paths.
LLM: suspicious (high) · 7 Sept 2026