SKILLEMALL.ai

AC sleep-optimizer

基于循证睡眠医学和生活阶段的个性化睡眠改善计划生成器(Node.js 实现,含可视化图表)。用户输入 sleep-optimizer(或 /sleep-optimizer)主动调用,或询问任何睡眠相关问题(睡眠、失眠、入睡困难、作息调整、睡眠质量、熬夜恢复、期末/考研期间睡眠等)时自动触发:先按问题框架收集睡眠数据,再生成含可视化图表的个性化睡眠改善计划

ClawHub Agent Skills author: 55zhang v1.0.0 MIT-0 6 files body ≈ 1 813 tokens Open the sourceclawhub.ai analyzed 2 d ago

基于循证睡眠医学和生活阶段的个性化睡眠改善计划生成器(Node.js 实现,含可视化图表)。用户输入 sleep-optimizer(或…

As a process C 53/100 · Has gaps — weak spots: result and completion, when it triggers, inputs and preconditions

ProcedureInfrastructuretype and topics are labelled automatically from the skill text
JSON
Technical rating
A
92/100
safety, quality, tests
Safety 60%
100
Quality 40%
80
Run on models
none yet
Process rating
C
53/100
Has gaps
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: 6. 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 53/100

  • 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
  • 100Tools and files. Tools declared in frontmatter
  • 100Steps. 92 steps
  • 100Consistency. Name and required fields are in place
  • 100Execution cost. Instruction body is 1813 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)
  • +3Output format is not stated: the model decides each time
  • +2Single-language instructions
  • +3Description length 178: enough signal without eating the budget
  • +4Structure: 31 headings
  • +3Step-by-step instructions: 92 items
  • +4Has examples (6 code blocks)
  • +4Reference files are cited in the instructions (2 of 2)
  • +3All 1 scripts are documented
  • +1License stated

Quality base 70; lint remarks subtract, signals add up to 100. Result: 80.

External checks

ClawHub: suspicious
The skill is a coherent sleep-planning helper, but it has broad automatic activation and under-scoped local file read/write behavior.
LLM: suspicious (high) · VirusTotal: · 30 Aug 2026