SKILLEMALL.ai

AC what-to-eat-today

为四口之家(夫妻+爷爷+2岁宝宝)规划一天三餐。当用户问「今天吃什么」「帮我安排一下饭菜」「早饭/午饭/晚饭吃什么」「明天带什么饭」「不知道吃啥」等日常吃饭决策问题时主动使用此skill。结合电饭锅预约、蒸菜省时、带饭便当、宝宝和老人适口等约束来推荐。自动感知日期(节气/节日/周末/季节),通过程序脚本实现跨会话排重,确保每次不重样。

ClawHub Agent Skills author: JiaNanHou v1.0.0 MIT-0 7 files body ≈ 707 tokens Open the sourceclawhub.ai analyzed 2 d ago

为四口之家(夫妻+爷爷+2岁宝宝)规划一天三餐。当用户问「今天吃什么」「帮我安排一下饭菜」「早饭/午饭/晚饭吃什么」「明天带什么饭」「不知道吃啥」等日常吃饭决策问题时主动使用此skill。结合电饭锅预约、蒸菜省时、带饭便当、宝宝和老人适口等约束来推荐。自动感知日期(节气/节日/周末/季节),通过程序脚本实现跨会话排重…

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

ProcedureAI and agentstype and topics are labelled automatically from the skill text
JSON
Technical rating
A
92/100
safety, quality, tests
Safety 60%
100
Quality 40%
79
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: 7. 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. No external tools needed
  • 100Steps. 16 steps
  • 100Consistency. Name and required fields are in place
  • 100Execution cost. Instruction body is 707 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
  • +1No license
  • +2Single-language instructions
  • +3Description length 168: enough signal without eating the budget
  • +4Structure: 16 headings
  • +3Step-by-step instructions: 16 items
  • +4Has examples (4 code blocks)
  • +4Reference files are cited in the instructions (2 of 2)
  • +3All 1 scripts are documented

Quality base 70; lint remarks subtract, signals add up to 100. Result: 79.

External checks

ClawHub: clean
This skill is a local meal-planning helper that only uses a dish library and a small meal-history file to avoid repeats.
LLM: benign (high) · VirusTotal: · 15 Jun 2026