AC smart-reminder
智能定时提醒助手，支持：1) 多人格提醒风格（可爱/元气/认真/毒舌/温柔），2) 多频次任务进度追踪（本周已完成训练 1/3），3) 上下文感知的鼓励/反馈（上次没完成则下次鼓励）。集成 cron 调度。触发词：'提醒我' '定个提醒' '定时提醒' 'remind me' '帮我记着' '设置提醒' '设定提醒'
As a process C 51/100 · Has gaps — weak spots: result and completion, when it triggers, inputs and preconditions
ProcedureSoftware developmentAI and agentstype and topics are labelled automatically from the skill text
How to improve
- 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: 3. 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 51/100
- 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
- 30Running it twice. 1 mutating operations with no state check
- 100Tools and files. No external tools needed
- 100Steps. 67 steps
- 100Consistency. Name and required fields are in place
- 100Execution cost. Instruction body is 1934 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)
- +3Output format is not stated: the model decides each time
- -216 emoji in the instructions: noise for the model
- +1No license
- +2Single-language instructions
- +3Description length 159: enough signal without eating the budget
- +4Structure: 18 headings
- +3Step-by-step instructions: 67 items
- +4Has examples (8 code blocks)
- +4Reference files are cited in the instructions (1 of 1)
- +3All 1 scripts are documented
Quality base 70; lint remarks subtract, signals add up to 100. Result: 77.
External checks
ClawHub: suspicious
The skill is a coherent reminder assistant, but it creates persistent scheduled agent jobs and cross-channel messages without clearly showing how those jobs are removed when a reminder is canceled.
LLM: suspicious (medium) · VirusTotal: · 29 May 2026