AC feishu-smart-alarm
读取飞书/Lark 消息文本，识别是否包含需要提醒的待办和截止时间，并在由系统根据消息语义和时间跨度自动判断，更偏宽松一点的预留时间发出一次提醒。适用于飞书机器人在私聊或群聊中处理诸如“今天 5 点前给我”“明天下午三点提醒我”“周五前记得提交”这类消息；默认提醒给原消息发送者，并将提醒发回原飞书会话。识别成功后立即发送确认消息“我已经记住并在$时间点$提醒”。
As a process C 51/100 · Has gaps — weak spots: result and completion, when it triggers, inputs and preconditions
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: 11. 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. 2 mutating operations with no state check
- 100Tools and files. No external tools needed
- 100Steps. 63 steps
- 100Consistency. Name and required fields are in place
- 100Execution cost. Instruction body is 635 tokens
- low 10 top-level sections: this looks like several domains in one skill
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
- +4Description does not say when NOT to use the skill (false activations)
- +3Output format is not stated: the model decides each time
- -34 of 5 scripts are never mentioned in SKILL.md
- +1No license
- +2Single-language instructions
- +5Description quotes 4 example trigger phrases
- +3Description length 182: enough signal without eating the budget
- +4Structure: 15 headings
- +3Step-by-step instructions: 63 items
- +4Has examples (6 code blocks)
- +4Reference files are cited in the instructions (2 of 2)
Quality base 70; lint remarks subtract, signals add up to 100. Result: 78.
External checks
ClawHub: suspicious
This appears to be a legitimate Feishu/Lark reminder bot, but it should be reviewed because it can process every chat message, store message details locally, and later post reminders back into chats without strong user controls.
LLM: suspicious (high) · VirusTotal: · 29 May 2026