BD personal-worklist-via-feishu
飞书多维表格个人工作台账。双层读取：Frontmatter(每次触发必读) + Body(按需读)。 【触发词】 "创建个人工作台账"/"create worklist" | "记一下工作"+内容/"add task"+内容 | "完成了"/"cancelled"/"推迟"/"defer" | "复盘"/"review" | "诊断"/"diagnose" 【每次触发必验5条】 1.语言未设置→先问用户(中文/英文/c/e)，禁止跳过 2.三项必填逐一确认(任务名称/优先级①~④/截止日期)，未提供则追问，禁止自行编造 3.来源分类自动归类(未提及→临时任务[U]，协作→协作任务[C]，周期→例行任务[R]，计划内→计划任务[P])，无需追问 4.可选字段(工作要求/链接/干系人/备注/预计时长)：用户提供则写，未提供则留空，禁止推断 5.openclaw cron add/delete已授权(2026-04-27)，无需确认直接执行 【关键约束】 init_table.js必须带--open-id(用户open_id)，否则用户无法访问表格 add_task.js首次录入成功后脚本内部自动触发cron提醒(memory判断) 禁止语言未确认前执行任何脚本 【字段速查】 优先级：①紧急且重要/②重要不紧急/③紧急不重要/④不紧急不重要 状态：待办/进行中/已完成/取消 来源：计划任务[P]/临时任务[U]/例行任务[R]/协作任务[C]
As a process D 42/100 · Unfinished process — 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.
- 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: 24. 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 42/100
- 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. 9 mutating operations with no state check
- 60Tools and files. Uses tools (node) that frontmatter does not declare
- 70Execution cost. Instruction body is 4441 tokens
- 100Steps. 160 steps
- 100Consistency. Name and required fields are in place
- low 12 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
- -230 emoji in the instructions: noise for the model
- -35 of 19 scripts are never mentioned in SKILL.md
- +1No license
- +2Single-language instructions
- +5Description quotes 6 example trigger phrases
- +3Description length 632: enough signal without eating the budget
- +4Structure: 30 headings
- +3Step-by-step instructions: 160 items
- +4Has examples (3 code blocks)
Quality base 70; lint remarks subtract, signals add up to 100. Result: 72.