AD record-keeper
工作记录归档标准。当用户要求记录工作内容时,严格按照本 skill 的类别和模板执行。 触发场景:记录会议、记录需求、记录规划、写SOP、写复盘/报告、值班/人事等行政记录、创建记录文件、归档工作记录。 类别严格封闭,共13类:meeting / requirement / plan / sop / report / admin / badcase / task / weekly / monthly / quarterly / yearly / memo,不可自行扩展。 所有记录文件存放在 records/YYYY-MM/ 下,文件名格式:[YYYYMMDD]-[category]-[topic]-[sub-topic]-[seq].md badcase 类使用专用文件名格式:[YYYYMMDD]-badcase-[service]-[keyword/topic][-seq].md
工作记录归档标准。当用户要求记录工作内容时,严格按照本 skill 的类别和模板执行。 触发场景:记录会议、记录需求、记录规划、写SOP、写复盘/报告、值班/人事等行政记录、创建记录文件、归档工作记录。 类别严格封闭,共13类:meeting / requirement / plan / sop / report…
As a process D 43/100 · 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 · 1
✓ No critical or high findings
Medium and low: 1
-
low Exfiltration
read-dotenvSKILL.md:294Reads a .env filesource .env && python3 embed.py init # 第一个词是 source
Files scanned: 9. 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") - note
frontmatter-keyunknown frontmatter key "alwaysLoad"
Process rating: all ten parameters 43/100
- 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
- 60Tools and files. Uses tools (python) that frontmatter does not declare
- 100Steps. 116 steps
- 100Consistency. Name and required fields are in place
- 100Execution cost. Instruction body is 2457 tokens
- low The response is described with custom markup (3 tags): a typed call is more reliable
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 396: enough signal without eating the budget
- +4Structure: 30 headings
- +3Step-by-step instructions: 116 items
- +4Has examples (15 code blocks)
- +4Reference files are cited in the instructions (15 of 15)
- +3All 2 scripts are documented
Quality base 70; lint remarks subtract, signals add up to 100. Result: 78.