BC dfma-activity-guide
DFMA活动引导技能，当群内被@机器人或出现DFMA相关关键词（如“DFMA会议”“设计评估”“风险识别”）时触发，按DFMA标准流程（前期准备→过程推进→结果输出）分步引导群聊用户推进DFMA活动，每一步明确告知需完成操作和提供的信息，实时跟踪参与进度并@提醒未响应，对偏离主题发言温和引导回归，最终自动生成完整DFMA活动报告并同步群聊，支持链接查看与下载。
As a process C 53/100 · Has gaps — weak spots: result and completion, when it triggers, inputs and preconditions
Proceduretype 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 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. 30 steps
- 100Consistency. Name and required fields are in place
- 100Execution cost. Instruction body is 327 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
- +4No input/output examples
- -42 reference files, but SKILL.md never points to them: the model will not open them
- +1No license
- +2Single-language instructions
- +3Description length 181: enough signal without eating the budget
- +4Structure: 9 headings
- +3Step-by-step instructions: 30 items
Quality base 70; lint remarks subtract, signals add up to 100. Result: 64.
External checks
ClawHub: clean
技能声明与其运行指令在功能上总体一致——它需要访问群聊上下文并在群内引导并生成报告，唯一需注意的是对群聊内容的读取与使用以及创建云文档的权限。
LLM: benign (medium) · VirusTotal: · 29 May 2026