BD Jobs-System
乔布斯式决策分析工作流（社区演示版）。当用户需要分析赛道/创业机会、做产品定义、战略取舍、砍需求做减法、竞品定位、用户洞察、技术窗口判断，或用「乔布斯视角/连点成线」拆解问题时启用。三层推理框架（理解意图+拷问+答案+Voice 蒸馏）产出带证据链、确定性标记与域类型路由的结构化决策；B 端/I 层危险域标⚠️翻车不模仿其判断，AI/云/社媒等未及域标「框架推演·非本人立场」。非触发（闲聊、纯信息检索、纯代码实现）不加载。
乔布斯式决策分析工作流（社区演示版）。当用户需要分析赛道/创业机会、做产品定义、战略取舍、砍需求做减法、竞品定位、用户洞察、技术窗口判断，或用「乔布斯视角/连点成线」拆解问题时启用。三层推理框架（理解意图+拷问+答案+Voice 蒸馏）产出带证据链、确定性标记与域类型路由的结构化决策；B 端/I…
As a process D 49/100 · 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: 10. Evidence is masked. Grey chips explain why severity was lowered.
Against the Agent Skills spec
- warning
name-formatname should be kebab-case (lowercase letters, digits, hyphens) - warning
description-no-whendescription does not say WHEN to use the skill (no "use when") - note
frontmatter-keyunknown frontmatter key "agent_created"
Process rating: all ten parameters 49/100
- 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
- 40Consistency. Frontmatter name (Jobs-System) differs from the folder (jobs-system-community)
- 100Tools and files. No external tools needed
- 100Steps. 92 steps
- 100Execution cost. Instruction body is 2289 tokens
- 100Running it twice. No mutating operations
- 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
- +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 213: enough signal without eating the budget
- +4Structure: 15 headings
- +3Step-by-step instructions: 92 items
- +4Has examples (1 code blocks)
Quality base 70; lint remarks subtract, signals add up to 100. Result: 66.