BD 多科学透视
多科学透视 — 用多个学科的视角透视任意想法，发现"未知的未知"。 将一段想法、对话或笔记，通过多个学科视角进行深度透视分析，拓展认知边界。 **当以下情况时使用此 Skill**： (1) 用户分享了一段对话、笔记或想法，希望多维度分析 (2) 用户说"多科学透视"、"多维分析"、"跨学科分析" (3) 用户想要头脑风暴，寻找创意的多种可能性 (4) 用户准备写深度文章，需要多角度切入点和随机性启发 (5) 用户想从跨学科视角重新审视一段内容
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.
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
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")
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 (多科学透视) differs from the folder (duoke-xue-tou-shi)
- 100Tools and files. No external tools needed
- 100Steps. 35 steps
- 100Execution cost. Instruction body is 504 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
- +1No license
- +2Single-language instructions
- +3Description length 226: enough signal without eating the budget
- +4Structure: 14 headings
- +3Step-by-step instructions: 35 items
- +4Has examples (1 code blocks)
- +4Reference files are cited in the instructions (6 of 6)
Quality base 70; lint remarks subtract, signals add up to 100. Result: 71.
External checks
ClawHub: clean
This is a text-only Chinese multidisciplinary analysis skill with no executable behavior, but users should be careful about any file paths or sensitive text they ask it to analyze.
LLM: benign (high) · VirusTotal: · 29 May 2026