BF universal-expert
百变专家 · Universal Expert Engine v5.3.3 任意领域的专业分析、决策支持、信息验证。 触发：说"深度分析 XXX"、"完整分析 XXX"、"全面评估 XXX"时加载。 日常闲聊/简单问答不触发。 ⚠️ 强制要求：分析前必须先搜索收集事实，禁止跳过事实层直接推演。累计修复32项逻辑缺陷。
As a process F 35/100 · Will not run — References files that are not bundled: [日期]
How to improve
- Say in the description WHEN to use the skill ("use when…", example requests): that is the agent's main cue.
- The text references files that are not there: add them or drop the references.
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: 2. 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") - warning
missing-refreference to a missing file: [日期]
Process rating: all ten parameters 35/100
Will not run. References files that are not bundled: [日期]
- 0Tools and files. 1 referenced file(s) missing: [日期]
- 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
- 100Steps. 40 steps
- 100Consistency. Name and required fields are in place
- 100Execution cost. Instruction body is 593 tokens
- 100Running it twice. No mutating operations
- low 10 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
- -216 emoji in the instructions: noise for the model
- +1No license
- +2Single-language instructions
- +5Description quotes 3 example trigger phrases
- +3Description length 159: enough signal without eating the budget
- +4Structure: 16 headings
- +3Step-by-step instructions: 40 items
- +4Has examples (3 code blocks)
Quality base 70; lint remarks subtract, signals add up to 100. Result: 69.
External checks
ClawHub: clean
This is an instruction-only analysis skill that asks the agent to research and cite sources before answering, with no code, persistence, or hidden access requests.
LLM: benign (high) · VirusTotal: · 29 May 2026