BC ai-intel-workshop
分析 AI 对任意行业的冲击。两阶段执行：先联网检索近 12 个月信息并按四级（S/A/B/噪音）判级、输出含来源时间与核实状态的信号报告，经用户确认后产出公众号/小红书/抖音三平台内容素材（长文、脚本、发布配文、封面提示词）并落盘。触发语：AI情报车间、AI行业影响分析、分析AI对XX行业的影响/冲击/机会、AI风向标、AI冲击波。
分析 AI 对任意行业的冲击。两阶段执行：先联网检索近 12…
As a process C 53/100 · Has gaps — 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: 8. 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. 126 steps
- 100Consistency. Name and required fields are in place
- 100Execution cost. Instruction body is 2218 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
- +2Single-language instructions
- +3Description length 168: enough signal without eating the budget
- +4Structure: 34 headings
- +3Step-by-step instructions: 126 items
- +1License stated
Quality base 70; lint remarks subtract, signals add up to 100. Result: 69.
External checks
ClawHub: clean
This skill is a disclosed content-research workflow that uses web search and writes generated files only within its stated AI industry-analysis purpose.
LLM: benign (high) · VirusTotal: · 27 Aug 2026