AC OAISR
OAISR - Occupational AI Displacement Risk | 职业AI替代风险评估 中文说明： 职业AI暴露度分析工作流。当用户发送职业名称、询问"XX职业的暴露度"、或提及"AI替代风险"时激活。 输出标准四步分析报告： 1. 双进度条（理论暴露度 vs 实际暴露度） 2. 任务分解表（6~8项核心工作活动的β值与估算） 3. 综合估算（加权暴露度 + 置信度 + 核心结论） 4. 可选：应对策略（AI不可替代能力清单） 数据来源：Anthropic《Labor market impacts of AI》(2026-03-05) 地址：https://www.anthropic.com/research/labor-market-impacts English Description: Occupational AI Displacement Risk Assessment. Activated when user sends a job title, asks about "AI exposure risk of XX profession", or mentions "AI replacement risk". Standard 4-Step Analysis Output: 1. Dual progress bars (theoretical vs actual exposure) 2. Task breakdown table (6-8 core work activities with β values) 3. Comprehensive estimate (weighted exposure + confidence + key conclusion) 4. Optional: Coping strategies (AI-irreplaceable capability清单) Data Source: Anthropic《Labor market impacts of AI》(2026-03-05)
As a process C 51/100 · Has gaps — weak spots: result and completion, when it triggers, inputs and preconditions
How to improve
- 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: 4. 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)
Process rating: all ten parameters 51/100
- 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
- 30Running it twice. 1 mutating operations with no state check
- 100Tools and files. No external tools needed
- 100Steps. 34 steps
- 100Consistency. Name and required fields are in place
- 100Execution cost. Instruction body is 696 tokens
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)
- +3Description length 890: 120–800 characters recommended
- +3Output format is not stated: the model decides each time
- -41 reference files, but SKILL.md never points to them: the model will not open them
- +1No license
- +2Single-language instructions
- +5Description quotes 4 example trigger phrases
- +4Structure: 14 headings
- +3Step-by-step instructions: 34 items
- +4Has examples (2 code blocks)
Quality base 70; lint remarks subtract, signals add up to 100. Result: 77.