技能详情（站内镜像，无评论）
作者：Li Xin @spyfree
许可证：MIT-0
MIT-0 ·免费使用、修改和重新分发。无需归因。
版本：v1.0.2
统计：⭐ 0 · 405 · 1 current installs · 1 all-time installs
⭐ 0
安装量（当前） 1
🛡 VirusTotal ：良性 · OpenClaw ：良性
Package：ai-displacement-monitor
安全扫描（ClawHub）
- VirusTotal ：良性
- OpenClaw ：良性
OpenClaw 评估
The skill is an instruction-only monitoring framework whose requirements and behavior are consistent with its stated purpose (no installs, no credentials requested).
目的
Name/description match the included indicator definitions and composite rules. The skill is instruction-only and uses the bundled thresholds.example.json for indicator IDs, tiers, triggers and interpretation; it does not request unrelated binaries, credentials, or filesystem access.
说明范围
SKILL.md is narrowly scoped to producing an indicator board, composite risk light, notes and gaps and explicitly references the bundled thresholds file. It does not instruct the agent to read unrelated system files or environment variables. One ambiguity: the instructions assume the agent will obtain values for the indicators from external data sources (job boards, JOLTS, LinkedIn, market data) but do not specify how to fetch them or which cre…
安装机制
No install spec and no code files—this is an instruction-only skill. Nothing is written to disk or fetched during installation.
证书
The skill requests no environment variables or credentials, which is proportional to an indicator/interpretation framework. However, practical use will typically require access to third-party data (APIs or web scraping). The skill itself does not request those credentials, so the user or host agent must supply them separately; verify any credentials you provide are only given to trusted integrations.
持久
always is false and the skill does not request persistent system-wide configuration or modify other skills. Autonomous invocation is allowed by default but that is standard and not by itself concerning here.
综合结论
This skill is a coherent, instruction-only framework (no installs or secrets). Before using: (1) confirm how your agent will source indicator data—if it will call external APIs or scrape sites, decide which API keys/credentials you will supply and to which component; (2) review and, if needed, adapt the thresholds.example.json to match your data definitions and coverage; (3) if you plan to automate alerts, test outputs manually first (check ti…
安装（复制给龙虾 AI）
将下方整段复制到龙虾中文库对话中，由龙虾按 SKILL.md 完成安装。
请把本段交给龙虾中文库（龙虾 AI）执行：为本机安装 OpenClaw 技能「AI Displacement Monitor」。简介：Monitor early-warning signals of AI-driven white-collar labor displacement and …。
请 fetch 以下地址读取 SKILL.md 并按文档完成安装：https://raw.githubusercontent.com/openclaw/skills/refs/heads/main/skills/spyfree/ai-displacement-monitor/SKILL.md
（来源：yingzhi8.cn 技能库）SKILL.md
---
name: ai-displacement-monitor
description: Monitor early-warning signals of AI-driven white-collar labor displacement and macro-financial spillovers. Use when you need a practical indicator framework, thresholds, alert logic, and concise risk updates for employment, consumption, and credit stress.
---
# AI Displacement Monitor
Use this skill to produce a structured risk monitor for AI-led labor substitution and downstream financial stress.
## Output Format
Always return:
1. **Signal Board** (10 indicators with latest value, direction, threshold status)
2. **Composite Risk Light** (`GREEN` / `YELLOW` / `ORANGE` / `RED`)
3. **Actionable Notes** (portfolio/risk posture suggestions)
4. **Data Gaps** (missing or stale inputs)
## Indicator Framework
Read `references/thresholds.example.json` and follow its indicator IDs, thresholds, and tiering.
Also apply the "Industrial-Revolution Lens" when interpreting risk:
- Do not evaluate layoffs alone.
- Compare **substitution speed** vs **re-absorption speed** (new demand + new capex).
- If substitution weakens labor but capex/reinvestment accelerates, avoid over-escalating crisis labels.
- **Tier A (Leading labor demand)**: A1-A4
- **Tier B (Labor market confirmation)**: B1-B3
- **Tier C (Spillover: consumption/credit)**: C1-C3
## Composite Rule
- **YELLOW**: Tier A triggered >= 2
- **ORANGE**: Tier A >= 2 and Tier B >= 1
- **RED**: Tier A >= 2 and Tier B >= 1 and Tier C >= 1
- **GREEN**: otherwise
## Weak-Links Interpretation (Jones Lens)
When assessing macro impact, apply a weak-links check:
- Broad automation can still deliver gradual macro gains if key bottleneck tasks remain scarce.
- Do not infer immediate macro collapse from partial task automation alone.
- If bottleneck proxies remain tight (D3 worsening, D4 weak reinvestment), keep risk elevated.
- If bottlenecks ease via reinvestment/capex and purchasing power improves (D1/D2), avoid over-escalation.
## Minimum Quality Rules
- Time-stamp each metric and note frequency mismatch (weekly vs monthly vs quarterly).
- If source coverage is partial, mark confidence as `low` or `medium`.
- Never hide missing data; list it under **Data Gaps**.
- If more than 3 indicators are missing, downgrade confidence by one level.
## Recommended Alert Style
Keep alerts short and decision-oriented:
- "What changed"
- "Why it matters now"
- "What to do next"
## Optional JSON Mode
If user asks for machine-readable output, return:
- `asOf`
- `signals[]` (id, value, unit, threshold, triggered, trend)
- `composite`
- `confidence`
- `gaps[]`
- `notes[]`