Setup & Installation
Or with the ClawHub CLI, for registry-managed skill folders outside a full OpenClaw workspace:
Version History
Add Weak-Links (Jones) interpretation layer for bottleneck-aware macro risk reading
What This Skill Does
Tracks early-warning signals of AI-driven white-collar labor displacement and downstream financial stress. Produces a structured risk monitor with 10 indicators across three tiers (leading labor demand, labor market confirmation, consumption/credit spillover) and a composite risk rating from GREEN to RED.
Balances substitution speed against re-absorption speed using a tiered indicator framework, avoiding the over-escalation typical of single-metric labor displacement assessments.
When to use it
- Weekly labor market stress briefings for risk managers
- Portfolio positioning reviews during rapid AI adoption cycles
- Tracking white-collar layoff trends against capex reinvestment data
- Monitoring consumer credit stress linked to AI-driven unemployment
- Generating machine-readable risk snapshots for financial dashboards
Example Workflow
Here's how your AI assistant might use this skill in practice.
User asks: What is the current AI displacement risk level based on the latest employment and credit indicators?
- 1Reads thresholds.example.json to load indicator IDs, thresholds, and tier assignments
- 2Evaluates each of the 10 indicators across Tier A (leading labor demand), Tier B (labor market confirmation), and Tier C (consumption/credit spillover)
- 3Applies the composite rule to assign a risk light: GREEN, YELLOW, ORANGE, or RED
- 4Runs the Industrial-Revolution and Jones Lens checks to avoid over-escalating from partial automation data
- 5Outputs a Signal Board, Composite Risk Light, Actionable Notes, and Data Gaps list
ORANGE risk level with 2 Tier A signals triggered (tech sector posting decline, AI tool adoption rate above threshold) and 1 Tier B signal (claims uptick in white-collar categories); recommends reducing consumer credit exposure and flagging stale quarterly wage data as a gap