Requirements
- Target platform
- OpenClaw
- Install method
- Manual import
- Extraction
- Extract archive
- Prerequisites
- OpenClaw
- Primary doc
- SKILL.md
Tencent SkillHub ยท Productivity
AI Displacement Monitor
Monitor early-warning signals of AI-driven white-collar labor displacement and macro-financial spillovers. Use when you need a practical indicator framework,...
skill openclawclawhub Free
Monitor early-warning signals of AI-driven white-collar labor displacement and macro-financial spillovers. Use when you need a practical indicator framework,...
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Install for OpenClaw
Quick setup
- Download the package from Yavira.
- Extract the archive and review SKILL.md first.
- Import or place the package into your OpenClaw setup.
Package facts
- Download mode
- Yavira redirect
- Package format
- ZIP package
- Source platform
- Tencent SkillHub
- What's included
- SKILL.md, references/thresholds.example.json
Validation
- Use the Yavira download entry.
- Review SKILL.md after the package is downloaded.
- Confirm the extracted package contains the expected setup assets.
Install with your agent
Agent handoff
Hand the extracted package to your coding agent with a concrete install brief instead of figuring it out manually.
- Download the package from Yavira.
- Extract it into a folder your agent can access.
- Paste one of the prompts below and point your agent at the extracted folder.
New install
I downloaded a skill package from Yavira. Read SKILL.md from the extracted folder and install it by following the included instructions. Tell me what you changed and call out any manual steps you could not complete.
Upgrade existing
I downloaded an updated skill package from Yavira. Read SKILL.md from the extracted folder, compare it with my current installation, and upgrade it while preserving any custom configuration unless the package docs explicitly say otherwise. Summarize what changed and any follow-up checks I should run.
Trust & source
Release facts
- Source
- Tencent SkillHub
- Verification
- Indexed source record
- Version
- 1.0.2
Provenance
- Publisher
- spyfree
- Source page
- View original listing
- Canonical URL
- Open canonical page
Documentation
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: Signal Board (10 indicators with latest value, direction, threshold status) Composite Risk Light (GREEN / YELLOW / ORANGE / RED) Actionable Notes (portfolio/risk posture suggestions) 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[]
Category context
Workflow acceleration for inboxes, docs, calendars, planning, and execution loops.
Source: Tencent SkillHub
Largest current source with strong distribution and engagement signals.
Package contents
Included in package
1 Docs1 Config
- SKILL.md
- references/thresholds.example.json