Getting it into your agent
One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.
npx skills add wentorai/research-plugins --skill post-labor-economicsgit clone --depth 1 https://github.com/wentorai/research-pluginsWrote this? Show the measurements
A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.
[](https://agentmods.dev/skills/wentorai/research-plugins/post-labor-economics)<a href="https://agentmods.dev/skills/wentorai/research-plugins/post-labor-economics"><img src="https://agentmods.dev/badge/skills/wentorai/research-plugins/post-labor-economics/github.svg" alt="Measured on agentmods" height="20"></a>Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.
<a href="https://agentmods.dev/skills/wentorai/research-plugins/post-labor-economics"><img src="https://agentmods.dev/badge/skills/wentorai/research-plugins/post-labor-economics.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector pass
What it costs to keep this loaded
Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5.1 | $0.00020 | $0.02591 |
| Opus 5 | $0.00010 | $0.01295 |
| Sonnet 5 | $0.00004 | $0.00518 |
| Haiku 4.5 | $0.00002 | $0.00259 |
Grade A, and why
post-labor-economics scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 7d ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
How it starts
The opening of the file, as written. The whole thing — 255 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Post-Labor Economics Guide
Overview
Post-labor economics studies the economic consequences of advanced automation -- the possibility that AI and robotics will displace human labor at a scale and speed that overwhelms traditional adjustment mechanisms. While technological unemployment is an old concern (dating to the Luddites and Keynes's "Economic Possibilities for Our Grandchildren"), the current wave of AI capabilities has made the question urgent: what happens to labor markets, income distribution, and economic growth when machines can perform most cognitive and physical tasks?
This is not science fiction. The academic literature on task displacement, skill-biased technological change, and automation risk has produced substantial empirical findings and theoretical frameworks. Researchers from economics, political science, sociology, and computer science are converging on these questions.
This guide covers the key theoretical models, empirical evidence, policy proposals (UBI, robot taxes, stakeholder funds), and methodological approaches for studying the economics of automation. It is designed for researchers entering this rapidly growing field and for those in adjacent disciplines who need to engage with the economic arguments.
Theoretical Frameworks
The Task-Based Model of Automation
The canonical model (Acemoglu & Restrepo, 2018, 2019) decomposes production into tasks rather than jobs:
Production = f(Tasks performed by Labor, Tasks performed by Capital)
Key dynamics:
1. DISPLACEMENT EFFECT
- Machines replace humans in existing tasks
- Reduces labor demand, depresses wages
- Concentrated in routine cognitive and manual tasks
2. PRODUCTIVITY EFFECT
- Automation lowers costs, increases output
- Some gains flow to workers via cheaper goods
- But distribution depends on market structure
3. REINSTATEMENT EFFECT
- New tasks created that require human comparative advantage
- Historically: ATMs → bank branch expansion → more tellers (temporarily)
- Question: Is this time different? Will new tasks emerge fast enough?
4. NET EFFECT
- Historical pattern: displacement < reinstatement (net job growth)
- Current concern: AI attacks both routine AND non-routine tasks
- Speed of displacement may exceed speed of reinstatement
What this file has done since we first saw it
Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.
- 7d ago First seen · 255 lines · 20 tokens per session scan A 1598a49fe468
post-labor-economics is a skill published in the GitHub repository wentorai/research-plugins (291 stars, last pushed 2mo ago), licensed MIT. It adds 20 tokens to every session and 2,591 once invoked, about $0.0001 per session on Opus 5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-09-03.
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