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agentCLAWHUBUnverified

Zero-Sum Game

Activate when: someone asks 'are we fighting over a fixed pie?', 'should we cooperate or compete?', 'is the market growing or are we just stealing share?', u... Skill: Zero-Sum Game Owner: deciqai Summary: Activate when: someone asks 'are we fighting over a fixed pie?', 'should we cooperate or compete?', 'is the market growing or are we just stealing share?', u... Tags: latest:1.0.6 Version history: v1.0.6 | 2026-07-16T18:22:27.731Z | user Description tail link + agents machine-readable metadata line (deciqai.com/s/zero-sum-game.json) v1.0.5 | 2026-07-09T11:22:58.435Z | user

OpenClaw

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Rank

Safety

Downloads

1.2k

Updated

Oct 10, 2026

Version

1.0.6

Source

CLAWHUB

About

What it does, and when to use it.

Capability contract not published. No trust telemetry is available yet. 1.2K downloads reported by the source. Last updated 10/10/2026.

Avoid when

Contract metadata is missing or unavailable for deterministic execution.

Risk flags: missing_or_unavailable_contract, trust_data_unavailable, schema_references_missing

Public facts

Every fact links back to the source it came from.

Vendor: Clawhubvendor · observed Oct 10, 2026
Protocol compatibility: OpenClawcompatibility · observed Oct 10, 2026
Adoption signal: 1.2K downloadsadoption · observed Oct 10, 2026
Latest release: 1.0.6release · observed Jul 16, 2026
Handshake status: UNKNOWNsecurity

Install and run

Setup complexity: low.

clawhub skill install s17a4mqcnk515kvaca5ze55d0x88pfpx:zero-sum-game

Setup complexity is classified as HIGH. You must provision dedicated cloud infrastructure or an isolated VM. Do not run this directly on your local workstation.
Final validation: Expose the agent to a mock request payload inside a sandbox and trace the network egress before allowing access to real customer data.

Contract: missing

curl -s "https://www.xpersona.co/api/v1/agents/clawhub-deciqai-zero-sum-game/snapshot"

Documentation

CLAWHUB

143,938 characters of source documentation, loaded on request.

Extracted files

5 files captured from the source.

SKILL.md

---
name: zero-sum-game
description: "Activate when: someone asks 'are we fighting over a fixed pie?', 'should we cooperate or compete?', 'is the market growing or are we just stealing share?', uses phrases like 'winner-take-all', 'race to the bottom', or 'your gain is my loss', or needs to check whether a negotiation/market/policy situation is truly zero-sum before designing strategy.
Do NOT activate when: the situation is already confirmed zero-sum (chess, derivatives, fixed-license auctions) and diagnosis is complete — go straight to minimax; or the question is already framed at the equilibrium level — use nash-equilibrium directly. More: deciqai.com/c/zero-sum-game"
---

# Zero-Sum Game

## Overview

Zero-sum means total value is fixed — one player's gain is another's exact loss. Most real-world competition is NOT zero-sum: the pie can grow, shrink, or be split in many ways. Misdiagnosis sends strategy in the wrong direction from step one. The most consequential error is **zero-sum bias**: the tendency to perceive non-zero-sum situations as zero-sum.

Neighbor skills: use `prisoners-dilemma` when confirmed non-zero-sum but cooperation keeps failing. Use `strategic-commitment` when genuinely zero-sum and you need credible deterrence. Use `nash-equilibrium` for the equilibrium solution in confirmed zero-sum settings.

## When to Use

Apply this skill when: entering a competitive situation before determining whether total value is fixed; someone proposes a negotiation assuming "what I gain, you lose"; a market entry hinges on whether total market size is fixed; a policy analysis needs to assess whether an intervention redistributes or creates welfare; someone uses zero-sum language ("winner-take-all", "race to the bottom", "fixed pie"); or someone frames the AI race, AI capex/compute buildout, AI-talent competition, or AI-native market entry as a single winner-take-all contest and you need to separate the genuinely fixed inputs (near-term compute/talent) from the growing pie (AI-driven productivity and adoption).

**When NOT to use:** already confirmed zero-sum — go straight to minimax; clear cooperative surplus with no competitive distribution problem; stakes trivial and reversible; question already at equilibrium level — use `nash-equilibrium` directly.

## Coaching Novices (Adaptive Front Door)

- **Engine mode:** user has a concrete case → run The Process directly.
- **Coach mode:** user is unfamiliar or has no concrete case → guide step by step.

In Coach mode, respond one step at a time. Each [WAIT] is a hard stop — output only that step's question, then stop.

1. **One-line what-it-is.** Zero-sum: total value fixed — if I get more, you get less by exactly the same amount. Most real-world competition is NOT zero-sum. The diagnosis changes everything about strategy.
2. **Check fit.** Is the resource at stake genuinely fixed? If the total can change through cooperation, innovation, or trade, it is likely non-zero-sum.
3. **Elicit the real

_meta.json

{
  "ownerId": "kn754b8sk22s8c6gjxt02bftbn88q7ye",
  "slug": "zero-sum-game",
  "version": "1.0.6",
  "publishedAt": 1784226147731
}

references/sources.md

# Sources — zero-sum-game

> *Primary sources for the [zero-sum-game](../SKILL.md) skill.*

- Von Neumann, J. & Morgenstern, O. (1944). *Theory of Games and Economic Behavior.* Princeton University Press. The founding text of game theory; contains the Minimax Theorem and the formal definition of zero-sum games. Reprint available via Princeton University Press. https://press.princeton.edu/books/paperback/9780691130613/theory-of-games-and-economic-behavior
- Schelling, T.C. (1960). *The Strategy of Conflict.* Harvard University Press. The canonical analysis of zero-sum vs. non-zero-sum conflict in negotiation and deterrence, including the Cold War application. https://www.hup.harvard.edu/books/9780674840317
- Nash, J. F. (1950). "Equilibrium Points in n-Person Games." *Proceedings of the National Academy of Sciences*, 36(1), pp. 48–49. The equilibrium concept that generalizes beyond zero-sum settings; for zero-sum games, Nash equilibrium coincides with minimax. https://doi.org/10.1073/pnas.36.1.48
- Meegan, D.V. (2010). "Zero-Sum Bias: Perceived Competition Despite Unlimited Resources." *Frontiers in Psychology*, 1, 191. Primary empirical documentation of zero-sum bias as a cognitive phenomenon — the systematic tendency to perceive zero-sum structures when they are not present. https://doi.org/10.3389/fpsyg.2010.00191
- Dixit, A. & Nalebuff, B. (1991). *Thinking Strategically.* W.W. Norton. The standard practical treatment of zero-sum vs. non-zero-sum games for practitioners; Chapter 4 covers the distinction in business contexts. ISBN 978-0393310351.
- Irwin, D.A. (2011). *Peddling Protectionism: Smoot-Hawley and the Great Depression.* Princeton University Press. The definitive historical account of the 1930 tariff — the political economy of its passage, the foreign retaliation it provoked, and its role in the collapse and fragmentation of world trade; the canonical documented case of zero-sum misdiagnosis in trade policy. ISBN 978-0691150321.

- International Energy Agency (2025). *Energy and AI* (World Energy Outlook Special Report), published April 2025. IEA, Paris. Documents the 2024–2025 scale-up of AI compute and data-center demand, and the physical constraints (power, hardware supply, lead times) that bound near-term capacity — useful for grounding the "near-term compute is a fixed input" side of the AI zero-sum diagnosis. https://www.iea.org/reports/energy-and-ai
- Stanford HAI (2025). *Artificial Intelligence Index Report 2025,* published April 2025. Stanford Institute for Human-Centered AI. Tracks model performance, investment, adoption, and compute trends through 2024 — the widely cited public baseline for the state of AI competition, capital expenditure, and the concentration of frontier capability and talent. https://hai.stanford.edu/ai-index/2025-ai-index-report

**What is not cited and why:** Popular business writing frequently attributes the phrase "zero-sum game" to competitive strategy without checking whether the specific situati

examples/ai-competition-fixed-vs-growing-pie-2024-2026.md

# Method in Action: Where the AI Race Is Zero-Sum and Where It Isn't (2024–2026)

> *Example for the [zero-sum-game](../SKILL.md) skill.*

By 2024–2026 the dominant framing of the AI boom was a single "race" — one leaderboard, one winner, everyone else loses. That framing quietly bundles together resources with very different structures. Some inputs to AI are genuinely fixed in the near term and therefore zero-sum; the output — AI-driven productivity — is not. Treating the whole thing as one zero-sum contest is exactly the diagnosis error this skill is built to catch: it pushes firms toward pure capture (outbid rivals, hoard talent, block competitors) when part of the game rewards expansion (build the market, enlarge supply, complement rather than substitute).

The point of the diagnosis is that "the AI race" is not one game — it is a **mixed** game, and you have to name the resource before you know which move applies.

Running the Diagnosis:

**Step 1 (define the contested resource).** Split "AI competition" into its distinct contested resources rather than treating it as one blob:
- *Near-term advanced-chip and high-bandwidth-memory (HBM) supply* — the units of leading-edge accelerators and the HBM stacks they require, buildable only through a small number of suppliers with long lead times.
- *Top-tier AI research talent* — the small pool of people who have actually trained frontier systems.
- *AI-driven productivity / the value AI creates for end users* — the output the whole boom is ostensibly about.

Each is a nameable, distinct unit. That is the precondition for a real diagnosis; "who wins AI" is not a resource.

**Step 2 (test fixity) — run separately per resource:**
- *Chips/HBM, near term:* **fixed.** Leading-edge fabrication and advanced-memory capacity cannot be expanded on a quarterly horizon — it is gated by a handful of suppliers and multi-year fab and packaging build-outs. Within a given year, one buyer's allocation is largely another's shortfall. **Zero-sum (near term).**
- *Top talent, near term:* **fixed.** The pool of people who have led frontier training runs is small and slow to grow. A senior hire at one lab is, for that cycle, a hire the rival did not get. **Zero-sum (near term).**
- *AI productivity / end-user value:* **not fixed.** Cooperation and innovation expand it — better models, cheaper inference, and new applications enlarge total value created rather than merely reallocating it. One firm shipping a useful AI product does not consume the possibility of another firm shipping one. **Non-zero-sum.**
- *Time dimension:* the fixity of chips and talent is a **near-term** property. Over a multi-year horizon, supply responds — new fab and advanced-packaging capacity comes online and the trained-talent pool grows — so even these resources become less zero-sum the longer the horizon.

**Step 3 (check for zero-sum bias).** The popular "one race, one winner" frame shows all three bias markers on the *productivity* dimension:
-

examples/smoot-hawley-tariff-1930.md

# Method in Action: The Smoot-Hawley Tariff and the Fixed-Pie Fallacy in Trade (1930–1934)

> *Example for the [zero-sum-game](../SKILL.md) skill.*

The Smoot-Hawley Tariff Act of 1930 is the most consequential documented case of zero-sum misdiagnosis in economic policy — a strategy built on the assumption that trade is a fixed pie, executed at national scale, with measurable results.

The implicit diagnosis behind the tariff: imports capture American production and jobs, so every unit of imports blocked is a unit of domestic output gained. On this logic, Congress raised duties on over 20,000 imported goods, and President Hoover signed the act in June 1930 — over a petition signed by more than a thousand economists urging a veto. The economists' objection was precisely a zero-sum objection: trade is mutual gain via comparative advantage, and blocking it destroys value on both sides rather than transferring it.

Running the Diagnosis on the 1930 decision:

**Step 1 (contested resource):** Domestic production and employment in import-competing sectors. Nameable and countable — which is exactly the condition under which zero-sum bias is strongest.

**Step 2 (fixity test):** Fails on all three dimensions. *Cooperation:* trade itself is the cooperative mechanism — specialization by comparative advantage makes total output larger than under autarky, so the "pie" of production is not fixed. *Innovation/technology:* export industries expand when trading partners prosper. *Time:* even if a tariff transfers demand to domestic producers this quarter, retaliation and shrinking foreign incomes cut export demand over the following years.

**Step 3 (bias audit):** All three bias markers present. Countability — imports arrive in visible, countable units at ports, while the diffuse gains from trade do not. Relative-position anchoring — the political debate framed foreign producers' sales as America's losses. Comparative-advantage blindness — the analysis treated a dollar of imports as a dollar of forgone domestic production, ignoring that both sides gain from specialization.

**Step 4/5 (what the wrong diagnosis produced):** Because policymakers treated a non-zero-sum game as zero-sum, they played capture instead of designing for surplus. Trading partners ran the same wrong playbook in reverse: Canada — the largest US trading partner — retaliated with duties targeting US exports, and other countries followed with tariffs, quotas, and preferential blocs. Both moves were individually "rational" under the fixed-pie frame and collectively destructive outside it. Between 1929 and 1933 world trade collapsed to a fraction of its former volume; the Depression drove much of the fall, but as Irwin documents, the tariff and the retaliation it provoked deepened the contraction and fragmented the world trading system into discriminatory blocs. The pie did not get redivided — it shrank for everyone.

**The corrected diagnosis:** The reversal came only when the game was reframe

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