Agent Bazaar Implementation — Development skill for Claude Code


Agent Bazaar

Implementation of Agent Bazaar: Enabling Economic Alignment in Multi-Agent Marketplaces, by Karten, Crow & Jin, in Swarms primitives.

The paper isolates two systemic failure modes that emerge when LLM agents run storefronts on behalf of humans, and shows that these failures are *orthogonal to general reasoning capability* — a more capable model is not necessarily more economically aligned. Two market-aligned harnesses (`StabilizingFirm` and `SkepticalGuardian`) are provided as drop-in policies that mitigate each failure mode.

A single number — the **Economic Alignment Score** (EAS, paper Eq. 5) — collapses four sub-scores (`S_stab`, `S_integ`, `S_welf`, `S_prof`) into a scalar in `[0, 1]`, so 20+ models can be ranked on one chart.

**We're hiring.** [swarms.ai](https://swarms.ai) is hiring **multi-agent researchers** to join our research team and work on **multi-agent scaling laws** — how collective behavior, coordination, and economic alignment scale with agent count, model size, and training compute. If problems like the ones in this repo are what you want to spend your days on, reach out at [kye@swarms.world](mailto:kye@swarms.world).

Install

git clone https://github.com/The-Swarm-Corporation/agent-bazaar-implementation
cd agent-bazaar-implementation
pip install -r requirements.txt

Environment variables

Swarms calls models through LiteLLM, which reads provider credentials from environment variables. Copy `.env.example` to `.env` and fill in the keys for the providers you plan to use.

$ cp .env.example .env

The paper evaluates three frontier models — set keys for whichever you want to drive:

Provider	Env var	Paper model	LiteLLM string
Anthropic	`ANTHROPI