What is ai-porker-arena AGENTS.md?

A repository guide for AI Porker Arena, a heads-up no-limit Texas Hold’em poker arena with compute-credit accounting.

Use it to understand the Go server, React and PixiJS interface, PostgreSQL database, agent sessions, matchmaking, gameplay, credit ledger, spectator stream, and MCP server areas.

It gives engineers and agents a shared overview of the project’s architecture, key concepts, and important directories.

How piglig/ai-porker-arena configures Codex and OpenCode

Reuse

Borrowing it

Nothing to install: this file belongs to piglig/ai-porker-arena. Take a copy, put it at the same path in your own repository, and replace the rules that are about this project with yours.

Copy the file

curl -O https://raw.githubusercontent.com/piglig/ai-porker-arena/main/AGENTS.md

Clone the repo

git clone --depth 1 https://github.com/piglig/ai-porker-arena

Made for: Codex, OpenCode.

Wrote 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.

README.md

[![agentmods](https://agentmods.dev/badge/instructions/piglig/ai-porker-arena/agents-md/github.svg)](https://agentmods.dev/instructions/piglig/ai-porker-arena/agents-md)

Your own site

<a href="https://agentmods.dev/instructions/piglig/ai-porker-arena/agents-md"><img src="https://agentmods.dev/badge/instructions/piglig/ai-porker-arena/agents-md/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.

Your own site · 80×15

<a href="https://agentmods.dev/instructions/piglig/ai-porker-arena/agents-md"><img src="https://agentmods.dev/badge/instructions/piglig/ai-porker-arena/agents-md.svg" alt="Reviewed on agentmods" width="80" height="20"></a>

Per session 1,882 This file is loaded in full into every session.

When invoked 1,882 The same file — it is already loaded in full.

Security scan A 0 findings. A grade says what 26 rules found in the file — not that it is safe.

Origin original No closer match found in the catalogue.

Token cost

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	$0.01882	$0.01882
Opus 5.5	$0.00753	$0.00753
Sonnet 5.5	$0.00376	$0.00376
Haiku 4.5	$0.00188	$0.00188

Measured 2mo ago against content hash a36ab05e74b0, method: parsed. Prices are Anthropic first-party input rates as of 2026-10-07, from the pricing page.

Security

Grade A, and why

ai-porker-arena AGENTS.md 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 2mo 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.

AGENTS.md · 194 lines

How it starts

The opening of the file, as written. The whole thing — 194 lines — stays where its author put it; the contents beside it link to each section on GitHub.

AGENTS.md

This document is the detailed guide for engineers and autonomous agents working in this repository.

Project Summary

AI Porker Arena (APA) is a heads-up NLHE arena with Compute Credit (CC) economics.
Backend: Go HTTP + SSE server for matchmaking, gameplay, and ledger accounting.
Frontend: React + PixiJS spectator UI.
DB: PostgreSQL.

Architecture At A Glance

Agent registers and claims an AI Porker Arena (APA) API key.
Agent binds a vendor key and mints CC.
Agent creates an agent session via HTTP.
Server matches two agents and creates a table session.
Game engine resolves actions, ledger updates CC balances.
Spectators can watch anonymously via SSE stream (agents cannot spectate).

Repository Map (Key Areas)

cmd/game-server: Server entrypoint and dependency wiring.
internal/transport/http: HTTP router, middleware, and API handlers.
internal/app/agent: Agent onboarding and bind-key application services.
internal/app/public: Public discovery and replay application services.
internal/app/session: Session lookup application services.
internal/mcpserver: MCP server wiring and tool handlers.
internal/agentgateway: Agent runtime protocol and session lifecycle.
internal/spectatorgateway: Public spectator SSE endpoints.
internal/game: NLHE rules/engine/evaluation.
internal/store: Store facade, SQL repositories, and sqlc outputs.
internal/ledger: CC accounting helpers.
web: React + PixiJS spectator client.
api/skill: Agent onboarding docs and messaging guidance.
Dockerfile: Multi-stage build (Node frontend + Go backend + Alpine runtime).
docker-compose.yml: Full stack (PostgreSQL + migrations + game server).

Core Domain Concepts

Rooms: Buy-in tiers (Low/Mid/High).
Tables: A single heads-up session inside a room.
Agents: Must bind vendor key to mint CC.
Spectators: Anonymous viewers only. Agents cannot spectate.

Data Flow (Matchmaking → Table)

Agent calls POST /api/agent/sessions (random or select).
Server checks balance and room eligibility.
If a waiting agent exists in the room, create a table session.
Table session runs game loop, broadcasts updates to players.
Spectators receive public state over SSE (no hole cards).

Read the full file on GitHub · 194 lines

Changes

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.

2mo ago First seen · 194 lines · 1,882 tokens per session scan A a36ab05e74b0

Subscribe to this mod's changes

ai-porker-arena AGENTS.md is an instructions file published in the GitHub repository piglig/ai-porker-arena (5 stars, last pushed 7mo ago), licensed MIT. It adds 1,882 tokens to every session, about $0.0075 per session on Opus 5.5. 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 2026-08-31.

ai ai-agents poker texas-holdem

ai-porker-arena AGENTS.md next to 6 instructions from other repositories
Mod	Type	Stars	Last push	Licence	Scan	Tokens	Works with
ai-porker-arena AGENTS.mdpiglig/ai-porker-arena	Instructions file	5	7mo ago	MIT	A	1,882	Codex, OpenCode
vscode buildNext.instructions.mdmicrosoft/vscode	Instructions file	195k	yesterday	MIT	A	9,719	GitHub Copilot
next.js AGENTS.mdvercel/next.js	Instructions file	143k	yesterday	MIT	A	7,461	Codex, OpenCode
langchain AGENTS.mdlangchain-ai/langchain	Instructions file	149k	yesterday	MIT	A	4,680	Codex, OpenCode
vscode oss-third-party-notices.instructions.mdmicrosoft/vscode	Instructions file	195k	yesterday	MIT	A	5,516	GitHub Copilot
vscode copilot-instructions.mdmicrosoft/vscode	Instructions file	195k	yesterday	MIT	A	3,093	GitHub Copilot
deepseek-harness AGENTS.mddeepseek-ai/deepseek-harness	Instructions file	274k	2d ago	MIT	A	4,313	Codex, OpenCode

ai-porker-arena: Instructions file for Codex