balancelab: Instructions file for Codex

AGENTS.md

balancelab AGENTS.md is an instructions file for Codex, OpenCode from sandeep-alluru/balancelab. It costs 455 tokens per session, scanned A, original, MIT.

Project instructions for balancelab, a tool that analyzes game economies for profitable exchange loops. They document the Python modules, data rules, storage, web API, command-line interface, and agent tools.

In plain words
What is it for?
Guide work on economy rules, exploit detection, SQLite storage, reports, command-line commands, the FastAPI web service, and MCP tools.
Why use it?
They provide the architecture and rules an AI coding assistant needs before changing the project.

Instructions file for CodexOpenCode

Written for Codex and OpenCode: the file is AGENTS.md. Also seen: mentions Claude Code.

This is sandeep-alluru/balancelab's own configuration. It tells Codex and OpenCode how to work on balancelab itself, so it is not a mod to install elsewhere. Copy it as a starting point and replace the rules that are about this project. Everything balancelab configures →

Reuse

Borrowing it

Nothing to install: this file belongs to sandeep-alluru/balancelab. 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/sandeep-alluru/balancelab/main/AGENTS.md
Clone the repo
git clone --depth 1 https://github.com/sandeep-alluru/balancelab

Made for: Codex, OpenCode.

Wrote this? Show the measurements

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README.md
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Per session 455 This file is loaded in full into every session.
When invoked 455 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.

ModelPer sessionOnce invoked
Fable 5.1 $0.00455 $0.00455
Opus 5.5 $0.00182 $0.00182
Sonnet 5.5 $0.00091 $0.00091
Haiku 4.5 $0.00046 $0.00046

Measured 1mo ago against content hash 428ca9d9c548, method: parsed. Prices are Anthropic first-party input rates as of 2026-10-07, from the pricing page.

Security

Grade A, and why

balancelab 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 1mo 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 · 45 lines

What it actually says

balancelab — Agent Context

This file describes the project architecture for AI coding assistants (Claude Code, Cursor, Copilot).

What this project does

Adversarial game economy red-team — detect arbitrage exploits in game economies via graph-based analysis.

Module map

src/balancelab/
├── __init__.py       # Public API exports: EconomyRule, EconomyGraph, ExploitFinder, ExploitPath, ExploitReport
├── economy.py        # Core data model: EconomyRule, EconomyGraph, ExploitPath, ExploitReport, ExploitFinder
├── store.py          # SQLite persistence: EconomyStore (save/get/list for rules and reports)
├── report.py         # Output formatters: print_report(), to_json(), to_markdown()
├── cli.py            # Click CLI: add, scan, report, log, status subcommands
├── api.py            # FastAPI server: /rule, /rules, /scan, /reports, /health endpoints
└── mcp_server.py     # MCP server: add_rule, scan_economy, list_reports tools

Key invariants

  • EconomyRule.id is SHA-256[:16] of source_item|target_item|source_qty|target_qty — same rule always same ID
  • ExploitFinder uses Bellman-Ford on log-weight graph: negative cycle = positive gain cycle
  • ExploitFinder.find_exploits() deduplicates by frozenset of path nodes
  • All library code uses rich.console.Console — never print()
  • EconomyStore uses SQLite with upsert (INSERT OR REPLACE)

Testing

make test       # full test suite
make lint       # ruff check + format
make typecheck  # mypy
make smoke      # end-to-end smoke test
make all        # everything

What NOT to change without careful thought

  • EconomyRule.id computation — changing it breaks all stored rules
  • ExploitFinder algorithm — must correctly detect negative cycles
  • EconomyStore schema — requires migration if changed
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.

  1. 1mo ago First seen · 45 lines · 455 tokens per session scan A 428ca9d9c548

Subscribe to this mod's changes

balancelab AGENTS.md is an instructions file published in the GitHub repository sandeep-alluru/balancelab (0 stars, last pushed 2mo ago), licensed MIT. It adds 455 tokens to every session, about $0.0018 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.

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