Borrowing it
Nothing to install: this file belongs to 0xSanei/darwinia. Take a copy, put it at the same path in your own repository, and replace the rules that are about this project with yours.
curl -O https://raw.githubusercontent.com/0xSanei/darwinia/main/AGENTS.mdgit clone --depth 1 https://github.com/0xSanei/darwiniaWrote 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/instructions/0xsanei/darwinia/agents-md)<a href="https://agentmods.dev/instructions/0xsanei/darwinia/agents-md"><img src="https://agentmods.dev/badge/instructions/0xsanei/darwinia/agents-md.svg" alt="Measured on agentmods" height="20"></a>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 | $0.01018 | $0.01018 |
| Opus 5 | $0.00509 | $0.00509 |
| Sonnet 5 | $0.00204 | $0.00204 |
| Haiku 4.5 | $0.00102 | $0.00102 |
Grade A, and why
darwinia 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 8d 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 — 112 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Darwinia — Instructions for AI Agents
This file tells AI agents (Claude Code, Cursor, OpenClaw, etc.) how to use Darwinia.
What Is Darwinia?
An evolutionary trading agent ecosystem. You don't write strategies — you evolve them. Agents with 17-gene DNA compete on real market data, face adversarial attacks, and only the fittest survive to breed.
Quick Commands
# Install
pip install -e ".[dev]"
# Run evolution (default: 50 gens, 50 agents, BTC 1h data)
python -m darwinia evolve
# Custom evolution
python -m darwinia evolve -g 100 -p 80 --arena-start 10
# Test a specific champion against attacks
python -m darwinia arena -c output/champions/champion_gen_0049.json -r 10
# Launch visualization dashboard
python -m darwinia dashboard
# Run tests
pytest tests/ -v
Key Files
| Path | Purpose |
|---|---|
darwinia/core/dna.py |
17-gene DNA definition + crossover/mutation |
darwinia/core/agent.py |
Trading agent that interprets DNA into decisions |
darwinia/core/market.py |
Market data loader (CSV) |
darwinia/evolution/engine.py |
Main evolution loop orchestrator |
darwinia/evolution/fitness.py |
Composite fitness scoring (Sharpe, drawdown, win rate) |
darwinia/evolution/population.py |
Selection + breeding |
darwinia/arena/adversary.py |
6 attack types targeting agent weaknesses |
darwinia/arena/arena.py |
Arena runner, survival scoring |
darwinia/discovery/analyzer.py |
Gene convergence + correlation analysis |
darwinia/chronicle/recorder.py |
JSON snapshot recorder |
darwinia/chronicle/speciation.py |
K-means species clustering |
darwinia/__main__.py |
CLI entry point |
data/btc_1h.csv |
10,946 BTC/USDT 1h candles (2024-01 to 2025-04) |
Common Tasks
"Evolve a trading strategy for BTC"
python -m darwinia evolve -g 50
# Results in output/champions/ and output/evolution_summary.json
"What patterns did the agents discover?"
# After evolution, check:
cat output/final_report.json | python -m json.tool | grep -A5 "patterns_discovered"
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.
- 8d ago First seen · 112 lines · 1,018 tokens per session scan A 2705b884a973
darwinia AGENTS.md is an instructions file published in the GitHub repository 0xSanei/darwinia (87 stars, last pushed 4mo ago), licensed MIT. It adds 1,018 tokens to every session, about $0.0051 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 2026-08-30.
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