agentbible 0.1.1

Production-grade infrastructure for AI-assisted research software

AgentBible

Production-grade infrastructure for AI-assisted research software.

AgentBible provides physics validation decorators, project scaffolding, provenance tracking, and testing utilities for scientific Python projects.

Installation

pip install agentbible

# With HDF5 provenance support
pip install agentbible[hdf5]

# Full development install
pip install agentbible[all]

Quick Start

Create a New Project

bible init my-quantum-sim --template python-scientific
cd my-quantum-sim
source .venv/bin/activate
pip install -e ".[dev]"
pytest  # 28 tests pass immediately

Use Physics Validators

from agentbible import validate_unitary, validate_density_matrix
import numpy as np

@validate_unitary
def create_hadamard():
    """Returns Hadamard gate - validated as unitary."""
    return np.array([[1, 1], [1, -1]], dtype=complex) / np.sqrt(2)

@validate_density_matrix
def create_mixed_state():
    """Returns maximally mixed state - validated as density matrix."""
    return np.eye(2, dtype=complex) / 2

# Validation happens automatically on return
H = create_hadamard()      # OK - unitary
rho = create_mixed_state() # OK - trace=1, Hermitian, positive semi-definite

Validate Data Files

# Validate a numpy matrix
bible validate state.npy --check unitarity

# Validate HDF5 with all checks
bible validate results.h5 --check all

# Multiple specific checks
bible validate matrix.npy -c hermiticity -c trace -c positivity

Save Data with Provenance

from agentbible.provenance import save_with_metadata, load_with_metadata
import numpy as np

# Save with full reproducibility metadata
save_with_metadata(
    "results.h5",
    {"density_matrix": rho, "eigenvalues": np.linalg.eigvalsh(rho)},
    description="Ground state calculation",
)

# Load with metadata
data, metadata = load_with_metadata("results.h5")
print(metadata["git_sha"])      # "a1b2c3d..."
print(metadata["timestamp"])    # "2026-01-01T12:00:00+00:00"
print(metadata["packages"])     # {"numpy": "1.26.0", ...}

Physics-Aware Testing

from agentbible.testing import physics_test, deterministic_seed
import numpy as np

@physics_test(checks=["unitarity", "hermiticity"])
def test_pauli_x():
    """Automatically validates return value."""
    return np.array([[0, 1], [1, 0]], dtype=complex)

def test_reproducible(deterministic_seed):
    """Seeds are set to 42 for reproducibility."""
    random_value = np.random.rand()
    assert random_value == 0.3745401188473625  # Always the same

Features

Validators

Decorator	Validates
@validate_unitary	U @ U.H = I
@validate_hermitian	A = A.H
@validate_density_matrix	Hermitian, trace=1, positive semi-definite
@validate_probability	Value in [0, 1]
@validate_probabilities	Array of probabilities
@validate_normalized	Sum or norm = 1
@validate_positive	Value > 0
@validate_non_negative	Value >= 0
@validate_range(min, max)	Value in [min, max]
@validate_finite	No NaN or Inf

CLI Commands

bible init <name>           # Create project from template
bible validate <file>       # Validate physics constraints
bible context               # Generate AI context
bible info                  # Show installation info

Provenance Metadata

save_with_metadata() automatically captures:

• Git SHA, branch, dirty status
• UTC timestamp
• Random seeds (numpy, python, torch)
• Hostname, platform, Python version
• Package versions (numpy, scipy, h5py, torch, etc.)

Testing Fixtures

Fixture	Purpose
deterministic_seed	Sets numpy/random to seed 42
tolerance	Returns {"rtol": 1e-10, "atol": 1e-12}
quantum_tolerance	Returns {"rtol": 1e-6, "atol": 1e-8}

Project Templates

Python Scientific (python-scientific)

Pre-configured with:

• ruff for linting (strict rules)
• mypy in strict mode
• pytest with 70% coverage minimum
• Physics validation helpers
• .cursorrules for AI agents

bible init my-project --template python-scientific

C++ HPC/CUDA (cpp-hpc-cuda)

Pre-configured with:

• CMake with zero-warning policy
• GoogleTest for testing
• CUDA support (optional)
• Physical validation functions

bible init my-project --template cpp-hpc-cuda

The 5 Principles

1. Correctness First — Physical accuracy is non-negotiable
2. Specification Before Code — Tests define the contract
3. Fail Fast with Clarity — Validate inputs, descriptive errors
4. Simplicity by Design — Functions ≤50 lines, single responsibility
5. Infrastructure Enables Speed — CI, tests, linting from day one

Development

# Clone and setup
git clone https://github.com/rylanmalarchick/research-code-principles
cd research-code-principles
./bootstrap.sh

# Or manually
python -m venv .venv
source .venv/bin/activate
pip install -e ".[dev,hdf5]"

# Run tests
pytest tests/ -v

# Lint and type check
ruff check agentbible/
mypy agentbible/

Documentation

Full documentation: rylanmalarchick.github.io/research-code-principles

• Getting Started
• Validators Guide
• Provenance Guide
• API Reference
• Philosophy — Why good code matters
• Style Guide — Coding conventions
• Agent Prompts — Modular AI context snippets
• CHANGELOG — Release history
• SECURITY — Security policy

License

MIT — Use and adapt freely.

Author

Rylan Malarchick — [e-mail]

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v0.1.1 — Documentation site, Dependabot, C++ template (January 2026)