binarybyte 0.3.2

Infrastructure layer for AI coding agents — evaluate, sync, and deploy agent configs across tools.

BinaryByte

BinaryByte is CI/CD for AI coding agents: evaluate agent-proposed diffs, version shared agent state, and deploy verified rules to multiple targets (Cursor, Gemini CLI, Claude Code, Windsurf, Copilot, plus plugins).

Current version: 0.3.0

---

Why BinaryByte

When you switch between editors and agents, rules and context drift. It’s also easy to merge risky diffs.

BinaryByte gives you:

• Eval — run checks on a patch file or a git diff range; write a verdict + a state snapshot per version label.
• State — keep one canonical state.yaml (memory + conventions) that can be deployed everywhere.
• Deploy (gated) — render that state into each tool’s native file format only if the chosen version’s verdict passed.

---

Quickstart (60 seconds)

pip install binarybyte
binarybyte init .
binarybyte state add --key "stack" --value "Python 3.11, pytest"
binarybyte eval run --git-range HEAD~1..HEAD --version demo-1
binarybyte deploy run --version demo-1

---

Install

pip install binarybyte
binarybyte --version

Optional extras:

• pip install "binarybyte[sandbox]" (Docker-based sandbox eval)
• pip install "binarybyte[all]"

From source (development):

git clone https://github.com/Aryannovice/BinaryByte.git
cd BinaryByte
pip install -e ".[dev]"
pytest
ruff check .

Sandbox evaluation uses the Docker CLI when enabled in config.

---

CLI commands (quick reference)

Global help:

binarybyte --help
binarybyte state --help
binarybyte eval --help
binarybyte deploy --help

Setup:

• Create .binarybyte/: binarybyte init (or binarybyte init path/to/project)

State:

• Add memory: binarybyte state add --key K --value "V" [--source manual]
• List entries: binarybyte state list
• List snapshots: binarybyte state snapshots
• Compare snapshots: binarybyte state diff --from v1 --to v2
• Restore state from snapshot: binarybyte state rollback --version v1 (or --version last-passed)

Eval:

• Evaluate a patch file: binarybyte eval run --diff changes.patch [--version v1]
• Evaluate a git range: binarybyte eval run --git-range HEAD~1..HEAD [--version v1]

Deploy:

• Deploy current state (defaults to latest verdict): binarybyte deploy run [--version latest|v1]
• Deploy from a previous snapshot: binarybyte deploy rollback --version v1 (or --version last-passed)
• Show deploy history: binarybyte deploy history
• List available targets (built-ins + plugins): binarybyte deploy targets

---

Use in CI

BinaryByte is CI-friendly: binarybyte eval run exits non-zero when the verdict fails, so it can gate merges/releases.

Example:

binarybyte init .
binarybyte eval run --git-range "$BASE_SHA...$HEAD_SHA" --version "pr-123"

---

What gets written on disk

After init, BinaryByte writes per project:

.binarybyte/
  config.yaml
  state.yaml
  results/<version>/verdict.json
  results/<version>/state_snapshot.yaml
  deploy_log.json
  plugins/*.py
  checks/*.py

---

Deploy targets

Built-in deploy targets (when listed in agents.targets in .binarybyte/config.yaml):

Target id	Output
cursor	.cursor/rules/binarybyte.mdc
gemini-cli	GEMINI.md
claude-code	CLAUDE.md
windsurf	.windsurfrules
copilot	.github/copilot-instructions.md

See the config template in examples/sample-config.yaml.

---

Built-in evaluation (summary)

• Safety — denied command patterns + denied paths + optional secret scanning.
• Imports — flags new third-party imports that don’t resolve.
• Secrets — scans added lines for API-key-like patterns (configurable).
• Plugins — add custom checks under .binarybyte/checks/.
• Sandbox (optional) — run commands in a Docker container against a temp project copy with the patch applied.

---

Plugins

Deploy adapters:

• Drop Python files into .binarybyte/plugins/ that subclass BaseAdapter.
• See examples/plugin_example.py.

Eval checks:

• Add Python files under .binarybyte/checks/ exposing check(diff_text, config) -> CheckResult.

---

Extending to new tools

Agent tools change frequently. BinaryByte is designed so new targets can be added without changing the core package.

The recommended approach is:

1. Add a deploy adapter as a project-local plugin under .binarybyte/plugins/.
2. Add its NAME to agents.targets in .binarybyte/config.yaml.

See examples/plugin_example.py for a working adapter template.

Requesting a new built-in target

If you want BinaryByte to support a new tool out of the box, open an issue with:

• Tool name + website/docs link
• Exact output file path(s) it expects
• Required format (Markdown/YAML/JSON) and a minimal example
• Any constraints (max size, headings, frontmatter, etc.)

We usually start by shipping it as a plugin adapter first, then promote it to a built-in target once it’s stable.

---

Releasing (maintainers)

1. Bump the version in pyproject.toml.
2. Tag and push vX.Y.Z.
3. GitHub Actions builds, validates (twine check), and publishes to PyPI via OIDC (Trusted Publishing).

---

Contributing

Contributions are welcome—new adapters, new checks, docs, and examples.

• Run pytest -q and ruff check . before opening a PR.
• Keep PRs focused and add tests where practical.

See CONTRIBUTING.md for the full dev workflow.

---

License

MIT — see LICENSE.