AI-agent-native VCS MVP
Project description
ait
ait is an AI-agent-native version control layer on top of Git.
The MVP tracks:
- structured intents
- isolated attempts in Git worktrees
- daemon-ingested tool events from agent harnesses
- queryable evidence, file access, and commit linkage
- verification, promote, discard, and rebase flows
Status
This repository is at 0.5.3 alpha quality for local dogfood use. It is
local-only: metadata lives in .ait/ inside one Git repository and is
intentionally not synchronized across machines.
Requirements
- Python 3.14+
- Git
- SQLite from the Python standard library
Install For Development
From the repository root:
python3.14 -m venv .venv
.venv/bin/pip install -e .
.venv/bin/pip install pytest
Verify:
.venv/bin/pytest -q
.venv/bin/ait --version
.venv/bin/ait --help
Install From GitHub
Install the tagged release with pipx:
pipx install "git+https://github.com/m24927605/ait.git@v0.5.3"
Or install into a virtual environment:
python3.14 -m venv .venv
.venv/bin/pip install "git+https://github.com/m24927605/ait.git@v0.5.3"
.venv/bin/ait --help
Install From PyPI
The PyPI distribution name is ait-vcs because the shorter ait name
is already owned by another project. The installed command is still
ait.
pip install ait-vcs
ait --version
ait --help
Or inside a virtual environment:
python3.14 -m venv .venv
.venv/bin/pip install ait-vcs
.venv/bin/ait --version
.venv/bin/ait --help
Quickstart
Initialize ait metadata in a Git repository:
ait init
Create an intent and attempt:
ait intent new "Fix auth expiry" --kind bugfix
ait attempt new <intent-id> --agent-id cli:human
The attempt command prints:
attempt_idworkspace_refbase_ref_oidownership_token
Make changes in the attempt worktree, then commit through ait:
cd <workspace_ref>
# edit files
git add <files>
cd <repo-root>
ait attempt commit <attempt-id> -m "fix auth expiry"
Promote the attempt:
ait attempt promote <attempt-id> --to main
If main advanced while the attempt was running:
ait attempt rebase <attempt-id> --onto main
ait attempt promote <attempt-id> --to main
Inspect state:
ait attempt show <attempt-id>
ait intent show <intent-id>
ait context <intent-id>
ait attempt list --verified-status succeeded
ait query --on attempt 'observed.tool_calls>0'
ait blame path/to/file.py
Daemon And Harness
Start the daemon:
ait daemon start
ait daemon status
The harness API streams lifecycle and tool events to the daemon:
python examples/harness_demo.py <attempt-id> <ownership-token> .ait/daemon.sock
After the demo:
ait attempt show <attempt-id>
Expected counters include tool calls, reads, writes, commands, and file
evidence under files.read and files.touched.
Universal Agent Runner
ait run wraps any CLI-based agent or command in an ait intent and
attempt. It creates an isolated attempt worktree, starts the daemon,
runs the command in that worktree, records the command event, and marks
the attempt finished with the command exit code.
ait run --agent shell:local --intent "Try a generated change" -- \
python -c "from pathlib import Path; Path('agent.txt').write_text('ok\n')"
The wrapped process receives:
AIT_INTENT_ID
AIT_ATTEMPT_ID
AIT_WORKSPACE_REF
Examples:
ait run --agent aider:main --intent "Fix auth expiry" -- aider src/auth.py
ait run --agent claude-code:manual --intent "Refactor query parser" -- claude
This is the shallow universal integration layer. Deeper adapters can add
native file-read/write events through hooks, but ait run already gives
session lifecycle, worktree isolation, exit-code verification, and
command provenance for any shell-launchable agent.
Use --adapter to select agent-specific defaults:
ait run --adapter shell --intent "Run local command" -- python script.py
ait run --adapter claude-code --intent "Refactor query parser" -- claude
ait run --adapter aider --intent "Fix auth expiry" -- aider src/auth.py
ait run --adapter codex --intent "Implement parser" -- codex
Adapters define the default agent_id, whether context is enabled by
default, and adapter-specific environment variables. --agent remains
available as an override.
Inspect adapter capabilities:
ait adapter list
ait adapter list --format json
ait adapter show claude-code
ait adapter show claude-code --format json
ait adapter doctor claude-code
ait adapter doctor claude-code --format json
ait adapter setup claude-code --print
The Claude Code doctor checks that the packaged hook script and settings sample are available after installation, so native hook setup can be generated without relying on a source checkout.
Add --with-context to write a compact agent-readable context file into
the attempt worktree and expose it as AIT_CONTEXT_FILE:
ait run --with-context --agent shell:local --intent "Continue previous work" -- \
python -c "import os; print(open(os.environ['AIT_CONTEXT_FILE']).read())"
Integration Guide
Most AI agent workflows should start with ait run. It works with any
CLI that can be launched from a shell, and it gives the agent an
isolated Git worktree plus these environment variables:
AIT_INTENT_ID
AIT_ATTEMPT_ID
AIT_WORKSPACE_REF
When context is enabled, ait run also writes .ait-context.md into the
attempt worktree and exposes its path as AIT_CONTEXT_FILE.
Use the generic shell adapter for scripts, one-off commands, and custom automation:
ait run --adapter shell --intent "Regenerate fixtures" -- \
python scripts/regenerate_fixtures.py
Use the Claude Code adapter when launching Claude from a repository. It
enables context by default, so Claude can read AIT_CONTEXT_FILE before
editing:
ait run --adapter claude-code --intent "Refactor query parser" -- claude
To make Claude edit an isolated attempt worktree and commit the result:
ait run --adapter claude-code \
--intent "Update README" \
--commit-message "update README with Claude" \
-- claude -p --permission-mode bypassPermissions \
'Append exactly this line to README.md: ait run worktree smoke ok'
The root checkout is unchanged until the attempt is promoted. Promote the resulting attempt after reviewing it:
ait attempt show <attempt-id>
ait attempt promote <attempt-id> --to main
See docs/claude-code-run-worktree.md for the live smoke workflow.
For deeper Claude Code event capture, install the native hook example after checking readiness:
ait adapter doctor claude-code
ait adapter setup claude-code
The hook bridge records Claude Code tool events such as file reads,
edits, and shell commands. It is optional: ait run --adapter claude-code is the simpler first integration, while hooks add richer
provenance for teams that want tool-level evidence.
Use the Codex and Aider adapters the same way:
ait run --adapter codex --intent "Implement parser edge cases" -- codex
ait run --adapter aider --intent "Fix auth expiry" -- aider src/auth.py
These adapters currently provide worktree isolation, context handoff, command provenance, and exit-code verification. Native tool-level hooks for Codex and Aider are not implemented yet.
For a custom workflow, either wrap the command with ait run or call
the Python harness API directly from your agent runner:
from ait.harness import AitHarness
with AitHarness.open(
attempt_id=attempt_id,
ownership_token=ownership_token,
socket_path=".ait/daemon.sock",
agent={
"agent_id": "my-agent:worker",
"harness": "my-agent",
"harness_version": "0.1",
},
) as harness:
harness.record_tool(
tool_name="Edit",
category="write",
duration_ms=120,
success=True,
files=[{"path": "src/app.py", "access": "write"}],
)
harness.finish(exit_code=0)
Choose the integration depth by how much evidence you need:
ait run: lifecycle, isolated worktree, command event, exit codeait run --with-context: adds compact handoff context- native hooks: adds per-tool read/write/command evidence
- harness API: full custom event capture from an agent runner
Agent Context
ait context <intent-id> summarizes the intent, prior attempts, files,
commits, observed tool counters, and simple recommendations:
ait context <intent-id>
ait context <intent-id> --format json
This gives the next agent a short handoff instead of requiring a full chat transcript or repeated repository exploration.
Claude Code Hook Example
ait adapter setup claude-code installs a conservative Claude Code hook
bridge into the current repository at:
.ait/adapters/claude-code/claude_code_hook.py
It also merges the hook configuration into:
.claude/settings.json
Use --print to inspect the generated settings without writing files,
or --target to write a different settings path:
ait adapter setup claude-code --print
ait adapter setup claude-code --target .claude/settings.json
The installed hook creates one ait intent and attempt per Claude
session, streams PostToolUse / PostToolUseFailure events through
AitHarness, sends a heartbeat on Stop, and finishes the attempt on
SessionEnd.
examples/claude_code_hook.py is the source version of the same hook.
Example settings are in:
examples/claude-code-settings.json
The hook expects ait to be importable by the Python interpreter used in
the command, so run it from an installed development environment.
The packaged hook path installed by ait adapter setup claude-code is
covered by an end-to-end regression test that simulates Claude Code
SessionStart, PostToolUse, and SessionEnd payloads and verifies
that ait records the attempt and tool evidence. A live Claude Code smoke
test with Claude Code 2.1.119 also verified real hook payloads record
ait attempts and tool evidence; see docs/claude-code-live-smoke.md.
Current limitation: the hook records provenance, but it does not force Claude Code to edit inside the ait attempt worktree. The SessionStart hook returns the attempt workspace path as additional context. A deeper integration can use Claude Code's worktree hook path or a wrapper command to make the ait worktree the actual execution directory.
Release Checks
Before cutting a release:
git status --short
.venv/bin/pytest -q
Clean clone smoke test:
tmpdir="$(mktemp -d)"
git clone https://github.com/m24927605/ait.git "$tmpdir/ait"
cd "$tmpdir/ait"
git checkout v0.5.3
python3.14 -m venv .venv
.venv/bin/pip install -e . pytest
.venv/bin/pytest -q
.venv/bin/ait --version
.venv/bin/ait --help
The release candidate should have:
- clean working tree
- passing tests
- dogfood notes updated
- changelog updated
- version in
pyproject.tomlmatching the tag
PyPI publishing uses Trusted Publishing from GitHub Actions. Configure
the PyPI ait-vcs project with these publisher values before relying on
automatic release uploads:
- owner:
m24927605 - repository:
ait - workflow:
publish.yml - environment:
pypi
Manual upload remains available from the repository root:
.venv/bin/python -m build
.venv/bin/python -m twine upload dist/*
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