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Repo-native runtime contract and context bootstrapper for coding agents

Project description

aictx

Install once. Initialize a repo. Give coding agents a real runtime contract.

aictx turns a normal repository into a repository that is prepared for coding agents.

Product surface

The sellable user flow stays intentionally small:

  1. aictx install
  2. aictx init
  3. use Codex, Claude Code, or your normal automation

Everything else exists to support that runtime, not to expand the primary UX.

What it really does today

After install + init, aictx can provide:

  • repo-local bootstrap memory under .ai_context_engine/
  • packet-oriented context for non-trivial work
  • task memory, failure memory, and memory graph scaffolds
  • repo-native instruction integration for Codex and Claude Code
  • wrapped middleware for generic automation via aictx internal run-execution
  • local/global telemetry and health artifacts

Honest limits

This is still a 0.x beta product.

  • final behavior depends on each runner honoring its instruction and hook system
  • telemetry quality is best-effort unless confidence is explicitly high
  • advanced/internal commands are supported, but not the main thing being sold
  • some deeper capabilities are still being extracted from the canonical engine

See docs/LIMITATIONS.md.

Install from PyPI

pip install aictx

Then:

aictx install
aictx init --repo .

Install once

aictx install

Non-interactive:

aictx install --yes --workspace-root ~/projects

This creates the global runtime under ~/.ai_context_engine/ and provisions:

  • global configuration
  • workspace registry
  • adapters and wrappers
  • global telemetry storage
  • global Codex instructions

Initialize a repo

aictx init

Non-interactive:

aictx init --repo . --yes

init creates:

  • .ai_context_engine/memory/
  • .ai_context_engine/cost/
  • .ai_context_engine/task_memory/
  • .ai_context_engine/failure_memory/
  • .ai_context_engine/memory_graph/
  • .ai_context_engine/library/
  • .ai_context_engine/metrics/
  • .ai_context_engine/adapters/
  • .ai_context_engine/state.json
  • .ai_context_engine/agent_runtime.md

And native repo integration files:

  • AGENTS.md
  • AGENTS.override.md
  • CLAUDE.md
  • .claude/settings.json
  • .claude/hooks/...
  • .gitignore

Runtime consistency

aictx boot --repo <path> and aictx execution prepare ... now expose:

  • effective communication policy
  • communication source precedence
  • runtime consistency checks between repo preferences and repo state

Precedence is:

explicit user instruction > repo prefs > global defaults > hardcoded fallback

Public beta posture

aictx is now distributed publicly as a beta 0.x package.

  • installation is supported through PyPI and GitHub releases
  • the core user flow is pip install aictx -> aictx install -> aictx init
  • compatibility is still best-effort, not a long-term 1.0 stability promise

Development quickstart

python3 -m venv .venv
.venv/bin/pip install --upgrade pip
.venv/bin/pip install -e . pytest build
make test
make smoke
make package-check

You can also call the installed script directly:

.venv/bin/aictx --help

Public release validation also checks clean wheel installation, not just editable installs.

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