Operational continuity for AI coding agents.
AICTX helps Codex, Claude, GitHub Copilot and other coding agents continue work across sessions and across tools by preserving the last useful execution state: active work, next actions, decisions, failures, validation evidence, repo context and quality signals for stale or unverified continuity.
pip install aictx
aictx install
aictx init
# Then just keep using your coding agent.
# Agents handle the lifecycle themselves:
# resume context → work → finalize continuity
Start from what actually happened.
Work State
Active task, hypothesis, relevant files, risks, next action and verification state.
Decisions and handoffs
Project decisions and what the previous session left for the next one.
Failures, validation and quality
Known failed commands, resolved patterns, canonical checks, validation evidence, lifecycle diagnostics and stale-context quality signals.
Disconnected sessions and disconnected agents are the problem.
Coding agents can reason through code, but every new session often starts operationally cold: it has to rediscover the repo, infer the task state, avoid old mistakes and guess which validation matters. Switching from Codex to Claude Code or Copilot should not mean losing the factual project state.
Without AICTX
A new agent session starts cold.
It scans README, docs and Makefile.
It rediscovers decisions.
It may repeat failed commands.
It guesses what should happen next.
With AICTX
The agent loads a resume capsule.
It sees active work and next action.
It sees known failures and validation path.
It finalizes factual evidence for the next session.
One repo memory for multiple coding agents.
AICTX stores continuity in the repository, not inside a single provider's chat history. Codex can finalize
what happened, and Claude Code, GitHub Copilot or another compatible agent can resume from the same
.aictx/ state later.
Codex finalize
→ .aictx continuity
→ Claude Code / GitHub Copilot / generic agent resume
Read shared continuity use case →
Inspectable, local, not hidden.
AICTX stores continuity under .aictx/. It is not cloud memory, not a
vector database and not locked inside one chat. You can inspect it, clean it up, and optionally make
a safe subset portable through Git.
Continuity View
Generate a local Markdown and Mermaid view of current operational continuity.
aictx view --repo .
# writes:
.aictx/reports/continuity-view.md
.aictx/reports/continuity-map.mmd
Local MCP server
Expose continuity as local MCP tools/resources/prompts. Compatible clients can launch it over stdio; CLI fallback remains available.
aictx mcp-server --repo . --profile full
Task Context Pack
Compile bounded read-only context for a specific goal without replacing the resume → work → finalize lifecycle.
aictx prepare "fix the parser bug" --repo . --json
# MCP readonly tool:
# aictx_prepare_task_context
Continuity Quality
Score whether repo-local continuity is fresh, stale, missing, demoted, obsolete or unverified before agents rely on it.
aictx doctor --repo . --json
# also exposed through:
# aictx resume --json
# MCP continuity quality
Simple start. Deep runtime when needed.
User Manual
Practical “I want to…” commands: portability, reports, MCP, cleanup, messages and diagnostics.
Open User Manual →Technical Docs
Full technical reference for Work State, contracts, RepoMap, MCP, plugins, portability and internals.
Browse Technical Docs →Compare continuity approaches
Understand how repo-local continuity differs from instructions, long context, vector memory, and agent-specific harness memory.
Read comparison →Works around the agents you already use.
Claude Code
Project instructions, hooks, MCP support and Claude Code plugin artifacts.
Claude Code continuity →GitHub Copilot
Best-effort repo instructions, prompt files and VS Code MCP config where supported.
Copilot continuity →Shared agent memory
Repo-local continuity lets different agents hand off through the same project state.
Shared continuity →What AICTX is not
AICTX is not an autonomous coding agent, a cloud memory service, a dashboard, a vector database or a replacement for human review.
AICTX does not guarantee correctness, productivity gains, token savings or that every agent will follow the lifecycle perfectly.