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This project is a Git-based AI session tracker and context manager designed to record AI agent interactions, transcripts, and tool usage directly into Git repositories. It functions as a system for capturing and indexing the reasoning behind code changes, linking AI prompts and responses to specific code commits to preserve developer intent.

The tool distinguishes itself by using Git as a primary storage layer for session metadata, utilizing shadow branches and checkpoints to track agent state without polluting the main commit log. It includes specialized capabilities for auditing AI contributions, allowing users to trace specific lines of code back to the original prompt and verify the ratio of agent versus human authorship.

The software covers a broad surface of capabilities, including automated Git hook management, repository mirroring across different transports, and secret redaction via entropy analysis. It also provides observability tools for visualizing session history in the terminal, managing agent plugin discovery, and restoring session states across different Git worktrees.

Features

Agentic Context Management - Provides a comprehensive system for capturing, indexing, and resuming LLM interaction history linked to specific code commits.

Coding Session Recordings - Captures AI interaction transcripts and model checkpoints to associate developer intent with specific code outcomes.

Semantic Reasoning Layers - Records agent sessions as versioned data within Git to create a semantic reasoning layer.

Commit-Linked Session Indexing - Indexes AI agent prompts and responses by linking them directly to specific Git commits via hooks.

Worktree Isolation - Maintains independent session tracking contexts for different git worktrees to prevent state conflicts.

AI Agent Integrations - Configures hooks for multiple AI agents to capture their respective session data within the development workflow.

AI Session Managers - Manages AI agent interaction history, allowing users to rewind and resume sessions across model providers.

AI Session State Preservation - Preserves reasoning and transcripts for every Git commit to document agent intent and project state.

Session History Retrieval - Retrieves detailed metadata from a snapshot including intent and conversation transcripts.

Code Modification Tracking - Tracks file modifications during agent tasks to produce a clean and meaningful commit history.

Shadow-Branch Checkpointing - Links agent interactions to commits using metadata checkpoints and shadow branches.

Agent Contribution Graphs - Implements an indexed contribution graph to retrieve specific AI prompts and decisions.

Intent-Based Search - Enables searching for the developer intent behind code changes by indexing prompts and agent reasoning.

Agent Session Lifecycles - Translates native session events and logs into a shared lifecycle using adapters for consistent recording.

Shadow-Branch Checkpointing - Writes mid-session checkpoints to hidden branches to allow rewinding without polluting the primary commit log.

Shadow-Branch State Tracking - Writes mid-session checkpoints to shadow branches to enable state rewinds without polluting the main commit log.

Agentic CLI Integrations - Provides native integrations for AI agents to record developer workflows directly via command-line interfaces.

Reasoning-to-Code Tracing - Links codebase diffs to the reasoning and session context that produced them.

Session-to-Commit Linking - Attaches AI sessions to code commits via checkpoints to preserve the research and intent behind changes.

Git-Based AI Session Trackers - Records AI agent transcripts and checkpoints directly into Git repositories to preserve developer intent.

AI Session Metadata Capture - Records transcripts and tool invocation events to provide essential context for code changes.

Prompt-to-Code Linking - Traces individual lines of code back to the original AI prompt and session checkpoint that generated them.

Commit-Linked Metadata - Attaches session details to repository commits using hooks to create a permanent record of the intent behind code changes.

Git-Based Session Storage - Stores session transcripts and agent state as git objects and branches to preserve history across remotes.

Git-Object Session Storage - Uses git objects and shadow branches to store session history across remote repositories.

AI Contribution Attribution - Distinguishes between agent-generated code and human refinements for audit and compliance purposes.

Agentic Session Persistence - Stores agent interaction metadata in a dedicated branch to resume work without repeating prompts.

AI Agent Sessions - Restarts stopped or idle sessions across different worktrees using an interactive session picker.

Commit-Linked Session Indexing - Preserves the link between AI agent sessions and code commits even after git history rewrites.

Git-Based Session Recording - Provides the primary capability of recording AI agent prompts and reasoning directly into Git to preserve developer intent.

Recording Triggers - Automates the recording of coding sessions via hooks for agents and IDE extensions.

AI Assisted Code Auditing - Traces codebase modifications back to original AI agent sessions to verify implementation and understand intent.

AI Contribution Auditors - Traces code changes back to original AI prompts to analyze the ratio of agent versus human authorship.

AI Development Attribution - Distinguishes between human and AI contributions by linking code checkpoints to agent transcripts.

Event Normalization - Translates diverse AI agent event payloads into a standardized internal protocol for consistent session recording.

AI Agent Observability - Links agent transcripts and tool activity to specific code checkpoints and commits for full observability.

AI Session Observability - Creates a searchable history by recording transcripts, token usage, and lifecycle events.

Agent Communication Protocols - Connects external agents via a standardized communication protocol to avoid core codebase changes.

Protocol Mapping - Maps native agent events and transcripts to a standardized protocol using a plugin.

Worktree Session Isolation - Maintains independent session tracking for different Git worktrees to prevent state conflicts.

AI Code Reviewers - Uses AI agents to analyze branch commit history and provide automated quality and security feedback.

Code Explanation - Traces functions or files back to the original session to reveal the underlying purpose.

Session Summaries - Produces markdown summaries of captured session data to recall technical project history.

Session Transcript Parsing - Displays readable user and assistant outputs by parsing transcripts from external AI agents.

Checkpoint Summarizations - Distills checkpoints from a specific branch or time range into a readable overview.

Sensitive Data Redaction - Replaces sensitive patterns in AI transcripts and metadata using regular expressions to prevent data leakage.

State Transfer - Summarizes task progress and discoveries from saved sessions to facilitate context transfer to a new agent.

Technical Decision Indexing - Creates a searchable record of technical decisions and session metadata tied directly to Git commits.

Checkpoint-Based State Restoration - Allows rehydrating the AI agent's execution state from specific checkpoints to resume work.

Branch State Rewinding - Returns a repository to a previous state by rewinding branches or recovering logs.

Checkpoint-Based Indexing - Captures snapshots of code and metadata using partial clones to maintain a clean local history.

Session State Summarizers - Automatically generates high-level summaries of AI session checkpoints at the time of commit.

AI Agent Activity Summaries - Generates concise explanations of agent activity and prompt-response pairs.

Topological Repository Synchronization - Indexes complex repository histories using packfiles and topological sorting for memory efficient data mirroring.

AI Development Session Bundles - Bundles code state, transcripts, and token usage into versioned units linked to repository commits.

AI Attribution Investigation - Combines version control blame with session checkpoints to explain why code was modified.

AI Agent Indexes - Optimizes agentic retrieval by prioritizing definitions and source files over test files.

Agent Session Recovery - Restores the full context and state of AI agents using version control worktrees and event logs after disruptive operations.

Git Hook Managers - Chains and manages custom Git hooks to automate session recording and metadata synchronization.

Repository Mirroring - Synchronizes Git repositories across different transports using SSH or SCP to ensure redundancy.

Partial-Clone Indexing - Indexes code checkpoints using partial clones to maintain a clean local history while tracking file modifications.

Session Context Search - Finds prior work by topic, repository, branch, or author to provide historical context for current sessions.

Session History Visualizations - Displays grouped session cards and checkpoint links tied to commits in a terminal UI.

Unified Session Logs - Displays agent session logs and corresponding code diffs in a single view.

Git Workflow Automation - Automates the recording of development sessions by managing complex Git hooks and repository mirroring.

Checkpoint Signing - Verifies the authenticity of recorded session checkpoints using GPG or SSH signing.

Credential Leak Detection - Scans commits using pattern and entropy detection to identify and redact leaked credentials.

Secret Entropy Detectors - Scans session logs and transcripts using entropy analysis to identify and redact sensitive credentials.

Session Resumption - Restores the latest checkpointed session metadata for a branch to continue an interaction.

Remote Metadata Resumption - Fetches session metadata from a remote source to restore agent state after cloning.

Secret Scanning - Identifies sensitive data using entropy analysis and redacts secrets before they are persisted to Git.

Session History Verifications - Signs checkpoint commits cryptographically to ensure the security and integrity of the agentic history.

Session Message Redactions - Filters secrets from session logs to prevent exposure while preserving the underlying source code.

Git Hook Lifecycle Integrations - Installs absolute binary paths into git hooks to automate the capture of agent intent during commits.

Agent Session Event Capture - Observes prompt submissions and turn completions in real time to preserve context.

Authorship Contribution Tracking - Visualizes the amount of code authored by AI agents versus human contributors.

Code Implementation Auditing - Compares original agent prompts against actual modifications to verify correct implementation.

Agent Transcript Analysis - Extracts prompt summaries and commit messages from transcripts to provide code context.

AI Agent Activity Monitors - Generates a breakdown of token consumption and tool utilization across repositories.

Agentic Code Reviews - Utilizes specialized AI agents to perform automated code reviews and identify issues before pull requests.

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Features

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