When is the best time to update the ledger?

You should update the ledger before running a /clear command, when context usage exceeds 70%, after major architectural decisions, or at natural session breakpoints.

Why use a ledger instead of context compaction?

Context compaction is lossy and leads to degraded understanding over time. A ledger allows for a full context clear, providing the AI with a fresh start while retaining 100% signal on critical project state.

Where are the ledger files stored in my project?

Ledger files are stored in the 'thoughts/ledgers/' directory, using a naming convention that includes the session name for easy identification and retrieval.

How does this differ from a standard handoff file?

While handoffs are generally used for transferring work between different users or major sessions, ledgers are optimized for intra-session continuity and high-frequency state updates.

Continuity Ledger

Name: Continuity Ledger
Author: wildcard

bywildcard

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Productivity & Workflow

Manages a session-specific state file to preserve critical context and project goals across AI context clears.

About

The Continuity Ledger skill provides a structured framework for managing long-running AI coding sessions by maintaining a persistent ledger file. Instead of relying on lossy context compaction, users can perform a full context reset and reload the ledger to maintain high-fidelity state, goals, and decisions. This ensures that complex refactors or multi-day tasks remain on track with fresh context and clear priorities without losing the thread of the implementation or suffering from degraded AI performance.

Key Features

Persistent state preservation that survives context clears and restarts
Recovery protocols to validate assumptions after a context reset
Standardized ledger templates for tracking goals, constraints, and decisions
23 GitHub stars
Done/Now/Next task prioritization to maintain development focus
Working set tracking for active files, branches, and test commands

Use Cases

Managing complex, multi-file refactors that exceed standard context limits
Preventing AI context degradation by enabling clean resets with full signal
Preserving progress and state during multi-day development sessions

About

Key Features

Persistent state preservation that survives context clears and restarts
Recovery protocols to validate assumptions after a context reset
Standardized ledger templates for tracking goals, constraints, and decisions
23 GitHub stars
Done/Now/Next task prioritization to maintain development focus
Working set tracking for active files, branches, and test commands

Use Cases

Managing complex, multi-file refactors that exceed standard context limits
Preventing AI context degradation by enabling clean resets with full signal
Preserving progress and state during multi-day development sessions