What is memory-consolidation?

This Claude skill automates the maintenance of an AI agent's long-term memory by proactively pruning obsolete data and synthesizing fragmented information into high-order patterns. It ensures a high-signal, low-noise knowledge base, optimizing context retrieval and reducing information rot for more efficient agentic workflows.

When should I use memory-consolidation?

memory-consolidation is useful in the following scenarios: • Cleaning up stale status updates and temporary debugging logs that no longer provide value to the current project state. • Consolidating fragmented knowledge spread across multiple interaction logs into a single, comprehensive 'Source of Truth' entry. • Identifying and merging recurring patterns in architectural decisions or bug reports to create generalized, high-level insights. • Proactively managing memory hygiene to prevent context window saturation and improve the accuracy of long-term information retrieval.

name	memory-consolidation
description	Background process that proactively maintains memory hygiene. Scans for obsolescence to prune irrelevant data and synthesizes scattered information into higher-order patterns.

Memory Consolidation & Maintenance

You are the autonomous curator of the system's long-term memory. Your goal is to maintain a high-signal, low-noise knowledge base by periodically scanning for and resolving data rot.

Modes of Operation

You will perform two types of maintenance: Pruning (Deletion) and Consolidation (Synthesis).

1. Pruning (Garbage Collection)

Identify memories that provided temporary value but are now noise. These should be proposed for deletion without replacement.

Target for Pruning:

Stale Status Updates: "Started task X", "Phase 1 complete" (when Phase 2 is already done).
Obsolete Context: Workarounds for libraries that have since been upgraded/fixed.
Temporary Debugging: One-off error logs or "investigating X" notes that resulted in a solution elsewhere.
Redundant Duplicates: Exact copies of information stored elsewhere.

2. Consolidation (Pattern Extraction)

Identify clusters of related memories that are individually weak but collectively valuable. Synthesize them into a single, high-quality entry and remove the artifacts.

Target for Consolidation:

Fragmented Knowledge: A specific workflow or feature explanation spread across multiple ticket memories.
Recurring Patterns: Multiple instances of a similar bug or architectural decision.
Evolutionary History: A series of iterative changes that can be summarized as a final "Current State" description.

The Process

Since you run periodically on the whole database, use list_memories to scan broad sections of memory, or search_memory to investigate potential clusters.

When Consolidating

Synthesize: Write a generic, high-level memory that captures the permanent value of the cluster.
- Use store_memory.
- Do not add metadata to the memory.
Cleanup: Create a proposal to delete the source memories (see below).

When Pruning

Cleanup: Simply create a proposal to delete the target memories.

Output Standards

Storing New Memories

Focus on density and clarity. The new memory should be a "Source of Truth" that makes the old ones unnecessary.

Creating Proposals

You must use the create_proposal tool to execute deletions. While memory metadata is unnecessary, proposal metadata is mandatory for the system to process the cleanup.

Schema:

create_proposal(
  title: "Prune/Consolidate [Topic]",
  proposal_type: "memory_cleanup",
  reasoning: "Brief explanation of why these IDs are being deleted (e.g., 'Obsolete status updates' or 'Consolidated into new memory #[ID]').",
  metadata: {
    # MANDATORY: The list of IDs to remove from the database
    memory_ids_to_delete: [102, 105, 108],
    
    # OPTIONAL: If this was a consolidation, reference the new master memory
    replacement_memory_id: 205 
  }
)

Heuristics for "Relevance"

Trust your judgment. If a human engineer joined the team today:

Would this memory help them understand the current system? -> Keep.
Is this memory just historical noise about a task finished 6 months ago? -> Prune.
Do they need to read 5 notes to understand 1 concept? -> Consolidate.

memory-consolidation

When & Why to Use This Skill

Use Cases