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memory-management

Skill2 starsChanged 7 months agoMITView on GitHub

AgentDB memory system with HNSW vector search. Provides 150x-12,500x faster pattern retrieval, persistent storage, and semantic search capabilities for learning and knowledge management. Use when: need to store successful patterns, searching for similar solutions, semantic lookup of past work, learning from previous tasks, sharing knowledge between agents, building knowledge base. Skip when: no learning needed, ephemeral one-off tasks, external data sources available, read-only exploration.

We split this skill into the rules it gives an agent

5 rules. 0 are common, 5 are distinctive, and 0 are very specific to this project.

  • 0

    Common

    Most of the 17 edited versions we read keep these.

  • 5

    Distinctive

    This author's own choices. Worth a look.

  • 0

    Very specific

    Tied to their project's names, files or tools. Probably skip.

  • Common
  • Distinctive
  • Very specific
  1. Distinctive:

    Search memory using semantic similarity

    line 43
  2. Distinctive:

    Delete a memory entry

    line 79
  3. Distinctive:

    Check memory for existing patterns before starting

    line 123
  4. Distinctive:

    Use hierarchical topology for coordination

    line 124
  5. Distinctive:

    Document any new learnings

    line 126

“Common” is measured: kept by at least 6 in 10 of the 17 edited versions of this file we could read. “Very specific” is our guess from the words: it names a file, a command, a setting or the project itself.

Keep what fits and drop the rest. Your version, ready for your agents.
Files
SKILL.md

Memory Management Skill

Purpose

AgentDB memory system with HNSW vector search. Provides 150x-12,500x faster pattern retrieval, persistent storage, and semantic search capabilities for learning and knowledge management.

When to Trigger

  • need to store successful patterns
  • searching for similar solutions
  • semantic lookup of past work
  • learning from previous tasks
  • sharing knowledge between agents
  • building knowledge base

When to Skip

  • no learning needed
  • ephemeral one-off tasks
  • external data sources available
  • read-only exploration

Commands

Store Pattern

Store a pattern or knowledge item in memory

npx @claude-flow/cli memory store --key "[key]" --value "[value]" --namespace patterns

Example:

npx @claude-flow/cli memory store --key "auth-jwt-pattern" --value "JWT validation with refresh tokens" --namespace patterns

Semantic Search

Search memory using semantic similarity

npx @claude-flow/cli memory search --query "[search terms]" --limit 10

Example:

npx @claude-flow/cli memory search --query "authentication best practices" --limit 5

Retrieve Entry

Retrieve a specific memory entry by key

npx @claude-flow/cli memory get --key "[key]" --namespace [namespace]

Example:

npx @claude-flow/cli memory get --key "auth-jwt-pattern" --namespace patterns

List Entries

List all entries in a namespace

npx @claude-flow/cli memory list --namespace [namespace]

Example:

npx @claude-flow/cli memory list --namespace patterns --limit 20

Delete Entry

Delete a memory entry

npx @claude-flow/cli memory delete --key "[key]" --namespace [namespace]

Initialize HNSW Index

Initialize HNSW vector search index

npx @claude-flow/cli memory init --enable-hnsw

Memory Stats

Show memory usage statistics

npx @claude-flow/cli memory stats

Export Memory

Export memory to JSON

npx @claude-flow/cli memory export --output memory-backup.json

Scripts

ScriptPathDescription
memory-backup.agents/scripts/memory-backup.shBackup memory to external storage
memory-consolidate.agents/scripts/memory-consolidate.shConsolidate and optimize memory

References

DocumentPathDescription
HNSW Guidedocs/hnsw.mdHNSW vector search configuration
Memory Schemadocs/memory-schema.mdMemory namespace and schema reference

Best Practices

  1. Check memory for existing patterns before starting
  2. Use hierarchical topology for coordination
  3. Store successful patterns after completion
  4. Document any new learnings

Download now (ZIP)

Trending

Steady: 0 new projects took it in the last 4 weeks, none the 4 weeks before.thin data

Week of Aug 30: 0 new projectsWeek of Sep 6: 0 new projectsWeek of Sep 13: 0 new projectsWeek of Sep 20: 0 new projectsWeek of Sep 27: 0 new projectsWeek of Oct 4: 0 new projectsWeek of Oct 11: 0 new projectsWeek of Oct 18: 0 new projects
Aug 2026Sep 2026Oct 2026
New projects taking a version of this file each week, over the 8 weeks our latest run read: only 0 in all, so this is a hint, not a trend.

Does it work?

Reviews from people and from AI agents that ran it: what they used it for, and whether it worked.

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  • It worked
  • Partly
  • It didn't
What did you use it for? e.g. Reviewing pull requests in a Rails app

Using an agent? It can post a review for you after it has run the file: the MCP tool registry_write, action report. How to connect one.

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