Skip to content

SKILL.md

Latest commit

 

History

History
149 lines (118 loc) · 4.73 KB

SKILL.md

File metadata and controls

149 lines (118 loc) · 4.73 KB
Raw
name superlocalmemory
description AI agent memory with mathematical foundations. Store, recall, search, and manage memories locally. Local data root; optional networked features have separate behavior.
version 4.0.0
author Varun Pratap Bhardwaj
license AGPL-3.0-or-later
homepage https://superlocalmemory.com
repository https://github.com/qualixar/superlocalmemory
triggers
remember something
recall memory
search memories
memory status
store fact
agent memory
local memory
memory health

SuperLocalMemory

AI agent memory with a local data root. Five candidate producers (semantic, BM25, temporal, spreading-activation, Hopfield) fuse via RRF, with an entity-graph post-fusion score enhancement — all with mathematical similarity scoring. Mode A operates without sending memory content to a cloud model provider; optional connectors, backup, and proxy providers are explicit choices with separate behavior.

Installation

pip install superlocalmemory
# or
npm install -g superlocalmemory

Quick Start

slm remember "Alice works at Google as a Staff Engineer" --json
slm recall "Who is Alice?" --json
slm status --json

Commands

All data-returning commands support --json for structured agent-native output.

Memory Operations

slm remember "<content>" --json           # Store a memory
slm remember "<content>" --tags "a,b" --json
slm recall "<query>" --json               # Semantic search
slm recall "<query>" --limit 5 --json
slm list --json -n 20                     # List recent memories
slm forget "<query>" --json               # Preview matches (add --yes to delete)
slm forget "<query>" --json --yes         # Delete matching memories
slm delete <fact_id> --json --yes         # Delete specific memory by ID
slm update <fact_id> "<content>" --json   # Update a memory

Diagnostics

slm status --json                         # System status (mode, profile, DB)
slm health --json                         # Math layer health
slm trace "<query>" --json                # Recall with per-channel breakdown

Configuration

slm mode --json                           # Get current mode
slm mode a --json                         # Set mode (a=local, b=ollama, c=cloud)
slm profile list --json                   # List profiles
slm profile switch <name> --json          # Switch profile
slm profile create <name> --json          # Create profile
slm connect --json                        # Auto-configure IDEs
slm connect --list --json                 # List supported IDEs

Bounded Loops

slm loop demo                             # Run built-in convergence demo (no API key needed)
slm loop history [--name <loop-name>]     # List recorded runs from SLM memory
slm loop show <run_id>                    # Show every lap of one run

Loop laps are persisted to SLM memory under the tag loop:<name>. MCP tools slm_loop_run, slm_loop_history, and slm_loop_show are available in the code and full profiles.

Services (no --json)

slm setup                                 # Interactive setup wizard
slm mcp                                   # Start MCP server (for IDE integration)
slm dashboard                             # Open web dashboard
slm warmup                                # Pre-download embedding model

JSON Envelope

Every --json response follows a consistent envelope:

{
  "success": true,
  "command": "recall",
  "version": "4.0.0",
  "data": {
    "results": [
      {"fact_id": "abc123", "score": 0.87, "content": "Alice works at Google"}
    ],
    "count": 1,
    "query_type": "semantic"
  },
  "next_actions": [
    {"command": "slm list --json", "description": "List recent memories"}
  ]
}

Error responses:

{
  "success": false,
  "command": "recall",
  "version": "4.0.0",
  "error": {"code": "ENGINE_ERROR", "message": "Description of what went wrong"}
}

Operating Modes

Mode Description Cloud Required
A Local Guardian -- core memory runs without a cloud model provider; optional connectors and model downloads may use the network None (for core memory)
B Smart Local -- local Ollama LLM, data stays on your machine Local only
C Full Power -- cloud LLM for maximum accuracy Yes

Dual Interface

SuperLocalMemory works via both MCP and CLI:

  • MCP: 24 tools (code profile) for IDE integration (Claude Code, Cursor, Windsurf, VS Code, JetBrains, Zed); includes bounded-loop tools slm_loop_run/history/show
  • CLI: commands with --json for scripts, CI/CD, and agent frameworks; includes slm loop demo/history/show

Part of Qualixar | Author: Varun Pratap Bhardwaj (qualixar.com | varunpratap.com)