Superlocalmemory

What it does

When your agent uses it

• Tasks that involve Agent memory

Example prompts

• “/superlocalmemory”

Requirements

• Python 3
• Node.js

What it can do on your machine

Read from SKILL.md and the folder at commit ce2d7a9. It shows what the files ask for, not the result of running them.

• Tool permissions

  Pre-approves nothing: there is no allowed-tools line, so your agent's usual permission prompts apply.

  From allowed-tools in the SKILL.md frontmatter.

• Runs code

  Ships 1 file in scripts/, which the agent can run.

  Shell commands in SKILL.md call:

  • pip
  • npm

  From the folder's file list and the shell code blocks in SKILL.md.

• Network

  No URLs in SKILL.md. Its commands use pip and npm, which can reach the network depending on how they are called.

  From URLs in SKILL.md, links to its own repository left out.

• Credentials

  Names no API keys, tokens, secrets or passwords.

  From names ending in _API_KEY, _TOKEN, _SECRET, _KEY or _PASSWORD in SKILL.md.

Context cost

Superlocalmemory loads about 1.2k tokens when it runs. Until then it costs about 46 tokens; SKILL.md has 237 words of instructions outside code blocks.

Always · name and description, kept in context so the agent knows when to use it

~46

When it runs · the whole SKILL.md, loaded when a task matches

~1.2k

Estimates: characters ÷ 4, the usual rule of thumb; real counts depend on the model's tokenizer. Scripts and assets cost tokens only if the agent reads them.

Safety

Automated static check — not a guarantee. Review scripts before installing. It scans the text of SKILL.md for risky patterns (piping downloads into a shell, reading credential files, hidden Unicode, destructive commands); the scripts in this folder are not scanned.

SKILL.md

The full file from qualixar/superlocalmemory at commit ce2d7a9, republished under its AGPL-3.0-or-later licence (© qualixar). 237 words, ~1,240 tokens.

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

pip install superlocalmemory
# or
npm install -g superlocalmemory

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

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

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

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

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

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

{
  "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"}
  ]
}

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

© qualixar, AGPL-3.0-or-later. Rendered from Markdown: HTML in the file is shown as text, images as links, and headings moved down two levels. Raw file

Files

SKILL.md and 3,064 other files (scripts, assets) in the repository root of qualixar/superlocalmemory.

• SKILL.md
• .claude-plugin/marketplace.json
• .gitattributes
• .github/FUNDING.yml
• .github/workflows/installer-matrix.yml
• .github/workflows/plugin-validate.yml
• .github/workflows/pypi-publish.yml
• .github/workflows/test.yml
• .gitignore
• .lfsconfig
• .npmignore
• AGENTS.md
• ATTRIBUTION.md
• AUTHORS.md
• CHANGELOG.md
• CITATION.cff
• COMMERCIAL-LICENSE.md
• CONTRIBUTING.md
• … and 3,047 more

Open the folder on GitHubat commit ce2d7a9