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dannydvm

Engram

by Dannydvm · GitHub ↗ · v0.2.0
cross-platform ✓ Security Clean
2019
Downloads
1
Stars
7
Active Installs
1
Versions
Install in OpenClaw
/install engram-memory
Description
Persistent semantic memory for AI agents — local, fast, free. Use when agent needs to recall past decisions, store new facts/preferences, search conversation history, or maintain context across sessions.
README (SKILL.md)

Engram — Agent Memory

Local semantic memory with biological decay, typed memories, and relationship graphs. No API keys. No cloud.

Boot Sequence

engram search "\x3Ccurrent task or context>" --limit 10

Always recall before working. Accessed memories get salience-boosted.

Storing

engram add "Client uses React with TypeScript" --type fact --tags react,client
engram add "We decided to pause ads" --type decision --tags ads
echo "Raw conversation text" | engram ingest

Types: fact, decision, preference, event, relationship

Searching

engram search "what tech stack"
engram search "pricing decisions" --type decision
engram search "client status" --agent client-agent

Relationships

engram relate \x3Csrc> \x3Ctgt> --type supports
engram auto-relate \x3Cid>
engram relations \x3Cid>

Types: related_to, supports, contradicts, caused_by, supersedes, part_of, references

Key Concepts

  • Decay: Unused memories lose salience daily. Recalled ones get boosted.
  • Types: Filter by fact, decision, preference, event, relationship.
  • Scoping: global, agent, private, shared.
  • Dedup: >92% similarity auto-merges.

Quick Reference

engram stats
engram recall --limit 10
engram export > backup.json
engram import backup.json
Usage Guidance
This skill appears internally consistent for a local CLI-based memory tool, but take these precautions before installing: 1) Inspect the npm package (engram-memory) on the npm registry or its repository — check package.json for postinstall scripts and examine the binary's source if available. 2) Prefer installing in a sandbox/container or with restricted permissions to confirm it behaves offline if you require 'no cloud' guarantees. 3) Be aware that export/import commands create/read local files (backup.json) — avoid exporting sensitive data to unsecured locations. 4) Run npm audit / malware scans and verify the package author and recent activity. If you cannot review the package source, treat the install as higher risk.
Capability Analysis
Type: OpenClaw Skill Name: Developer: Version: Description: OpenClaw Agent Skill The OpenClaw AgentSkills bundle defines a skill for persistent semantic memory. It installs the `engram-memory` npm package, providing the `engram` binary. All instructions in `SKILL.md` demonstrate the use of this binary for memory operations like adding, searching, ingesting, exporting, and importing data. There is no evidence of data exfiltration, malicious execution, persistence mechanisms, or prompt injection attempts to subvert the agent's behavior beyond the skill's stated purpose. File operations (`engram export > backup.json`, `engram import backup.json`) are confined to the skill's own data management.
Capability Assessment
Purpose & Capability
Name/description (local persistent semantic memory) match the declared binary 'engram' and the npm package 'engram-memory' that provides that CLI. Required binaries and declared install step are coherent with the skill's stated purpose.
Instruction Scope
SKILL.md contains only CLI usage for search/add/ingest/relate/export/import and references local files (e.g., export/import) and stdin ingestion — all expected for a local memory CLI. It does not instruct reading unrelated system files or requiring unrelated env vars.
Install Mechanism
Install uses a public npm package (engram-memory) which is a typical distribution method for a CLI. This is proportionate, but npm packages can execute arbitrary install scripts and the installed binary can perform network I/O; the skill claims 'No cloud' but that cannot be verified without inspecting the package.
Credentials
No environment variables, credentials, or config paths are requested. That is consistent with the 'local, no API keys' claim. Because no secrets are requested, there is no immediate credential overreach.
Persistence & Privilege
always:false and normal autonomous invocation are used. The skill does not request system-wide config changes or other skills' credentials. It will read/write local files (backup.json etc.) as expected for a local memory tool.
How to Use
  1. Make sure OpenClaw is installed (local or Docker)
  2. Run the install command in chat: /install engram-memory
  3. After installation, invoke the skill by name or use /engram-memory
  4. Provide required inputs per the skill's parameter spec and get structured output
Version History
v0.2.0
- Added comprehensive SKILL.md documentation outlining usage, key concepts, and commands for Engram agent memory. - Detailed instructions for memory storage, recall, and relationship management. - Explained memory decay, typing, deduplication, and scoping features. - Provided code examples for common tasks and quick reference commands. - Added metadata for installation and system requirements.
Metadata
Slug engram-memory
Version 0.2.0
License
All-time Installs 7
Active Installs 7
Total Versions 1
Frequently Asked Questions

What is Engram?

Persistent semantic memory for AI agents — local, fast, free. Use when agent needs to recall past decisions, store new facts/preferences, search conversation history, or maintain context across sessions. It is an AI Agent Skill for Claude Code / OpenClaw, with 2019 downloads so far.

How do I install Engram?

Run "/install engram-memory" in the OpenClaw or Claude Code chat to install it in one step — no extra setup required.

Is Engram free?

Yes, Engram is completely free (open-source). You can download, install and use it at no cost.

Which platforms does Engram support?

Engram is cross-platform and runs anywhere OpenClaw / Claude Code is available (cross-platform).

Who created Engram?

It is built and maintained by Dannydvm (@dannydvm); the current version is v0.2.0.

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