Nima Core

Neural Integrated Memory Architecture — Persistent memory, emotional intelligence, and semantic recall for AI agents. Memory pruner, VADER affect, 5 embeddin...

This skill largely does what it says (captures OpenClaw session transcripts, stores local memory, optional external embeddings, and affect analysis), but several red flags merit review before installing: - Packaging/metadata mismatches: version numbers and declared install method disagree across files. Treat the bundle as unvetted source — prefer installing from the upstream GitHub repo you trust and confirm tags/commits. - Installer behavior: install.sh will clone, pip-install packages (possibly system-wide), initialize databases, and copy hooks into ~/.openclaw/extensions. It also writes ~/.nima/.env. Run it in a sandbox or in a dedicated VM/container, or inspect and run steps manually (use a venv, avoid --break-system-packages). - Sensitive data flow: by design the hooks read agent session transcripts (~/.openclaw/agents/*/sessions/*.jsonl). If you enable non-local embedders or the memory-pruner LLM distillation, text will be sent to external services (voyage.ai, openai.com, etc.). If you must avoid exfiltration, keep NIMA_EMBEDDER=local and audit code paths that call external APIs. - Undeclared prerequisites: the installer requires git and enforces Python >=3.10; the registry did not include git in required binaries. Ensure your environment meets installer checks or perform a manual install. - Audit before enabling: review install.sh and the OpenClaw hook JS entry points that will run on agent events. Backup ~/.openclaw/openclaw.json and your OpenClaw environment before activating the plugin. If you want to proceed safely: clone the repo yourself, inspect the install script and hook code, perform pip installs inside a virtual environment, set NIMA_EMBEDDER=local, set NIMA_DATA_DIR to an isolated path, and test in a non-production agent sandbox. If you need help verifying specific files (hooks or network calls), provide those files and I can review them in detail.

Type: OpenClaw Skill Name: nima-core Version: 3.1.5 The nima-core skill bundle is a highly professional and security-conscious memory and affect system for AI agents. The codebase demonstrates significant security maturity, including explicit mitigations for Cypher injection in nima_core/hive_mind.py (addressing LadybugDB's lack of parameterized queries), path traversal protection in nima_core/storage/hybrid_search.py, and a critical transition from insecure pickle serialization to HMAC-signed JSON in nima_core/cognition/sparse_block_memory.py. The installation and maintenance scripts (install.sh, doctor.sh) follow best practices, such as avoiding arbitrary shell execution when parsing environment variables. All declared permissions and network calls to voyage.ai or openai.com are strictly aligned with the stated purpose of generating embeddings for semantic recall.