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Biologically-inspired cognitive memory for AI agents. Panksepp affects, Free Energy consolidation, VSA binding, sparse retrieval, temporal prediction, metacognition. Website - https://nima-core.ai
기본적으로 소스를 먼저 확인하는 Prompt가 선택됩니다. 직접 명령으로 전환하거나 로컬 사본을 다운로드할 수도 있습니다.
설치 여부를 결정하기 전에 SKILL.md와 SkillsMP에 표시된 보조 파일을 읽어 보세요.
Codex 또는 Claude로 설치 이 Prompt를 복사해 Codex, Claude 또는 다른 어시스턴트에 붙여 넣으면 Skill 페이지를 검토하고 설치를 진행할 수 있습니다.
직접 명령은 검토 Prompt를 거치지 않습니다. 실행하기 전에 소스를 확인하세요.
npx skills add https://github.com/duclm1x1/Dive-Ai --skill nima-core명령은 한 줄로 유지됩니다. 복사하기 전에 가로로 스크롤해 전체 내용을 확인하세요.
로컬 사본을 원하시나요? SkillsMP에서 현재 제공할 수 있는 파일을 다운로드하세요.
Persistent memory system for AI agents following Model Context Protocol (MCP). Use for storing long-term memories across sessions, semantic search of past knowledge, building knowledge graphs, auto-injecting context, deduplicating memories, syncing to cloud storage. Essential for agents that need to remember decisions, solutions, preferences, and learned patterns over time.
Persistent memory system for AI agents following Model Context Protocol (MCP). Use for storing long-term memories across sessions, semantic search of past knowledge, building knowledge graphs, auto-injecting context, deduplicating memories, syncing to cloud storage. Essential for agents that need to remember decisions, solutions, preferences, and learned patterns over time.
Master REST and GraphQL API design principles to build intuitive, scalable, and maintainable APIs that delight developers. Use when designing new APIs, reviewing API specifications, or establishing API design standards.
SKILL.md 표시 중
SOC 직업 분류 기준
| name | nima-core |
| description | Biologically-inspired cognitive memory for AI agents. Panksepp affects, Free Energy consolidation, VSA binding, sparse retrieval, temporal prediction, metacognition. Website - https://nima-core.ai |
| version | 1.1.3 |
| metadata | {"openclaw":{"emoji":"🧠","requires":{"bins":["python3"]}}} |
Plug-and-play cognitive memory architecture for AI agents.
Website: https://nima-core.ai
GitHub: https://github.com/lilubot/nima-core
pip install nima-core
# Auto-setup (detects OpenClaw, installs hooks, configures everything)
nima-core
openclaw gateway restart
openclaw hooks install /path/to/nima-core
openclaw hooks enable nima-bootstrap
openclaw hooks enable nima-recall
openclaw gateway restart
from nima_core import NimaCore
nima = NimaCore(
name="MyBot",
important_people={"Alice": 1.5, "Bob": 1.3}, # These people's memories get priority
)
nima.experience("Alice asked about the project", who="Alice", importance=0.7)
results = nima.recall("project")
Configure which people, emotions, and topics matter most:
from nima_core.services.heartbeat import NimaHeartbeat, SmartConsolidation
smart = SmartConsolidation(
important_people={"Alice": 1.5, "Bob": 1.3}, # Weight multipliers
emotion_words={"love", "excited", "proud", "worried"}, # Force-consolidate
importance_markers={"family", "milestone", "decision"}, # Force-consolidate
noise_patterns=["system exec", "heartbeat_ok"], # Skip these
)
heartbeat = NimaHeartbeat(nima, message_source=my_source, smart_consolidation=smart)
heartbeat.start_background()
Memories from important people get boosted. Emotional content is always kept. Noise is filtered out.
All V2 components are enabled by default (v1.1.0+). No configuration needed.
To disable: export NIMA_V2_ALL=false
nima.experience(content, who, importance) — Process through affect → binding → FE pipelinenima.recall(query, top_k) — Semantic memory searchnima.capture(who, what, importance) — Explicit memory capture (bypasses FE gate)nima.synthesize(insight, domain, sparked_by, importance) — Lightweight insight capture (280 char max)nima.dream(hours) — Run consolidation (schema extraction)nima.status() — System statusnima.introspect() — Metacognitive self-reflectionMETACOGNITIVE — Self-model, 4-chunk WM, strange loops
SEMANTIC — Hyperbolic embeddings, concept hierarchies
EPISODIC — VSA + Holographic storage, sparse retrieval
CONSOLIDATION — Free Energy decisions, schema extraction
BINDING — VSA circular convolution, role-filler composition
AFFECTIVE CORE — Panksepp's 7 affects (SEEKING, RAGE, FEAR, LUST, CARE, PANIC, PLAY)
| Variable | Default | Description |
|---|---|---|
NIMA_DATA_DIR | ./nima_data | Memory storage path |
NIMA_MODELS_DIR | ./models | Model files path |
NIMA_V2_ALL | true | Full cognitive stack (affects, binding, FE, etc.) |
NIMA_SPARSE_RETRIEVAL | true | Two-stage sparse index |
NIMA_PROJECTION | true | 384D → 50KD projection |
README.md — Full documentation with all settingsnima_core/config/nima_config.py — All feature flags.env.example — Environment variable template