Skill: Cognitive

Domain: agent | Depth: axiom

Capabilities

• Reasoning chains: chain-of-thought, tree-of-thought, self-consistency
• Working memory management: context window, sliding window, summarization
• Episodic memory: store and retrieve past experiences
• Semantic memory: vector-based concept retrieval (ChromaDB)
• Attention modeling: relevance scoring, salience weighting
• Meta-cognition: confidence estimation, uncertainty quantification
• Belief updating: Bayesian reasoning primitives
• Pattern recognition across dimensional records (Akashic field)

Architecture

• Working memory: last N turns + auto-summarize on overflow
• Episodic memory: SQLite — timestamped facts and sessions
• Semantic memory: ChromaDB — vector similarity retrieval
• Akashic field: dimensional records — domain/depth/resonance retrieval

Libraries

Library	Purpose
torch	Attention, embeddings
numpy	Probability and belief arrays
scipy	Statistical reasoning
chromadb	Semantic memory backend

Module

agents/skills/cognitive.py

Key Functions

• chain_of_thought(problem, steps) — structured reasoning scaffold
• confidence(logits) — softmax confidence from raw scores
• bayesian_update(prior, likelihood, evidence) — posterior belief
• attention_score(query, keys) — dot-product attention weights
• summarize_context(turns, max_tokens) — compress working memory
• retrieve_relevant(concept, memory, n) — semantic memory retrieval