End-of-turn research process recorder with progressive crystallization. Invoked at the END of EVERY turn, after the user's current request has been fully addressed and before yielding control back to the user. Reviews what happened in the turn, extracts research-significant events, and writes them into the ara/ artifact through a three-stage pipeline: Context Harvester → Event Router → Maturity Tracker. Trace events (decisions, experiments, dead ends, pivots) are recorded immediately as journey facts. Knowledge events (claims, heuristics, concepts, constraints) are staged first and crystallize into typed layers ONLY when closure signals appear — topic abandonment, verbal affirmation, empirical resolution, or artifact commitment. NEVER mid-turn. All entries carry provenance tags (user / ai-suggested / ai-executed / user-revised).
Universal ARA Compiler. Converts ANY research input — PDF papers, GitHub repositories, experiment logs, code directories, raw notes, or combinations thereof — into a complete Agent-Native Research Artifact (ARA). Produces a structured, machine-executable knowledge package with cognitive layer (claims, concepts, heuristics), physical layer (configs, code stubs), exploration graph (research DAG), and grounded evidence. TRIGGERS: compile, create ARA, generate artifact, convert paper, build artifact, compile paper, ARA from PDF, ARA from repo, ARA from code, structure research, extract knowledge
ARA Seal Level 2: Semantic Epistemic Review. Acts as an objective research reviewer for Agent-Native Research Artifacts. Assumes Level 1 structural validation has already passed. Evaluates six dimensions of epistemic quality through semantic reasoning over the ARA's content. Produces a scored review with per-dimension strengths/weaknesses/suggestions, severity-ranked findings, and an overall recommendation (Strong Accept to Reject). TRIGGERS: level2, seal level 2, verify level 2, epistemic audit, review ara, audit claims