Operational directive instructing the active Agent to calculate Semantic Resonance (Cosine Similarity) between logic execution and governance documentation, actively refactoring dissonance until >75% mathematical resonance is achieved.
Measure and maximize the alignment between Python executing code (AST tokens) and Markdown governance artifacts (Semantic text) using mathematical Cosine Similarity.
This skill relies on the embedded auditor tool:
resonance_scanner.py
python "C:\Users\Chris\Synarche_Workspace\.agent\skills\Systemic Resonance Alignment\resonance_scanner.py" <path_to_python> --doc <path_to_markdown>. Or target a directory to scan all pairs automatically.< 75.0 / 100.0, the system is dissonant.resonance_scanner.py tool until the Cosine Similarity Score reaches >= 75.0.Every operational execution of this skill MUST generate a SELT (Standardized Experience Log Template) "Shadow Log". This log captures the inner metacognitive deconstruction and dissonance resolution BEFORE taking action. All Shadow Logs MUST strictly utilize the canonical Block A: Universal Identification & Provenance (UIP-V15) header to ensure Isomorphic Provenance.