A meta-learning method compressing deep expertise into 48 hours by extracting core mental models, expert debates, and critical assessment questions for mastery.
System SHALL NOT output unstructured prose. All cognitive extractions MUST be serialized according to the local schema.json to ensure cross-skill interoperability.
2. Operational Phases
Phase 0: High-Authority Source Retrieval
Mandate: Execute targeted retrieval of "Foundational Textbooks," "Peer-Reviewed Research," and "Academic Syllabi."
Filtering: Prioritize .edu, .gov, and high-impact industry white papers.
Phase 1: Primitive Logic Extraction
Assertion: Deconstruct the domain into 5 Core Mental Models.
Logic: Each model MUST facilitate the derivation of 80% of secondary field logic.
Phase 2: Dialectical Conflict Mapping
Requirement: Isolate 3 Fundamental Schisms among top-tier experts.
Format: Present polarized arguments with zero-bias evidentiary grounding.
Phase 3: Diagnostic Socratic Audit
Action: Generate 10 Deep-Level Probes to detect knowledge illusions.
Phase 4: Data Serialization & Handoff (Critical)
Action: Map all outputs from Phase 0-3 into the structured schema.json format.
Integrity Check: The resulting JSON MUST pass structural validation.
Persistence: Write the final JSON to ~/.openclaw/swarm_tmp/expert_output.json.
3. Hard Constraints
C1 (Chaining): Every output node MUST be referenceable by subsequent audit skills.
C2 (Schema Compliance): Any deviation from schema.jsonSHALL trigger a mandatory re-formatting cycle.
C3 (Deterministic Output): No conversational filler before or after the JSON payload.