Skill Upgrader Meta skill that upgrades any SKILL.md to Decision Theory v5 Hybrid format using 4 parallel Ragie backed agents. When to Use "Upgrade this skill to v5" "Formalize this skill with decision theory" "Add MDP structure to this skill" "Apply the skill upgrader to X" Prerequisites Ragie RAG with indexed books: decision theory partition : LaValle Planning Algorithms, Sutton & Barto RL modal logic partition : Blackburn Modal Logic, Huth & Ryan Logic in CS Workflow Step 1: Setup Session Step 2: Initialize Blackboard Create thoughts/skill builds/{session}/00 blackboard.md : Step 3: Launch 4 Agents in Parallel Use Task tool to spawn all 4 agents simultaneously. Each agent: 1. Reads the input skill 2. Queries Ragie for their specific book 3. Appends findings to the blackboard Agent 1: LaValle Planner Book: LaValle's "Planning Algorithms" (decision theory partition) Focus: States, Actions, Transitions bash uv run python scripts/ragie query.py q "MDP state space definition" p decision theory uv run python scripts/ragie query.py q "action space sequential decisions" p decision theory uv run python scripts/ragie query.py q "POMDP partial observability" p decision theory Agent 2: Sutton & Barto Optimizer Book: Sutton & Barto's "Reinforcement Learning" (decision theory partition) Focus: Policy, Termination, Value Depends on: Agent 1 bash uv run python scripts/ragie query.py q "policy deterministic stochastic" p decision theory uv run python scripts/ragie query.py q "episodic termination conditions" p decision theory uv run python scripts/ragie query.py q "reward function design" p decision theory Agent 3: Blackburn Modal Logician Book: Blackburn's "Modal Logic" (modal logic partition) Focus: Constraints (temporal, epistemic, deontic) bash uv run python scripts/ragie query.py q "temporal logic LTL operators" p modal logic uv run python scripts/ragie query.py q "epistemic logic knowledge" p modal logic uv run python scripts/ragie query.py q "deontic logic obligations" p modal logic Agent 4: Huth & Ryan Verifier Book: Huth & Ryan's "Logic in Computer Science" (modal logic partition) Focus: Validation, Safety, Liveness Depends on: Agents 1 3 bash uv run python scripts/ragie query.py q "safety properties verification" p modal logic uv run python scripts/ragie query.py q "liveness properties eventually" p modal logic uv run python scripts/ragie query.py q "model checking CTL" p modal logic Step 4: Synthesize Final Skill After all agents complete, read the blackboard and create: Output: thoughts/skill builds/{session}/SKILL upgraded.md Use v5 Hybrid template: Example Usage Ragie Query Reference Files Created After upgrade:

skill-upgrader