Create a new SKILL.state execution session. Stores the immutable skill specification P and the initial execution state Σ_0, then returns the initial prompt payload (P, Σ_0, boot observation). From this point on, the LLM must treat that payload as its ENTIRE context — there is no message history. Advances happen exclusively through execute_step.

Advance a skill session by exactly one step t → t+1. INPUT: reasoning_trace R_t (Chain-of-Thought — discarded by the runtime and never stored), state_update ΔΣ_t (sparse JSON patch; null deletes a key), action a_t, and the environment_observation O_t you consumed this turn. LOGIC: validate ΔΣ_t → apply Σ_{t+1} = Σ_t ⊕ ΔΣ_t (null-deletion semantics) → execute a_t → obtain observation O_{t+1}. OUTPUT: the strict next-turn tuple {skill_spec: P, current_state: Σ_{t+1}, latest_observation: O_{t+1}}. Nothing else is retained — no history, no reasoning, no old observations.

Deliver an asynchronous environment observation / event alert into an active session (e.g. background alerts, customer orders, or external world drift per arXiv:2608.26263 §5.4). Does not advance the step count.

Parses a raw LLM response string containing free-form reasoning and a fenced ```json block { 'state_patch': {...}, 'action': '...' } per arXiv:2608.26263 Appendix A.4. Separates the reasoning trace R_t (for discarding) from the structured payload, mitigating JSON syntax slips (arXiv:2608.26263 §5.7).

Housekeeping: permanently remove a skill session and its execution state from the runtime. Returns the final Σ snapshot for auditability before deletion.