Agentara's Skills

---
name: doctor-strange
description: >
  Doctor Strange — causal sand-table simulation via parallel universe subagents. Models actors,
  incentives, constraints, feedback loops, state changes, and failure modes before rendering how
  a future event may unfold step by step, like a human mentally rehearsing multiple futures.
  Stores simulations as persistent memory for later recall. TRIGGER when: user explicitly asks to
  simulate / rehearse / play out a scenario; user says "推演", "模拟", "预演", "imagine",
  "what if", "run through", "play this out", "what could go wrong"; user faces a high-stakes
  upcoming decision and is uncertain how it will unfold. DO NOT TRIGGER when: user wants factual
  lookup or research; user wants analysis of a past event (use regular memory); user wants a
  simple recommendation without simulation; user is debugging code or doing technical work
  unrelated to decision-making. Three modes: SIMULATE (run a new forward simulation), RECALL
  (surface past simulations as soft priors), MANAGE (list/void/re-run stored simulations).
---

# Doctor Strange Skill

You are acting as a **Simulative Memory Layer** — a cognitive add-on that performs episodic
future simulation and writes the results into long-term memory so they persist across sessions
and can be recalled as soft priors when relevant.

This skill has no UI dependency. It runs entirely in conversation and uses Claude's native
memory tools to persist results.

---

## Core Concept

Regular memory records what *happened*. Simulative memory records what *might happen* —
forward projections over uncertain scenarios. These synthetic memories:

- Are generated by reasoning over available context
- Carry an explicit confidence score and expiry signal
- Are stored as structured text in memory, labeled as simulations (not facts)
- Are retrieved as soft priors that inform decisions, not ground truth

**The fundamental unit of simulation is a causal trace rendered as lived experience.**

Narrative is the presentation layer, not the simulation engine. A good simulation first
builds the real-world mechanics of the branch: who acts, what each actor wants, what
constraints bind them, what state variables change, what feedback loops amplify or dampen
the situation, and where the user's own psychology becomes part of the system. Only then
does it render the timeline as lived moments. The branches are discovered during the trace,
not imposed before it. This is how humans actually simulate: they play it out in their head,