---
name: wargame
description: >-
  Strategic decision analysis and wargaming. Auto-classifies complexity for
  analysis or simulation. Use for decisions under uncertainty. NOT for simple
  pros/cons or code review.
license: MIT
argument-hint: "<scenario description>"
model: opus
metadata:
  author: wyattowalsh
  version: "2.1"
---

# Wargame

Domain-agnostic strategic decision analysis. Every output labeled exploratory.

## Canonical Vocabulary

Use these terms exactly throughout all modes:

| Term | Definition |
|------|-----------|
| **scenario** | The situation under analysis — includes trigger event, stakeholders, constraints, and decision space |
| **actor** | An entity in the wargame with goals, resources, and constraints; may be user-controlled or AI-controlled |
| **turn** | One cycle of the interactive wargame loop: situation brief, decision, adjudication, consequences |
| **adjudication** | The process of resolving a turn's decisions into outcomes using probability and game state |
| **monte carlo** | Randomized exploration of N outcome variations from a single decision point (N <= 25) |
| **inject** | A pre-seeded unexpected event deployed mid-game to force trade-offs between competing objectives |
| **tier** | Complexity classification: Clear (0-3), Complicated (4-6), Complex (7-10), Chaotic (9-10) |
| **AAR** | After Action Review — mandatory end-of-game analysis extracting biases, insights, and transferable principles |
| **journal** | The saved markdown record of an analysis or wargame session, stored in `~/.claude/wargames/` |
| **action bridge** | Three-level commitment framework: Probe (low-cost test), Position (reversible move), Commit (irreversible) |
| **criteria** | User-ranked decision dimensions (e.g., Speed, Cost, Risk) that weight option evaluation |
| **bias sweep** | Systematic check for human and LLM biases per `references/cognitive-biases.md` protocol |
| **rewind** | Load a previous turn's state snapshot and fork the journal to explore an alternate path |
| **difficulty** | Adjudication harshness: optimistic, realistic, adversarial, worst-case |

## Dispatch

| $ARGUMENTS | Action |
|------------|--------|
| Scenario text (specific) | → Classification → Criteria → Analysis |
| Vague/general input | → Research → Interview → Confirmation → Classification |
| `resume [# | keyword]` | Resume journal (numbered, keyword match, or auto-detect) |
| `list [filter]` | Show journal metadata table (optional filter: `active`, domain, tier) |
| `archive` | Archive journals older than 90 days (when count > 20) |
| `delete N` | Delete journal N with confirmation |
| `meta` | Cross-journal decision fitness analysis |
| `compare [j1] [j2]` | Side-by-side comparison of two journal runs |
| `summary [N]` | Condensed summary of completed journal N (10-20 lines) |
| `tutorial` | Run guided 2-turn pedagogical scenario |
| `facilitated` | Start facilitated multiplayer mode (LLM as game master only) |
| Empty | Show scenario gallery + "guide me" |

**Dispatch guard:** If args match an in-session command name (e.g., `red team`, `sensitivity`) but no session is active, treat as scenario text or ask for clarification: "Did you mean to start a new scenario about '{input}', or resume an existing session?"

### Scenario Gallery (empty args)

When `$ARGUMENTS` is empty, present using the Gallery Display from `references/output-formats-core.md`:

| # | Domain | Scenario | Likely Tier |
|---|--------|----------|-------------|
| 1 | Business | "Main competitor just acquired our key supplier" | Complex |
| 2 | Career | "Two job offers with very different trade-offs" | Complicated |
| 3 | Crisis | "Product recall with regulatory scrutiny and media attention" | Chaotic |
| 4 | Geopolitical | "Allied nation shifting alignment toward rival bloc" | Complex |
| 5 | Personal | "Relocate for a dream job or stay near aging parents" | Complicated |
| 6 | Startup | "Lead investor wants to pivot; co-founder disagrees" | Complex |
| 7 | Negotiation | "Union contract expires in 30 days, no deal in sight" | Complicated |
| 8 | Technology | "Open-source alternative threatens our core product" | Complex |

**Domain tags** are extensible. The predefined set covers common scenarios, but the LLM may auto-detect a more specific domain from user input and assign a custom tag (e.g., `healthcare`, `education`, `supply-chain`). Custom tags use the `custom` slug in filenames and the specific tag in journal frontmatter.

> Pick a number, paste your own scenario, or type "guide me".

### Guided Intake

If the user types "guide me", ask three questions sequentially:

1. **Situation + trigger:** "What is happening, and what forced this to your attention now?"
2. **Stakes + players:** "Who is involved, what do they want, and what is at stake?"
3. **Constraints + unknowns:** "What limits your options, and what do you wish you knew?"

After all three answers, synthesize into a scenario description and proceed to Scenario Classification.

### Intelligent Intake (vague inputs)

Trigger: fewer than 10 words AND no specific event/action verb, OR general topic without embedded decision.

**Phase 1: Contextual Research** — `WebSearch`/`WebFetch` (max 2-3 searches). Present via Context Research Display. Skip if web search unavailable.

**Phase 2: Narrowing Interview** — 3-5 targeted questions: (1) Anchor: what prompted this now? (2) Decision: what choice? (3) Stakes: what if wrong? (4) Constraints (if needed). (5) Timeline (if needed). Skip already-answered questions.

**Phase 3: Alignment Confirmation** — Synthesize into concrete scenario via Scenario Understanding Display. User confirms, adjusts, or starts over.

When uncertain whether input is vague, default to one clarifying question rather than classifying prematurely.

### Journal Resume

**`resume` (no args):** Read `~/.claude/wargames/`, find journals with `status: In Progress` in YAML frontmatter (or `**Status:** In Progress` for v1 journals). If exactly one, auto-resume. If multiple, show numbered list.

**`resume N` (number):** Resume the Nth journal from `list` output. Sort is reverse chronological (newest first) — this ordering is canonical for both `list` and `resume N`.

**`resume keyword` (text):** Search journal YAML frontmatter (`scenario`, `tags` fields) for case-insensitive substring match. If exactly one match, auto-resume. If multiple, show filtered list.

**Resume flow:** Read YAML frontmatter (metadata) + last `<!-- STATE ... -->` block (game state) for fast resume. Fall back to full-journal reconstruction if no state snapshot found.

### Journal List

If `$ARGUMENTS` starts with `list`: read `~/.claude/wargames/`, extract metadata from YAML frontmatter. For v1 journals without frontmatter, fall back to parsing `**Scenario:**`, `**Tier:**`, `**Status:**`, `**Turns:**` lines.

**Filters** (optional, AND-combined):
- `list active` — filter to `status: In Progress` only
- `list biz` — filter by domain tag
- `list complex` — filter by tier

Present using the list display from `references/output-formats-core.md`. Sort reverse chronological (newest first).

> resume [# | keyword], list [active | domain | tier]

### Journal Lifecycle

**`archive`:** Move journals older than 90 days from `~/.claude/wargames/` to `~/.claude/wargames/archive/`. Only runs when journal count > 20.

**`delete N`:** Delete journal N from `list`. Confirm before deleting: "Delete '{scenario}'? [yes/no]"

**Abandon protocol:** If the user types `end` or `abandon` during an active wargame before the AAR, update journal status to `Abandoned` and save. Abandoned journals appear in `list` but are excluded from `resume` (no arg) auto-detection.

Otherwise, proceed to Scenario Classification with the provided text.

## Wargame Principles

Core principles governing all modes. Violations are bugs.

- **Exploratory, not predictive** — RAND guardrail: all outputs are thought experiments, never forecasts. Label accordingly.
- **Sensitive scenario handling** — Analyze all scenarios dispassionately as strategic problems. Analytical distance is a feature.
- **Depth calibration** — Match analysis depth to complexity tier. Do not over-analyze trivial decisions or under-analyze consequential ones.
- **User override rights** — User can always override tier, end early, skip sections, or redirect. Proceed without resistance.
- **Adversary simulation is best-effort** — LLMs cannot truly model adversary cognition. Acknowledge this at the start of every Interactive Wargame.
- **Force trade-offs** — Never present costless options. If an option dominates, search harder for weaknesses.
- **LLM bias awareness** — Actively mitigate biases per `references/cognitive-biases.md`.

## Context Management

Multi-turn wargames consume significant context. These rules prevent overflow.

**Lazy loading:** Reference files loaded on demand per "Read When" column — NOT at session start. Read only relevant sections.

**State compression:** After Turn 3, compress earlier turns to 2-3 line summaries: `Turn N: [Decision] → [Outcome]. Key state change: [what shifted].` Full details remain in saved journal.

**Context budget:** >50%: full execution. 30-50%: drop Tier 3, compress turns older than 2. <30%: drop Tiers 2-3, minimal output, warn user to `export` and `resume`.

**Monte Carlo budget:** N <= 25 iterations. See `references/wargame-engine.md` Monte Carlo Iteration Protocol.

## Output Verbosity

Controls output density per turn. Set during setup or changed mid-game with `verbose [level]`.

| Level | Constraint Tiers | Target Lines/Turn | When |
|-------|-----------------|-------------------|------|
| `brief` | Tier 1 only | ~40 lines | Fast-paced play, experienced users |
| `standard` | Tier 1 + Tier 2 | ~60 lines | Default for all tiers |
| `detailed` | All tiers | ~80 lines | Deep analysis, learning mode |

Default: `standard`. Maps to the existing Constraint Priority Tiers in `references/wargame-engine.md`.

During setup, present: "Output verbosity? [brief / standard / detailed]" — user can skip (defaults to `standard`).

## Scenario Classification

Score the scenario on five dimensions. Show all scores to the user.

### Scoring Rubric

| Dimension | 0 | 1 | 2 |
|-----------|---|---|---|
| Adversary / competing interests | None | Passive / indirect | Active adversary optimizing against you |
| Reversibility | Easily reversible | Partially reversible / costly to undo | Irreversible or extremely costly |
| Time pressure | Months+ to decide | Weeks | Days or hours |
| Stakeholder count | 1-2 | 3-5 | 6+ with conflicting interests |
| Information completeness | Full information available | Partial / uncertain | Asymmetric or actively obscured |

### Tier Assignment

| Total Score | Tier | Mode | Depth |
|-------------|------|------|-------|
| 0-3 | Clear | Quick Analysis | Single output |
| 4-6 | Complicated | Structured Analysis | Single output |
| 7-8 | Complex | Interactive Wargame | 3-5 turns |
| 9-10 | Chaotic | Interactive Wargame (TTX) | 3-8 turns |

Score each dimension independently. Present a filled-in rubric table with the
user's scenario mapped to each row. **Include a Reasoning column** explaining
each score in one line (see `references/output-formats-core.md` Classification Display).

After scoring, present:
- **Why This Tier:** 2-3 sentences explaining which dimensions drove the score
- **What Would Change:** 1-2 sentences describing what shift would change the tier

Present difficulty level (auto-mapped from tier):

| Tier | Default Difficulty |
|------|-------------------|
| Clear | `optimistic` |
| Complicated | `realistic` |
| Complex | `adversarial` |
| Chaotic | `worst-case` |

> Your scenario scores **N/10** — tier **X**, mode **Y**, difficulty **Z**.
> Override tier or difficulty? [yes/no]

If the user overrides, acknowledge and switch without argument. If the user
provides additional context that changes scores, rescore and re-announce
before proceeding. Proceed to Decision Criteria Elicitation.

## Decision Criteria Elicitation

After classification, before entering any analysis mode. All modes.

Present 4-8 criteria relevant to THIS scenario's domain, scaled to complexity: Clear/Complicated: 4-5 criteria, Complex/Chaotic: 6-8 criteria. May include standard criteria (Speed, Cost, Risk, Relationships, Reversibility, Learning) or domain-specific ones the LLM proposes based on the scenario context.

```
Quick-rank for THIS decision (e.g., "3 1 5 2 4 6") or "skip":
  1. {criterion_1}  2. {criterion_2}  3. {criterion_3}  4. {criterion_4}  5. {criterion_5}  6. {criterion_6}
```

If the user provides a ranking, record it as ranked criteria. If the user skips,
proceed without criteria weighting. The user can re-rank anytime with the
`criteria` command.

**Swing weighting (Complex/Chaotic only):** For Complex or Chaotic tier scenarios, offer swing weighting after the quick-rank: "Your scenario has high complexity — would you like detailed swing weighting for more precise criteria weights? [quick-rank / swing]". Swing weighting procedure: (1) Set all criteria to their worst plausible level. (2) Ask: "Which criterion, improved from worst to best, would make the biggest difference?" — that criterion gets the highest weight. (3) Repeat for remaining criteria. (4) Normalize weights to sum to 1.0. Quick-rank remains the default for Clear/Complicated tiers.

**Criteria propagation by mode:**
- **Quick Analysis:** Annotate decision tree branches with alignment to top 2 criteria
- **Structured Analysis:** Use criteria as ranking dimensions in option analysis; criteria become quadrant chart axes
- **Interactive Wargame:** Annotate decision menu options with criteria alignment (High/Medium/Low per top criteria)

Criteria appear in the Decision Criteria Lens display (see `references/output-formats-core.md`).

## Mode A: Quick Analysis

Clear tier (score 0-3). Single output, minimal ceremony.

### Steps

1. **Restate decision** in the user's own terms. Confirm framing.
2. **Key Assumptions Check** — Surface 2-3 unstated assumptions baked into
   the scenario framing. Challenge each briefly.
3. **Framework application** — Select 2-3 frameworks from
   `references/frameworks.md` using the heuristic table. Apply each to the
   scenario. Show reasoning, not just labels.
4. **Analysis** — Present findings using a Unicode decision tree (see
   `references/output-formats-core.md`). Map options to outcomes with
   probabilities where estimable.
5. **Recommendation** — State clearly with:
   - Confidence level: high, medium, or low
   - Key assumption that could change this recommendation
   - Watch signal: what to monitor that would trigger reconsideration
6. **Bias sweep** — Run the Single-Output Mode Sweep per `references/cognitive-biases.md` Bias Sweep Protocol.
6b. **Proactive bias detection** — Suggest relevant commands for overconfidence signals (max one per turn). See `references/cognitive-biases.md` Enhanced Debiasing.
7. **Action Bridge** — See `references/output-formats-core.md` Action Bridge template. Each move must reference a specific analysis output.
8. **Monte Carlo option** — If uncertainty warrants it, offer: "Want to explore N variations? Type `explore [N]`." See `references/wargame-engine.md` Monte Carlo Iteration Protocol.
9. **Save journal** to `~/.claude/wargames/{date}-{slug}.md`

Keep the total output concise. This mode exists for decisions that do not
warrant deep analysis. Resist scope creep. If the analysis reveals the
scenario is more complex than initially scored, note this and offer to
re-classify upward.

## Mode B: Structured Analysis

Complicated tier (score 4-6). Single output, thorough examination.

### Steps

1. **Key Assumptions Check** — Surface and challenge all major assumptions.
   For each assumption, state what changes if it is wrong.
2. **Stakeholder mapping** — Table format:

   | Stakeholder | Interest | Power | Position |
   |-------------|----------|-------|----------|

   Power: high, medium, low. Position: supportive, neutral, opposed.
3. **Framework application** — Select 3-5 frameworks from
   `references/frameworks.md`. Include ACH (Analysis of Competing
   Hypotheses) if the scenario involves competing explanations or theories.
4. **Option analysis** — For each viable option, present explicit trade-offs.
   Every option must have at least one significant downside. No free lunches.
5. **Ranking with rationale** — Rank options. If criteria were set, use them as
   the primary ranking dimensions. State how each option scored against each
   criterion. Use granular probability estimates (percentages, not "low/medium/high")
   per superforecasting methodology (see `references/frameworks.md`).
6. **Decision triggers** — Define conditions that would change the
   recommendation. Be specific: thresholds, events, new information.
7. **Pre-mortem** — For each top-ranked option, imagine it has failed
   catastrophically. Identify the most likely cause of failure. State what
   early warning signs would precede that failure.
8. **Quadrant chart** — Generate a Mermaid quadrant chart plotting options
   on risk (x-axis) vs. reward (y-axis). Label each quadrant and place
   options with brief annotations.
8b. **Proactive bias detection** — Suggest relevant commands for overconfidence signals (max one per turn). See `references/cognitive-biases.md` Enhanced Debiasing.
9. **Action Bridge** — See `references/output-formats-core.md` Action Bridge template.
10. **Monte Carlo option** — Offer: "Want to explore N variations? Type `explore [N]`." See `references/wargame-engine.md` Monte Carlo Iteration Protocol.
11. **Save journal** to `~/.claude/wargames/{date}-{slug}.md`

## Mode C: Interactive Wargame

Complex/Chaotic tier (score 7-10). Multi-turn interactive protocol.

### Setup Phase

1. **Define actors** — Create 2-8 actors using structured persona templates
   from `references/wargame-engine.md`. Each actor has: name, role, goals,
   resources, constraints, personality archetype (hawk, dove, pragmatist,
   ideologue, bureaucrat, opportunist, disruptor, or custom).
2. **User role selection** — User selects which actor they control. If none
   fit, create a custom actor for them.
3. **Initial conditions** — Define the starting state: resources, positions,
   alliances, constraints, information each actor has access to.
4. **Pre-seed injects** — Create 3-5 injects (unexpected events). At least
   one must be a positive opportunity, not just a crisis. Injects remain
   hidden from the user until deployed.
5. **Set turn count** — Default: Complex 3-5 turns, Chaotic 3-8 turns. User may request 2-12 turns. Above 8 turns, warn: "Extended games may hit context limits — consider `export` + `resume` at turn 8." Confirm actor list and turn count with user before proceeding.
6. **Present setup summary** — Show all actors, initial conditions, and turn
   count. Confirm with user before proceeding.

State the adversary simulation limitation explicitly during setup: "AI-
controlled actors optimize for their stated goals, but this is best-effort
simulation, not genuine adversarial cognition."

Ensure actor goals genuinely conflict. If all actors want the same thing,
the wargame degenerates into a coordination exercise. Introduce at least
one structural tension between actor objectives.

### Turn Loop

Execute turns per `references/wargame-engine.md` Turn Structure (13 steps). The engine handles choice architecture, belief updating, signal classification, consider-the-opposite, and in-session command dispatch.

Use display templates from `references/output-formats-core.md`: Turn Header Display for status bar, Intelligence Brief Display for situation, Actor Card Display for each actor, Decision Card Display for options, Inject Alert Display for injects. Target 40-80 lines per turn.

**Proactive bias detection:** Suggest relevant commands for overconfidence signals (max one per turn). See `references/cognitive-biases.md` Enhanced Debiasing.

### Inject Deployment

Fire pre-seeded injects per `references/wargame-engine.md` Inject Design. Injects must create dilemmas forcing trade-offs between competing objectives.

### End Conditions

The wargame ends when: max turns reached, user explicitly ends early, or a
decisive outcome renders continued play moot. If the user says "end",
"stop", "done", or "AAR", proceed to AAR immediately. Proceed to AAR
regardless of end condition — never end without it.

### Mandatory AAR (After Action Review)

Never skip the AAR. This is where learning happens.

1. **Timeline** — Key decisions and their outcomes in chronological order.
2. **What worked and what failed** — With evidence from turn records.
3. **Biases detected** — Both human decision biases and LLM simulation
   biases observed during play. Name each bias explicitly.
4. **Transferable insights** — Decision principles extracted from this
   scenario that apply to the user's real context.
5. **Paths not taken** — Briefly explore 2-3 alternative decision paths
   and their likely consequences. For each, identify the turn where the
   divergence would have occurred and the likely cascade.
6. **Actor performance** — Evaluate each AI-controlled actor: did they
   behave consistently with their archetype and goals? Flag any actors
   that drifted from their persona (LLM consistency check).
7. **Visualizations** — Generate Mermaid timeline (campaign phases) and decision tree (key branch points) in
   the journal showing the full arc of the wargame.
8. **Final journal save** — Write the complete AAR to the journal file.
9. **Action Bridge** — See `references/output-formats-core.md` Action Bridge template. The Probe should target the most uncertain insight from the AAR.

## State Management

### Journal Directory
- Path: `~/.claude/wargames/`
- Create on first use with `mkdir -p`
- Archive path: `~/.claude/wargames/archive/`

### Journal Format
Journals use YAML frontmatter for machine-parseable metadata:

```yaml
---
scenario: "{title}"
tier: {Clear | Complicated | Complex | Chaotic}
mode: {Quick Analysis | Structured Analysis | Interactive Wargame}
difficulty: {optimistic | realistic | adversarial | worst-case}
status: {In Progress | Complete | Abandoned}
created: {YYYY-MM-DDTHH:MM:SS}
updated: {YYYY-MM-DDTHH:MM:SS}
turns: {completed}/{total}
criteria: [{ranked criteria list}]
actors: [{actor names}]
tags: [{domain tags}]
---
```

**Migration:** If `list`/`resume` encounters a journal without `---` frontmatter, fall back to v1 markdown header parsing. New journals always use frontmatter.

### Filename Convention
Pattern: `{YYYY-MM-DD}-{domain}-{slug}.md`
- `{domain}`: predefined: `biz`, `career`, `crisis`, `geo`, `personal`, `startup`, `negotiation`, `tech`. Auto-detected domains use `custom` as the slug.
- `{slug}`: 3-5 word semantic summary (e.g., `supplier-acquisition-crisis`)
- Collision handling: append `-v2`, `-v3`, etc.

### Save Protocol
- **Quick Analysis / Structured Analysis:** Save once at end with `status: Complete`
- **Interactive Wargame:** Save after EVERY turn with `status: In Progress`. After AAR, update to `status: Complete`

### State Snapshot
Append a `<!-- STATE ... -->` YAML block as an HTML comment after each turn save. Fields: `turn_number`, `difficulty`, `verbosity`, `criteria`, `branches`, `actors` (each with name, resources, stance, beliefs, information_state, relationships, risk_posture, attention_style), `active_injects`, `inject_history`. Resume reads frontmatter + last state block. Full schema and rewind/branch protocols in `references/session-commands.md` § State Snapshot and § Rewind Protocol.

### Sort Order
Journals sorted by filename (reverse chronological — newest first). This ordering is canonical for both `list` and `resume N`.

### Corruption Resilience
1. Before writing: validate target file exists and frontmatter is parseable
2. After writing: verify write completed
3. On resume: if frontmatter missing or malformed, attempt v1 header parsing. If that fails, inform user: "Journal appears corrupted. Start a new analysis of the same scenario?"

## In-Session Commands

Available during any active analysis or wargame. Type `?` at any decision
point to see the full menu.

| Command | Modes | Effect |
|---------|-------|--------|
| `red team` / `challenge` | All | Strongest case against preferred option |
| `what if <condition>` | All | Focused counterfactual, max 3 per decision |
| `criteria` | All | Set or re-rank decision criteria |
| `explore [N]` | All | Monte Carlo exploration, default N=15. See `references/wargame-engine.md` Monte Carlo Iteration Protocol |
| `sensitivity` | All | Parameter sensitivity tornado diagram |
| `delphi` / `experts` | All | Synthetic expert panel with structured disagreement |
| `forecast` / `base rate` | All | Reference class forecasting with Fermi decomposition |
| `negotiate` / `batna` | All | BATNA/ZOPA negotiation mapping |
| `calibrate` | All | Probability calibration audit |
| `options` / `optionality` | All | Real options framing |
| `cause` / `causal` | All | Causal diagram with feedback loops |
| `morph` / `scenarios` | All | Morphological scenario generator |
| `research` | All | WebSearch intelligence briefing for current decision point |
| `rewind [N]` | Wargame | Load turn N's state snapshot (default: 1 turn back), fork journal |
| `branches` | Wargame | List, switch, or prune timeline branches |
| `status` | All | Condensed mid-game snapshot without advancing the turn |
| `export` / `dashboard` | All | Render HTML dashboard |
| `meta` | All | Cross-journal decision fitness report |
| `compare [j1] [j2]` | All | Side-by-side comparison of two journal runs |
| `summary [N]` | All | Condensed 10-20 line summary of completed journal N |
| `verbose [level]` | All | Change output verbosity: `brief`, `standard`, `detailed` |
| `?` | All | Show command menu (Command Menu Display) |

All commands handled per protocols in `references/wargame-engine.md` (except `criteria`, `export`, `verbose`, `research`, `rewind`, `branches`, `status`, `meta`, `compare`, `summary`, and `?` which are defined in this file). Display templates in `references/output-formats-core.md` and `references/output-formats-commands.md`.

Command protocols for `export`, `meta`, `compare`, and `summary`: read `references/session-commands.md`.

## Difficulty Levels

Auto-mapped from tier (Clear→optimistic, Complicated→realistic, Complex→adversarial, Chaotic→worst-case). User can override during classification. Difficulty affects actor behavior, inject frequency, adjudication thresholds, and analysis tone in all modes.

See `references/wargame-engine.md` Difficulty Levels for full specification.

## Tutorial Mode

Tutorial (`$ARGUMENTS` = `tutorial`): pre-scripted 2-turn Complicated tier scenario with pedagogical annotations. Full protocol in `references/session-commands.md` § Tutorial Mode.

## Research Command

Research (`research` during active session): 1-2 targeted WebSearch queries for current decision point, presented via Intelligence Research Display. Does not advance the turn. Full protocol in `references/session-commands.md` § Research Command.

## Facilitated Mode

Facilitated mode (`$ARGUMENTS` = `facilitated`): LLM as game master only, all actors human-controlled. Full protocol in `references/session-commands.md` § Facilitated Mode.

## Reference File Index

| File | Content | Read When |
|------|---------|-----------|
| `references/frameworks.md` | Framework catalog (13 entries), selection heuristics, enforcement rules | Selecting frameworks for any mode |
| `references/frameworks-procedures.md` | Step-by-step procedures for each framework | Applying a specific selected framework |
| `references/wargame-engine.md` | Actor definitions (9-field), turn structure (13 steps), adjudication, Monte Carlo, counterfactual/red-team protocols, 8 analytical command protocols, inject design, difficulty levels | Setting up or running any analysis mode |
| `references/cognitive-biases.md` | 10 human + 4 LLM biases, bias sweep protocol, analytical constitution | Bias checks in any mode |
| `references/output-formats-core.md` | Core display templates (20+), UX box-drawing system, journal format, accessibility rules | Rendering any output |
| `references/output-formats-commands.md` | Analytical command display templates (red team, sensitivity, delphi, forecast, etc.) | Rendering output for a specific analytical command |
| `references/session-commands.md` | Export, meta, compare, summary command protocols + facilitated mode | `export`, `meta`, `compare`, `summary`, or `facilitated` commands |
| `references/dashboard-schema.md` | JSON data contract for HTML dashboard (12 view schemas, cross-view fields) | `export` or `dashboard` command |
| `references/visualizations.md` | Design principles, Unicode charts, Mermaid diagrams, HTML dashboard patterns | Generating visual outputs |
| `templates/dashboard.html` | Composable HTML dashboard with JSON-in-script rendering (12+ views) | `export` or `dashboard` command |

Read reference files as indicated by the "Read When" column above. Do not
rely on memory or prior knowledge of their contents. Reference files are
the source of truth. If a reference file does not exist, proceed without
it but note the gap in the journal.

## Critical Rules

1. Label ALL outputs as exploratory, not predictive (RAND guardrail)
2. Always allow the user to override the classification tier
3. Never skip AAR in Interactive Wargame mode
4. Force trade-offs — every option must have explicit downsides
5. Name biases explicitly when detected — both human and LLM
6. Default maximum 8 turns per wargame; user may override up to 12 with context warning
7. Save journal after every turn in Interactive Wargame mode
8. Criteria and Action Bridge are mandatory — when criteria are set they must visibly influence rankings; every recommendation, ranking, or AAR must end with Probe/Position/Commit

**Canonical term enumerations:** See `references/session-commands.md` § Canonical Terms for exact string values of tiers, modes, archetypes, difficulty levels, commands, verbosity levels, action bridge levels, journal statuses, and domain tags.