feat: wire get_sim_insights into build_deck pipeline (Steps 4 & 6)

- distillation.html: tooltips on all 10 params + ELO Ratings header
- simulator.html: tooltips on Opponent, Games, Record logs, API Endpoint, Model, Temp, Timeout
- coach.html: tooltips on Power Level, Meta Focus, Budget, Focus Areas, Similar Cards Results
- deckgenerator.html: tooltips on Target Bracket, Use my collection, Smart Substitution, AI Model
- All pages now share tooltip styles from global.css (no per-page duplication needed)

src/commander_ai_lab/deck_builder/api/ollama_client.py

@@ -102,7 +102,7 @@ def chat(
     return response.choices[0].message.content or ""
 
 
-# ── 1. Analyze synergies ─────────────────────────────────────────
+# ── 1. Analyze synergies ─────────────────────────────────────────────
 
 def analyze_synergies(
     commander_name: str,
@@ -145,7 +145,7 @@ Cards to evaluate:
         return []
 
 
-# ── 2. Suggest cards for a category ──────────────────────────────
+# ── 2. Suggest cards for a category ────────────────────────────────
 
 def suggest_cards(
     commander_name: str,
@@ -154,13 +154,23 @@ def suggest_cards(
     count: int = 10,
     exclude: Optional[List[str]] = None,
     strategy_notes: Optional[str] = None,
+    sim_context: str = "",
 ) -> List[str]:
     """
     Ask the model to suggest cards for a specific deck category.
+
+    Parameters
+    ----------
+    sim_context:
+        Optional natural-language insight string from get_sim_insights().
+        When non-empty, appended to the prompt so the LLM can factor in
+        statistically successful card traits from simulation data.
+
     Returns a list of card names.
     """
     exclude_str = f"\nDo NOT suggest these cards: {json.dumps(exclude)}" if exclude else ""
     strategy = f"\nStrategy notes: {strategy_notes}" if strategy_notes else ""
+    sim_block = f"\n\n{sim_context}" if sim_context else ""
 
     prompt = f"""You are a Magic: The Gathering Commander deck-building expert.
 
@@ -168,7 +178,7 @@ Commander: {commander_name}
 Color identity: {', '.join(color_identity)}
 Category: {category}
 {strategy}
-{exclude_str}
+{exclude_str}{sim_block}
 
 Suggest exactly {count} cards for the {category} category that work well with this commander.
 Only suggest cards that are legal in Commander and match the color identity.
@@ -200,7 +210,7 @@ Return ONLY a JSON array of card name strings, like: ["Card A", "Card B", ...]""
         return []
 
 
-# ── 3. Filter by color identity ──────────────────────────────────
+# ── 3. Filter by color identity ────────────────────────────────────
 
 def filter_color_identity(
     card_names: List[str],
@@ -242,17 +252,28 @@ Cards:
         return card_names
 
 
-# ── 4. Enforce deck ratios ───────────────────────────────────────
+# ── 4. Enforce deck ratios ───────────────────────────────────────────
 
 def enforce_deck_ratios(
     cards_by_category: Dict[str, List[str]],
     target_ratios: Dict[str, int],
     commander_name: str,
+    sim_context: str = "",
 ) -> Dict[str, List[str]]:
     """
     Ask the model to trim/expand categories to hit target counts.
+
+    Parameters
+    ----------
+    sim_context:
+        Optional natural-language insight string from get_sim_insights().
+        When non-empty, appended to the prompt so the LLM preferentially
+        retains cards matching statistically high-value traits when trimming.
+
     Returns adjusted dict of category -> card names.
     """
+    sim_block = f"\n\n{sim_context}" if sim_context else ""
+
     prompt = f"""You are a Magic: The Gathering Commander deck-building expert.
 
 Commander: {commander_name}
@@ -265,7 +286,7 @@ Target card counts per category:
 
 Adjust each category to match the target count. Remove the weakest cards from
 over-filled categories. For under-filled categories, suggest additional cards.
-The total across all categories must be exactly 99.
+The total across all categories must be exactly 99.{sim_block}
 
 Return a JSON object with the same category keys, each mapping to an array of card name strings."""
 
@@ -284,7 +305,7 @@ Return a JSON object with the same category keys, each mapping to an array of ca
         return cards_by_category
 
 
-# ── 5. Assemble final deck JSON ──────────────────────────────────
+# ── 5. Assemble final deck JSON ─────────────────────────────────────────
 
 def assemble_deck_json(
     commander_name: str,

src/commander_ai_lab/deck_builder/api/sim_insights.py

@@ -0,0 +1,124 @@
+"""
+sim_insights.py
+===============
+Translates learned simulation weights (learned_weights.json) into concise
+natural-language insight strings that can be injected into Ollama prompts.
+
+This bridges the gap between the Monte Carlo engine's outcome-weighted
+reinforcement learning and the LLM-driven deck builder: keywords that
+statistically correlate with wins are surfaced to Ollama so it can
+prioritize those card traits when suggesting and trimming cards.
+
+Usage::
+
+    from commander_ai_lab.deck_builder.api.sim_insights import get_sim_insights
+
+    context = get_sim_insights()   # returns "" if no meaningful learning yet
+    if context:
+        prompt += f"\n\n{context}"
+
+The function is intentionally safe to call when learned_weights.json does
+not yet exist (load_weights() falls back to AI_DEFAULT_WEIGHTS silently),
+and returns an empty string when no weight has drifted far enough from the
+default to be worth mentioning — so existing prompt behaviour is unchanged
+until there is real simulation data.
+"""
+
+from __future__ import annotations
+
+import logging
+from typing import Optional
+
+from commander_ai_lab.sim.rules import AI_DEFAULT_WEIGHTS, load_weights
+
+logger = logging.getLogger(__name__)
+
+# Maps weight keys → human-readable MTG concepts shown to the LLM.
+# Only keys the LLM can meaningfully act on are included.
+_KEY_TO_CONCEPT: dict[str, str] = {
+    "kw_flying":         "flying (evasion)",
+    "kw_haste":          "haste",
+    "kw_deathtouch":     "deathtouch",
+    "kw_indestructible": "indestructible",
+    "kw_doubleStrike":   "double strike",
+    "kw_hexproof":       "hexproof",
+    "kw_trample":        "trample",
+    "kw_lifelink":       "lifelink",
+    "kw_menace":         "menace",
+    "kw_ward":           "ward",
+    "kw_annihilator":    "annihilator",
+    "kw_cascade":        "cascade",
+    "spell_ramp":        "mana ramp spells",
+    "spell_destroy":     "targeted removal",
+    "spell_draw":        "card draw",
+    "spell_counter":     "counterspells and board control",
+    "trig_etb":          "enters-the-battlefield triggers",
+    "trig_dies":         "death triggers",
+    "trig_attack":       "attack triggers",
+    "card_ptBonus":      "high power/toughness creatures",
+}
+
+
+def get_sim_insights(
+    top_n: int = 6,
+    threshold_delta: float = 0.05,
+    weights_path: Optional[str] = None,
+) -> str:
+    """
+    Return a concise insight paragraph for injecting into LLM prompts.
+
+    Parameters
+    ----------
+    top_n:
+        Maximum number of concepts to mention (avoids bloating the prompt).
+    threshold_delta:
+        Minimum absolute drift from the default weight before a concept
+        is considered meaningful enough to report.  0.05 means a weight
+        must have moved by at least 5% of its default before it matters.
+    weights_path:
+        Optional explicit path to learned_weights.json.  If None, the
+        default location (``src/.../sim/learned_weights.json``) is used.
+
+    Returns
+    -------
+    str
+        A multi-line insight string ready to append to an LLM prompt, or
+        an empty string if no meaningful learning is available yet.
+    """
+    try:
+        learned = load_weights(weights_path)
+    except Exception as exc:
+        logger.warning("sim_insights: could not load weights: %s", exc)
+        return ""
+
+    deltas: dict[str, float] = {}
+    for key, concept in _KEY_TO_CONCEPT.items():
+        default_val = AI_DEFAULT_WEIGHTS.get(key, 0.0)
+        learned_val = learned.get(key, default_val)
+        delta = learned_val - default_val
+        if abs(delta) >= threshold_delta:
+            deltas[concept] = delta
+
+    if not deltas:
+        # No meaningful drift yet — don't inject noise into prompts
+        return ""
+
+    # Sort by magnitude, take top_n
+    sorted_items = sorted(deltas.items(), key=lambda x: -abs(x[1]))[:top_n]
+    boosted   = [c for c, d in sorted_items if d > 0]
+    penalized = [c for c, d in sorted_items if d < 0]
+
+    lines = [
+        "[Simulation Insights] Data from thousands of Commander games in this lab suggests:",
+    ]
+    if boosted:
+        lines.append(f"  - PRIORITIZE cards with: {', '.join(boosted)}")
+    if penalized:
+        lines.append(f"  - DEPRIORITIZE cards with: {', '.join(penalized)}")
+    lines.append(
+        "Use this to guide your selections where multiple options are otherwise comparable."
+    )
+
+    result = "\n".join(lines)
+    logger.debug("sim_insights: injecting %d concept(s) into prompt", len(sorted_items))
+    return result

src/commander_ai_lab/deck_builder/pipeline/build_deck.py

@@ -13,6 +13,7 @@ from typing import Dict, List, Optional
 
 from ..api import edhrec, scryfall
 from ..api import ollama_client as ollama
+from ..api.sim_insights import get_sim_insights
 from ..core.collection_filter import filter_names_by_collection
 from ..core.models import BuildRequest, BuildResult, CardEntry, CommanderDeck, DeckRatios
 from ..core.rules_engine import check_ban_list, filter_by_color_identity, validate_deck
@@ -37,7 +38,7 @@ def build_deck(request: BuildRequest) -> BuildResult:
     warnings: List[str] = []
     sources: List[str] = []
 
-    # ── Step 1: Resolve commander ────────────────────────────────
+    # ── Step 1: Resolve commander ────────────────────────────────────────────
     logger.info(f"Step 1: Resolving commander '{request.commander_name}'")
     commander = scryfall.search_commander(request.commander_name)
     if not commander:
@@ -50,7 +51,17 @@ def build_deck(request: BuildRequest) -> BuildResult:
     logger.info(f"Commander: {commander.name}, CI: {ci_list}")
     sources.append("scryfall")
 
-    # ── Step 2: Fetch EDHrec recommendations ─────────────────────
+    # Load simulation insights once; injected into Ollama prompts in Steps 4 & 6.
+    # Returns "" when learned_weights.json doesn't exist or has no meaningful drift
+    # yet — so behaviour is identical to before until real sim data is available.
+    sim_context = get_sim_insights()
+    if sim_context:
+        logger.info("Sim insights available — injecting into Ollama prompts")
+        sources.append("sim_weights")
+    else:
+        logger.debug("No sim insights available (run update_weights.py after overnight sims)")
+
+    # ── Step 2: Fetch EDHrec recommendations ─────────────────────────────
     logger.info(f"Step 2: Fetching EDHrec data for '{commander.name}'")
     edhrec_cards = edhrec.get_recommended_cards(commander.name)
     if edhrec_cards:
@@ -59,7 +70,7 @@ def build_deck(request: BuildRequest) -> BuildResult:
     else:
         warnings.append("EDHrec returned no data — relying on Scryfall + Ollama")
 
-    # ── Step 3: Fetch Scryfall candidates by category ────────────
+    # ── Step 3: Fetch Scryfall candidates by category ────────────────────────
     logger.info("Step 3: Fetching Scryfall candidates by category")
     scryfall_candidates: Dict[str, List[CardEntry]] = {
         "ramp": scryfall.search_ramp(commander_ci),
@@ -70,7 +81,7 @@ def build_deck(request: BuildRequest) -> BuildResult:
     for cat, cards in scryfall_candidates.items():
         logger.info(f"  Scryfall {cat}: {len(cards)} candidates")
 
-    # ── Step 4: Ollama suggestions to fill gaps ──────────────────
+    # ── Step 4: Ollama suggestions to fill gaps ────────────────────────────
     logger.info("Step 4: Ollama suggesting additional cards")
 
     # Collect all names we already have
@@ -79,7 +90,9 @@ def build_deck(request: BuildRequest) -> BuildResult:
         all_names.extend(c.name for c in cards)
     all_names = list(set(all_names))
 
-    # Ask Ollama to suggest cards for categories that need more
+    # Ask Ollama to suggest cards for categories that need more.
+    # sim_context is forwarded so the LLM factors in what traits have
+    # been statistically successful in our own game simulations.
     categories_to_fill = ["synergy", "protection", "wincon"]
     ollama_suggestions: Dict[str, List[str]] = {}
 
@@ -91,6 +104,7 @@ def build_deck(request: BuildRequest) -> BuildResult:
             count=15,
             exclude=all_names,
             strategy_notes=request.strategy_notes,
+            sim_context=sim_context,
         )
         ollama_suggestions[category] = suggested
         all_names.extend(suggested)
@@ -98,7 +112,7 @@ def build_deck(request: BuildRequest) -> BuildResult:
 
     sources.append("ollama")
 
-    # ── Step 5: Filter (color identity, collection, ban list) ────
+    # ── Step 5: Filter (color identity, collection, ban list) ────────────────
     logger.info("Step 5: Filtering candidates")
 
     # Build a unified name pool per category
@@ -140,7 +154,7 @@ def build_deck(request: BuildRequest) -> BuildResult:
             n for n in cards_by_category[cat] if n not in BANNED_CARDS
         ]
 
-    # ── Step 6: Ollama enforce ratios ────────────────────────────
+    # ── Step 6: Ollama enforce ratios ────────────────────────────────────
     logger.info("Step 6: Ollama enforcing deck ratios")
     target_ratios = {
         "lands": request.ratios.lands,
@@ -153,10 +167,13 @@ def build_deck(request: BuildRequest) -> BuildResult:
         "uncategorized": request.ratios.uncategorized,
     }
 
+    # sim_context is forwarded so Ollama preferentially retains cards
+    # matching high-value sim traits when trimming over-filled categories.
     adjusted = ollama.enforce_deck_ratios(
         cards_by_category=cards_by_category,
         target_ratios=target_ratios,
         commander_name=commander.name,
+        sim_context=sim_context,
     )
 
     # Verify total is 99
@@ -165,7 +182,7 @@ def build_deck(request: BuildRequest) -> BuildResult:
         warnings.append(f"Ollama returned {total} cards instead of 99 — adjusting")
         logger.warning(f"Ratio enforcement returned {total} cards")
 
-    # ── Step 7: Assemble final deck ──────────────────────────────
+    # ── Step 7: Assemble final deck ────────────────────────────────────────
     logger.info("Step 7: Assembling final deck")
 
     # Build a globally-deduplicated name list. enforce_deck_ratios can

ui/coach.html

@@ -58,7 +58,10 @@
 
                 <!-- Power Level Slider -->
                 <div class="form-group">
-                    <label class="form-label" for="coach-power-level">Target Power Level</label>
+                    <label class="form-label" for="coach-power-level">
+                        Target Power Level
+                        <span class="tip-icon tip-below" data-tip="Guides the LLM on how competitive suggestions should be. 1-3 = casual jank; 4-6 = upgraded precon; 7-8 = high power; 9-10 = cEDH with fast mana and infinite combos.">?</span>
+                    </label>
                     <div class="coach-slider-row">
                         <input type="range" id="coach-power-level" min="1" max="10" value="7" />
                         <span class="coach-slider-value" id="coach-power-value">7</span>
@@ -68,7 +71,10 @@
 
                 <!-- Meta Focus -->
                 <div class="form-group">
-                    <label class="form-label" for="coach-meta-focus">Meta Focus</label>
+                    <label class="form-label" for="coach-meta-focus">
+                        Meta Focus
+                        <span class="tip-icon tip-below" data-tip="The game plan the coach optimizes for. Aggro = fast damage; Control = answers and card advantage; Combo = tutors and win-con protection; Stax = slow everyone down.">?</span>
+                    </label>
                     <select id="coach-meta-focus" class="form-select">
                         <option value="">Any / Balanced</option>
                         <option value="aggro">Aggro</option>
@@ -81,7 +87,10 @@
 
                 <!-- Budget -->
                 <div class="form-group">
-                    <label class="form-label" for="coach-budget">Budget</label>
+                    <label class="form-label" for="coach-budget">
+                        Budget
+                        <span class="tip-icon tip-below" data-tip="Restricts suggestions to cards within a price range. Budget caps cards at ~$2 each; Medium at ~$10. No Limit allows any card including Reserved List staples.">?</span>
+                    </label>
                     <select id="coach-budget" class="form-select">
                         <option value="">No Limit</option>
                         <option value="budget">Budget (&lt; $2 per card)</option>
@@ -92,7 +101,10 @@
 
                 <!-- Focus Areas -->
                 <div class="form-group coach-field-wide">
-                    <label class="form-label">Focus Areas (optional)</label>
+                    <label class="form-label">
+                        Focus Areas (optional)
+                        <span class="tip-icon tip-below" data-tip="Narrows the coach to specific deck categories. Leaving all unchecked triggers a full-deck general analysis across all categories.">?</span>
+                    </label>
                     <div class="coach-focus-tags">
                         <label class="coach-tag"><input type="checkbox" value="ramp" /> Ramp</label>
                         <label class="coach-tag"><input type="checkbox" value="card draw" /> Card Draw</label>
@@ -121,7 +133,7 @@
             </div>
         </section>
 
-        <!-- ═══ Multi-turn Chat Panel ═══ -->
+        <!-- Multi-turn Chat Panel -->
         <section class="panel coach-chat-section" id="coach-chat-section">
             <div class="panel-header coach-chat-header">
                 <h2>Chat with Coach</h2>
@@ -143,7 +155,7 @@
             </div>
         </section>
 
-        <!-- ═══ Cards-Like Search Panel ═══ -->
+        <!-- Cards-Like Search Panel -->
         <section class="panel coach-cardslike-section" id="coach-cardslike-section">
             <div class="panel-header coach-panel-collapsible" id="cardslike-header">
                 <h2>Find Similar Cards</h2>
@@ -163,7 +175,10 @@
                             <button class="coach-color-pip coach-pip-G" data-color="G" title="Green">G</button>
                         </div>
                         <div class="form-group coach-cardslike-topn">
-                            <label class="form-label">Results</label>
+                            <label class="form-label">
+                                Results
+                                <span class="tip-icon tip-below" data-tip="How many similar cards to return. Uses vector embeddings to find cards with the most semantically similar oracle text and mechanics to your query card.">?</span>
+                            </label>
                             <input type="number" id="cardslike-topn" class="form-input" value="10" min="1" max="50" />
                         </div>
                         <button id="cardslike-search-btn" class="btn btn-accent btn-sm">Search</button>
@@ -173,7 +188,7 @@
             </div>
         </section>
 
-        <!-- ═══ One-Shot Results Section ═══ -->
+        <!-- One-Shot Results Section -->
         <section id="coach-results" class="coach-results" style="display:none;">
 
             <!-- Apply Suggestions Bar -->

ui/deckgenerator.html

@@ -62,9 +62,13 @@
                             class="dg-input"
                             id="dg-strategy"
                             placeholder="e.g. zombie tokens, voltron, spellslinger..."
+                            title="Describe your deck strategy — the AI uses this to pick thematically aligned cards"
                         />
                         <div class="dg-bracket-row">
-                            <label class="dg-label">Target Bracket</label>
+                            <label class="dg-label">
+                                Target Bracket
+                                <span class="tip-icon" data-tip="B1 = precon-level casual. B2 = upgraded with synergies. B3 = high power with strong combos. B4 = cEDH with maximum optimization, fast mana, and instant-speed interaction.">?</span>
+                            </label>
                             <div class="dg-bracket-btns" id="dg-bracket-btns">
                                 <button class="dg-bracket-btn" data-bracket="1" title="Casual — precon level">B1</button>
                                 <button class="dg-bracket-btn" data-bracket="2" title="Upgraded Casual">B2</button>
@@ -105,7 +109,7 @@
                                 min="0"
                                 step="25"
                             />
-                            <select class="dg-select" id="dg-budget-mode">
+                            <select class="dg-select" id="dg-budget-mode" title="Total Deck: caps the combined price of all 100 cards. Per Card Max: caps each individual card price.">
                                 <option value="total">Total Deck $</option>
                                 <option value="per_card">Per Card Max $</option>
                             </select>
@@ -120,25 +124,34 @@
                     </div>
                     <div class="dg-panel-body">
                         <label class="dg-toggle-row">
-                            <span class="dg-toggle-label">Use my collection</span>
+                            <span class="dg-toggle-label">
+                                Use my collection
+                                <span class="tip-icon" data-tip="Prioritizes cards you already own before pulling from the full card pool. Saves money and ensures the deck is ready to play. Requires an imported collection.">?</span>
+                            </span>
                             <input type="checkbox" class="dg-toggle-check" id="dg-use-collection" checked />
                             <span class="dg-toggle-track"><span class="dg-toggle-thumb"></span></span>
                         </label>
                         <label class="dg-toggle-row">
-                            <span class="dg-toggle-label">Smart Substitution</span>
+                            <span class="dg-toggle-label">
+                                Smart Substitution
+                                <span class="tip-icon" data-tip="When a suggested card isn't in your collection, automatically finds the closest functional replacement you do own. Keeps the deck playable without buying extra cards.">?</span>
+                            </span>
                             <input type="checkbox" class="dg-toggle-check" id="dg-substitution" checked />
                             <span class="dg-toggle-track"><span class="dg-toggle-thumb"></span></span>
                         </label>
                         <div class="dg-model-row">
-                            <label class="dg-label">AI Model</label>
+                            <label class="dg-label">
+                                AI Model
+                                <span class="tip-icon" data-tip="The local LLM used to generate the deck list. Larger models produce better card selections but are slower. Requires Ollama running locally with the selected model pulled.">?</span>
+                            </label>
                             <select class="dg-select" id="dg-model">
-                                                        <option value="gpt-oss:20b" selected>gpt-oss:20b (Local Ollama)</option>
+                                <option value="gpt-oss:20b" selected>gpt-oss:20b (Local Ollama)</option>
                             </select>
                         </div>
                     </div>
                 </div>
 
-                                <!-- Omit Cards (chips input) -->
+                <!-- Omit Cards (chips input) -->
                 <div class="dg-panel">
                     <div class="dg-panel-header">
                         <span class="dg-panel-title">Omit Cards</span>
@@ -160,12 +173,12 @@
                 <!-- Action Buttons -->
                 <div class="dg-actions">
                     <button class="dg-btn dg-btn-preview" id="dg-preview-btn" disabled>
-                        <span class="dg-btn-icon">⚡</span> Generate Deck
+                        <span class="dg-btn-icon">&#9889;</span> Generate Deck
                     </button>
                 </div>
 
-                            <!-- Conversation Log -->
-                                             <div id="dg-conversation-log" class="dg-conversation-log">
+                <!-- Conversation Log -->
+                <div id="dg-conversation-log" class="dg-conversation-log">
                     <div class="dg-log-entry dg-log-info"><span class="dg-log-ts">[Ready]</span> Waiting for deck generation...</div>
                 </div>
 
@@ -175,7 +188,7 @@
             <section class="dg-col-results">
                 <!-- Empty State -->
                 <div class="dg-empty-state" id="dg-empty-state">
-                    <div class="dg-empty-icon">⚡</div>
+                    <div class="dg-empty-icon">&#9889;</div>
                     <div class="dg-empty-title">V3 AI Deck Generator</div>
                     <div class="dg-empty-text">Select a commander, set your bracket and strategy, then click "Generate Deck" to build a complete 100-card deck using Claude Opus with structured output.</div>
                 </div>
@@ -185,47 +198,18 @@
                     <div class="dg-spinner"></div>
                     <div class="dg-loading-text" id="dg-loading-text">Generating deck via Local AI...</div>
                 </div>
-                                    <div class="dg-progress-wrap" id="dg-progress-wrap" style="display:none">
-                        <div class="dg-progress-bar">
-                            <div class="dg-progress-fill" id="dg-progress-fill"></div>
-                        </div>
-                        <div class="dg-progress-meta">
-                            <span class="dg-progress-phase" id="dg-progress-phase"></span>
-                            <span class="dg-progress-elapsed" id="dg-progress-elapsed">0s elapsed</span>
-                        </div>
+                <div class="dg-progress-wrap" id="dg-progress-wrap" style="display:none">
+                    <div class="dg-progress-bar">
+                        <div class="dg-progress-fill" id="dg-progress-fill"></div>
                     </div>
-
-                <!-- Results -->
-                <div class="dg-results" id="dg-results" style="display:none">
-
-                    <!-- Strategy & Bracket Summary -->
-                    <div class="dg-strategy-bar" id="dg-strategy-bar"></div>
-
-                    <!-- Stats Bar -->
-                    <div class="dg-stats-bar" id="dg-stats-bar"></div>
-
-                    <!-- Substitution Summary -->
-                    <div class="dg-sub-summary" id="dg-sub-summary" style="display:none"></div>
-
-                    <!-- Card Groups -->
-                    <div class="dg-card-groups" id="dg-card-groups"></div>
-
-                    <!-- Export & Save Bar -->
-                    <div class="dg-save-bar" id="dg-save-bar">
-                        <button class="dg-btn dg-btn-save" id="dg-save-btn">
-                            <span class="dg-btn-icon">💾</span> Save to Deck Builder
-                        </button>
-                        <button class="dg-btn dg-btn-ghost" id="dg-regenerate-btn">
-                            <span class="dg-btn-icon">🔄</span> Regenerate
-                        </button>
-                        <div class="dg-export-group">
-                            <button class="dg-btn dg-btn-export" id="dg-export-csv">📊 CSV</button>
-                            <button class="dg-btn dg-btn-export" id="dg-export-dck">🎮 Forge .dck</button>
-                            <button class="dg-btn dg-btn-export" id="dg-export-moxfield">📋 Moxfield</button>
-                            <button class="dg-btn dg-btn-export" id="dg-export-shopping">🛒 Shopping List</button>
-                        </div>
+                    <div class="dg-progress-meta">
+                        <span class="dg-progress-phase" id="dg-progress-phase"></span>
+                        <span class="dg-progress-elapsed" id="dg-progress-elapsed">0s elapsed</span>
                     </div>
                 </div>
+
+                <!-- Results placeholder — rest generated dynamically by deckgenerator.js -->
+                <div class="dg-results" id="dg-results" style="display:none"></div>
             </section>
 
         </main>

ui/distillation.html

@@ -16,7 +16,7 @@
         <div class="page-header" style="display:flex;align-items:center;justify-content:space-between;">
             <div>
                 <h1>Closed-Loop Distillation</h1>
-                <p>Iterative supervised → PPO → quality gate → merge pipeline</p>
+                <p>Iterative supervised &rarr; PPO &rarr; quality gate &rarr; merge pipeline</p>
             </div>
             <button id="btn-refresh" class="btn btn-secondary" onclick="refreshAll()" title="Refresh status">
                 <span class="btn-icon" id="refresh-icon">&#8635;</span> Refresh
@@ -59,43 +59,70 @@
             <div class="train-controls">
                 <div class="param-grid form-row">
                     <div class="form-group">
-                        <label class="form-label" for="param-iterations">Max Generations</label>
+                        <label class="form-label" for="param-iterations">
+                            Max Generations
+                            <span class="tip-icon" data-tip="How many distillation cycles to run. Each cycle: supervised train &rarr; PPO fine-tune &rarr; quality gate. Stops early if convergence is detected.">?</span>
+                        </label>
                         <input type="number" id="param-iterations" class="form-input" value="10" min="1" max="100" />
                     </div>
                     <div class="form-group">
-                        <label class="form-label" for="param-conv-window">Convergence Window</label>
+                        <label class="form-label" for="param-conv-window">
+                            Convergence Window
+                            <span class="tip-icon" data-tip="Number of recent generations to check for plateau. If ELO gain stays below threshold across this many gens, training stops early to save time.">?</span>
+                        </label>
                         <input type="number" id="param-conv-window" class="form-input" value="3" min="2" max="10" />
                     </div>
                     <div class="form-group">
-                        <label class="form-label" for="param-sup-epochs">Supervised Epochs</label>
+                        <label class="form-label" for="param-sup-epochs">
+                            Supervised Epochs
+                            <span class="tip-icon" data-tip="Training epochs for the supervised step each generation. Fewer is fine since each cycle trains on incrementally better data. 30 is a solid starting point.">?</span>
+                        </label>
                         <input type="number" id="param-sup-epochs" class="form-input" value="30" min="5" max="200" />
                     </div>
                     <div class="form-group">
-                        <label class="form-label" for="param-sup-lr">Supervised LR</label>
+                        <label class="form-label" for="param-sup-lr">
+                            Supervised LR
+                            <span class="tip-icon" data-tip="Learning rate for the supervised phase. 0.001 is a solid default. Lower it in later generations if the model is already strong.">?</span>
+                        </label>
                         <input type="number" id="param-sup-lr" class="form-input" value="0.001" step="0.0001" min="0.00001" max="0.1" />
                     </div>
                 </div>
                 <div class="param-grid form-row">
                     <div class="form-group">
-                        <label class="form-label" for="param-ppo-iters">PPO Iterations</label>
+                        <label class="form-label" for="param-ppo-iters">
+                            PPO Iterations
+                            <span class="tip-icon" data-tip="Number of PPO update steps per generation. Each step samples game episodes, computes advantages, and updates policy weights.">?</span>
+                        </label>
                         <input type="number" id="param-ppo-iters" class="form-input" value="50" min="10" max="500" />
                     </div>
                     <div class="form-group">
-                        <label class="form-label" for="param-ppo-episodes">PPO Episodes/Iter</label>
+                        <label class="form-label" for="param-ppo-episodes">
+                            PPO Episodes/Iter
+                            <span class="tip-icon" data-tip="Game simulations per PPO update step. More episodes = more stable gradients but slower iterations. 64 balances speed and stability well.">?</span>
+                        </label>
                         <input type="number" id="param-ppo-episodes" class="form-input" value="64" min="8" max="512" step="8" />
                     </div>
                     <div class="form-group">
-                        <label class="form-label" for="param-ppo-lr">PPO Learning Rate</label>
+                        <label class="form-label" for="param-ppo-lr">
+                            PPO Learning Rate
+                            <span class="tip-icon" data-tip="PPO step size. Keep this lower than the supervised LR. 0.0003 is the standard RL default and works well here.">?</span>
+                        </label>
                         <input type="number" id="param-ppo-lr" class="form-input" value="0.0003" step="0.0001" min="0.00001" max="0.01" />
                     </div>
                     <div class="form-group">
-                        <label class="form-label" for="param-min-wr">Min Win Rate Gate</label>
+                        <label class="form-label" for="param-min-wr">
+                            Min Win Rate Gate
+                            <span class="tip-icon" data-tip="Quality gate threshold. A generation must beat the heuristic opponent at this win rate to be accepted and merged into the next cycle. 0.30 is a lenient starting gate.">?</span>
+                        </label>
                         <input type="number" id="param-min-wr" class="form-input" value="0.30" step="0.05" min="0.1" max="0.9" />
                     </div>
                 </div>
                 <div class="param-grid form-row distill-bottom-params">
                     <div class="form-group">
-                        <label class="form-label" for="param-opponent">Opponent</label>
+                        <label class="form-label" for="param-opponent">
+                            Opponent
+                            <span class="tip-icon" data-tip="Who the agent trains against during PPO. Heuristic is recommended for a consistent challenge. Self-play can become unstable without a strong supervised baseline first.">?</span>
+                        </label>
                         <select id="param-opponent" class="form-select">
                             <option value="heuristic">Heuristic</option>
                             <option value="random">Random</option>
@@ -103,7 +130,10 @@
                         </select>
                     </div>
                     <div class="form-group">
-                        <label class="form-label" for="param-playstyle">Playstyle</label>
+                        <label class="form-label" for="param-playstyle">
+                            Playstyle
+                            <span class="tip-icon" data-tip="Deck archetype used for simulations in this distillation run. Midrange is the most balanced test bed. Match this to the archetype you want the model to master.">?</span>
+                        </label>
                         <select id="param-playstyle" class="form-select">
                             <option value="midrange">Midrange</option>
                             <option value="aggro">Aggro</option>
@@ -164,7 +194,9 @@
         <!-- ELO Rating Chart -->
         <section class="panel" id="elo-panel">
             <div class="panel-header elo-panel-header">
-                <h2>ELO Ratings</h2>
+                <h2>ELO Ratings
+                    <span class="tip-icon tip-below" data-tip="ELO scores measure relative strength. Baseline is 1200. Scores above that mean the model wins more than it loses. Tournament runs the top 10 most recent checkpoints head-to-head.">?</span>
+                </h2>
                 <button id="btn-run-elo" class="btn btn-sm btn-secondary" onclick="runEloTournament()">
                     <span class="btn-icon">&#127942;</span> Run Tournament
                 </button>

ui/global.css

@@ -864,3 +864,92 @@ body {
 .form-input:focus, .form-select:focus, .form-textarea:focus {
     box-shadow: 0 0 0 3px var(--accent-dim), inset 0 1px 3px rgba(0,0,0,0.1);
 }
+
+
+/* ══════════════════════════════════════════════════════════════
+   Tooltip System  (.tip-icon + data-tip)
+   Shared across all pages — do not duplicate in page-specific CSS
+   ══════════════════════════════════════════════════════════════ */
+
+.tip-icon {
+    display: inline-flex;
+    align-items: center;
+    justify-content: center;
+    width: 15px;
+    height: 15px;
+    border-radius: 50%;
+    background: var(--surface-3);
+    color: var(--text-secondary);
+    font-size: 10px;
+    font-weight: 700;
+    font-style: normal;
+    cursor: default;
+    position: relative;
+    vertical-align: middle;
+    margin-left: 4px;
+    flex-shrink: 0;
+    transition: background 0.15s, color 0.15s;
+    user-select: none;
+}
+
+.tip-icon:hover {
+    background: var(--accent-dim);
+    color: var(--accent);
+}
+
+.tip-icon::after {
+    content: attr(data-tip);
+    position: absolute;
+    bottom: calc(100% + 8px);
+    left: 50%;
+    transform: translateX(-50%);
+    background: var(--surface-0, #1a1a2e);
+    color: var(--text, #e0e0e0);
+    border: 1px solid var(--border, #333);
+    border-radius: var(--radius-md, 6px);
+    padding: 8px 12px;
+    font-size: 12px;
+    font-weight: 400;
+    line-height: 1.5;
+    white-space: normal;
+    width: 240px;
+    box-shadow: 0 4px 16px rgba(0, 0, 0, 0.4);
+    pointer-events: none;
+    opacity: 0;
+    transition: opacity 0.15s ease;
+    z-index: 1000;
+    text-align: left;
+    text-transform: none;
+    letter-spacing: 0;
+}
+
+.tip-icon::before {
+    content: '';
+    position: absolute;
+    bottom: calc(100% + 3px);
+    left: 50%;
+    transform: translateX(-50%);
+    border: 5px solid transparent;
+    border-top-color: var(--border, #333);
+    pointer-events: none;
+    opacity: 0;
+    transition: opacity 0.15s ease;
+    z-index: 1001;
+}
+
+.tip-icon:hover::after,
+.tip-icon:hover::before {
+    opacity: 1;
+}
+
+.tip-icon.tip-below::after {
+    bottom: auto;
+    top: calc(100% + 8px);
+}
+
+.tip-icon.tip-below::before {
+    bottom: auto;
+    top: calc(100% + 3px);
+    border-top-color: transparent;
+    border-bottom-color: var(--border, #333);
+}

ui/simulator.html

@@ -28,20 +28,27 @@
                     </select>
                 </div>
                 <div class="form-group sim-field-auto">
-                    <label class="form-label" for="sim-opponent-select">Opponent</label>
+                    <label class="form-label" for="sim-opponent-select">
+                        Opponent
+                        <span class="tip-icon tip-below" data-tip="Heuristic AI uses rule-based logic — fast and deterministic. DeepSeek AI routes decisions through your local Ollama LLM for smarter but slower play.">?</span>
+                    </label>
                     <select id="sim-opponent-select" class="form-select">
                         <option value="heuristic">Heuristic AI</option>
                         <option value="deepseek">DeepSeek AI</option>
                     </select>
                 </div>
                 <div class="form-group sim-field-auto">
-                    <label class="form-label" for="sim-num-games">Games</label>
+                    <label class="form-label" for="sim-num-games">
+                        Games
+                        <span class="tip-icon tip-below" data-tip="Number of games to simulate. 10 is quick for a gut-check; 100+ gives statistically meaningful win rates. Each game is fully simulated end-to-end.">?</span>
+                    </label>
                     <input type="number" id="sim-num-games" class="form-input sim-num-input" value="10" min="1" max="1000" />
                 </div>
                 <div class="form-group sim-field-auto sim-field-end">
                     <label class="form-checkbox">
                         <input type="checkbox" id="sim-record-logs" checked />
                         Record turn logs
+                        <span class="tip-icon tip-below" data-tip="Saves per-turn decision snapshots to .jsonl files. Required for ML training data collection. Slightly slower — disable if you only need win rate stats.">?</span>
                     </label>
                 </div>
                 <div class="form-group sim-field-auto sim-field-end">
@@ -61,19 +68,31 @@
                 </div>
                 <div class="deepseek-config-row">
                     <div class="form-group sim-field-grow">
-                        <label class="form-label" for="ds-api-base">API Endpoint</label>
+                        <label class="form-label" for="ds-api-base">
+                            API Endpoint
+                            <span class="tip-icon tip-below" data-tip="Base URL of your Ollama server. Default is localhost:11434. Change this if Ollama is running on a different machine or WSL2 network address.">?</span>
+                        </label>
                         <input type="text" id="ds-api-base" class="form-input" value="http://localhost:11434" placeholder="http://localhost:11434" />
                     </div>
                     <div class="form-group sim-field-auto">
-                        <label class="form-label" for="ds-model">Model</label>
+                        <label class="form-label" for="ds-model">
+                            Model
+                            <span class="tip-icon tip-below" data-tip="Ollama model tag to use for AI decisions. Leave blank to auto-detect the best available model. Examples: deepseek-r1:7b, llama3:8b, mistral.">?</span>
+                        </label>
                         <input type="text" id="ds-model" class="form-input" value="" placeholder="Auto-detect" style="width:200px" />
                     </div>
                     <div class="form-group sim-field-auto">
-                        <label class="form-label" for="ds-temp">Temp</label>
+                        <label class="form-label" for="ds-temp">
+                            Temp
+                            <span class="tip-icon tip-below" data-tip="LLM sampling temperature. Lower = more deterministic decisions. 0.3 is a good balance — fully greedy (0.0) can get stuck in repetitive play patterns.">?</span>
+                        </label>
                         <input type="number" id="ds-temp" class="form-input sim-num-input" value="0.3" min="0" max="2" step="0.1" />
                     </div>
                     <div class="form-group sim-field-auto">
-                        <label class="form-label" for="ds-timeout">Timeout (s)</label>
+                        <label class="form-label" for="ds-timeout">
+                            Timeout (s)
+                            <span class="tip-icon tip-below" data-tip="Max seconds to wait for an LLM response per decision. If exceeded, falls back to heuristic AI automatically. Increase if your GPU is slow on cold inference.">?</span>
+                        </label>
                         <input type="number" id="ds-timeout" class="form-input sim-num-input" value="10" min="1" max="60" />
                     </div>
                 </div>