Agent-almanac build-tcg-deck
git clone https://github.com/pjt222/agent-almanac
T=$(mktemp -d) && git clone --depth=1 https://github.com/pjt222/agent-almanac "$T" && mkdir -p ~/.claude/skills && cp -r "$T/i18n/caveman-ultra/skills/build-tcg-deck" ~/.claude/skills/pjt222-agent-almanac-build-tcg-deck-452e0d && rm -rf "$T"
i18n/caveman-ultra/skills/build-tcg-deck/SKILL.mdBuild TCG Deck
Construct TCG deck archetype → final optimization. Works across Pokemon TCG, MTG, FaB, other major TCGs.
Use When
- New deck for tournament format or casual
- Adapt existing deck to changed meta
- Eval whether new card/set warrants change
- Teach deck construction principles
- Convert concept → tournament-ready list
In
- Required: Game (Pokemon TCG, MTG, FaB, etc.)
- Required: Format (Standard, Expanded, Modern, Legacy, Blitz, etc.)
- Required: Goal (competitive, casual, budget)
- Optional: Preferred archetype (aggro, control, combo, midrange)
- Optional: Budget constraints
- Optional: Current meta (top decks, expected field)
Do
Step 1: Define Archetype
Choose strategic identity.
- ID available archetypes in format:
- Aggro: Early pressure + efficient attackers
- Control: Answer threats, win late via card advantage
- Combo: Assemble card combos → powerful synergy / instant wins
- Midrange: Flexible, shifts aggro ↔ control
- Tempo: Resource advantage via efficient timing + disruption
- Select based on:
- Playstyle
- Meta positioning (what beats top?)
- Budget (combo needs specific expensive)
- Format legality (bans, rotation)
- ID 1-2 primary win conditions:
- How does deck actually win?
- Ideal game state to reach?
- State archetype + win condition clearly
→ Clear archetype + win conditions. Specific enough to guide selection, flexible to adapt.
If err: No archetype feels right → start w/ strongest individual cards, let archetype emerge from pool. Sometimes best deck built around a card, not concept.
Step 2: Build Core
Select cards defining strategy.
- Core engine (12-20 cards depending on game):
- Directly enable win condition
- Max legal copies
- Non-negotiable — deck fails w/o
- Support (8-15):
- Find/protect core
- Draw/search for consistency
- Protection (counters, shields, removal)
- Interaction (8-12):
- Removal for opponent threats
- Disruption for opponent strategy
- Defensive opts appropriate to format
- Resource base (game-specific):
- MTG: Lands (24-26 for 60-card, 16-17 for 40-card)
- Pokemon: Energy (8-12 basic + special)
- FaB: Pitch value distribution (balance red/yellow/blue)
→ Complete list at/near min deck size. Every card has role (core, support, interaction, resource).
If err: Exceeds format size → cut weakest support first. Core needs too many (>25) → strategy too fragile, simplify win condition.
Step 3: Analyze Curve
Verify resource distribution supports strategy.
- Plot mana/energy/cost curve:
- Count cards at each cost (0, 1, 2, 3, 4, 5+)
- Match archetype:
- Aggro: peaks 1-2, drops after 3
- Midrange: peaks 2-3, moderate at 4-5
- Control: flatter, more high-cost finishers
- Combo: concentrated at combo-piece costs
- Check color/type distribution (MTG: color balance; Pokemon: energy coverage):
- Resource base can reliably cast on curve?
- Color-intensive cards need dedicated support?
- Verify card type balance:
- Enough creatures/attackers for pressure
- Enough spells/trainers for interaction + consistency
- No critical category missing
- Adjust if curve doesn't support
→ Smooth curve → deck executes strategy on time. Aggro fast, control survives early, combo assembles on schedule.
If err: Lumpy (too many expensive, not enough early) → swap expensive support for cheaper. Curve > any individual card.
Step 4: Meta Positioning
Eval vs expected field.
- ID top 5 decks in current meta (tournament results, tier lists)
- Each top deck:
- Favorable: Strategy counters theirs (+1)
- Even: No structural advantage (0)
- Unfavorable: Theirs counters yours (-1)
- Calc expected win rate vs field:
- Weight by opponent meta share
- 60%+ vs top 5 = well-positioned
- Poor positioning → consider:
- Switch interaction to target worst matchups
- Sideboard (if format allows) for unfavorable
- Whether diff archetype better positioned
→ Clear picture of where deck sits. Favorable + unfavorable matchups ID'd w/ specific reasons.
If err: Meta data unavailable → focus on versatility, interact w/ multiple strategies vs optimizing for one matchup.
Step 5: Sideboard
Construct sideboard/side deck for format adaptation (if applicable).
- Each unfavorable matchup (Step 4):
- 2-4 cards significantly improve
- High-impact, not marginal
- Each sideboard card, know:
- What matchup(s) it comes in against
- What it replaces from main
- Whether bringing it changes curve significantly
- Verify sideboard ≤ format limits (MTG: 15, FaB: varies)
- No sideboard card only relevant vs one fringe deck
- Each slot covers ≥2 matchups if possible
→ Focused sideboard meaningfully improves worst matchups w/o diluting main.
If err: Sideboard can't fix worst matchups → deck poorly positioned in meta. Core strategy may need adjust, not sideboard patches.
Check
- Archetype + win conditions clearly defined
- Format legality met (bans, rotation, card count)
- Every card has defined role (core, support, interaction, resource)
- Curve supports strategy speed
- Resource base reliably casts on curve
- Meta matchups evaluated w/ specific reasoning
- Sideboard targets worst matchups w/ clear swap plans
- Budget satisfied (if applicable)
Traps
- Too many win conditions: 3 ways to win → none done well. Focus 1-2
- Curve blindness: Powerful expensive cards w/o checking if deck casts on time
- Ignore meta: Building in vacuum. Best in theory loses to most common in practice
- Emotional inclusion: Pet card not serving strategy. Every slot earns place
- Sideboard afterthought: Last w/ leftover. Sideboard = part of deck, not appendix
- Over-teching: Narrow answers to specific decks vs proactive strategy
→
— card condition assessment for tournament legality + collection valuegrade-tcg-card
— inventory mgmt for tracking which cards availablemanage-tcg-collection