Agent skill

aoc

Solve Advent of Code puzzles, algorithm challenges, and competitive programming problems. Activate when user provides AoC problem context/input, mentions solving puzzles/challenges, asks about algorithm selection (BFS, DFS, DP, etc.), or needs help with parsing structured input.

Stars 163
Forks 31

Install this agent skill to your Project

npx add-skill https://github.com/majiayu000/claude-skill-registry/tree/main/skills/development/aoc

SKILL.md

Advent of Code Solver

Language-agnostic problem-solving with TDD and correctness-first approach.

Workflow

1. READ      → Study problem + examples (examples are your spec)
2. PARSE     → Extract data structures from input
3. TEST      → Write tests from example input/output
4. IMPLEMENT → Minimal code to pass
5. RUN       → Execute on real input
6. ADAPT     → Refactor for Part 2

Solution Architecture

parse(input) → data structure
part1(data)  → answer
part2(data)  → answer

Parse once. Solve both parts. Test each function independently.

Algorithm Selection

Scenario Algorithm
Unweighted shortest path BFS
Path existence / exhaustive DFS
Weighted shortest path Dijkstra
Weighted + good heuristic A*
"After N iterations..." (huge N) Cycle detection
"Find minimum X such that..." Binary search
"Count ways..." / "Min/max..." Dynamic programming
Connected regions Flood fill

Deep dive: See algorithms.md

Input Patterns

Format Approach
Numbers in text Regex -?\d+
Grid of chars 2D array or dict by coords
Blank-line groups Split on \n\n first
Key-value pairs Parse into map/dict
Instructions/opcodes Pattern match each line

Grids: Use (row, col) with row↓. Sparse dict for infinite/sparse grids. Directions: UP=(-1,0), DOWN=(1,0), LEFT=(0,-1), RIGHT=(0,1)

Deep dive: See parsing.md

Part 2 Patterns

  1. Scale up → Optimize algorithm
  2. Add dimensions → 2D → 3D/4D
  3. Many iterations → Find cycle, skip ahead
  4. Reverse question → "Find X" → "Given X, find Y"
  5. Add constraints → New rules or edge cases

Debugging

  • Print intermediate state at each step
  • Compare with example walkthrough
  • Add assertions for every assumption
  • Test parsing separately from logic
  • Binary search on input size to isolate failures

Complexity Targets

Input Size Target
n ≤ 20 O(2^n) OK
n ≤ 500 O(n³) OK
n ≤ 10,000 O(n²) OK
n ≤ 1,000,000 O(n log n)
n > 1,000,000 O(n) or O(log n)

References

  • algorithms.md - Graph traversal, DP, cycle detection, search
  • parsing.md - Input formats, grids, coordinates, hex grids
  • reference.md - Data structures, optimization, anti-patterns

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