acm-icpc-problem-setting_skill

This skill helps you design high-quality ACM-ICPC style problems by guiding statement writing, test data generation, and contest organization end-to-end.
  • Shell

2

GitHub Stars

1

Bundled Files

2 months ago

Catalog Refreshed

3 months ago

First Indexed

Readme & install

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Installation

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npx veilstrat add skill lihaoze123/my-claude-code --skill acm-icpc-problem-setting

  • SKILL.md3.0 KB

Overview

This skill helps craft and deliver high-quality algorithm competition problems for ACM-ICPC, CCPC, Codeforces and similar contests. It guides you from idea conception through statement writing, test data generation, validators, and contest organization. The focus is practical: clarity, correctness, and reproducible test infrastructure.

How this skill works

The skill inspects every phase of problem preparation: idea originality, formal statement completeness, constraint and sample coverage, and test data quality. It provides templates and examples for testlib-based generators and basic checkers, plus guidance on time/memory limits and subtask design. It also highlights platform-specific workflows and common anti-patterns to stop and fix.

When to use it

  • Designing new contest problems or problem sets
  • Writing formal problem statements and LaTeX templates
  • Generating and validating test data with testlib
  • Implementing checkers, special judges, and validators
  • Setting time/memory limits and subtask constraints

Best practices

  • Ensure original, non-trivial problem ideas and avoid duplicates
  • Write unambiguous statements: define every term and specify all ranges
  • Provide strong samples including edge cases and common wrong interpretations
  • Combine random and handcrafted tests; include extremes and boundaries
  • Use testlib for reproducible generators and build simple, robust checkers for correctness
  • Set time limits based on reference solutions (test std × 2) and design clear subtask structure

Example use cases

  • Create a rated Codeforces contest problem from concept to deployable files
  • Write LaTeX statements and sample I/O for an ICPC regional problem set
  • Implement testlib generators producing mixed random and handcrafted data sets
  • Develop a basic special judge or checker for non-unique-output problems
  • Design subtasks and choose time/memory limits for multi-tier contests

FAQ

Benchmark a correct reference implementation on the judge machine or a comparable environment, then set the limit to roughly twice the observed run time to allow language and I/O variance.

What makes a sample set strong?

Include normal cases, boundary values, and examples that expose common misinterpretations. Add at least one sample that would fail naive or greedy approaches.

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