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pathwaycom/arc-task-gen

Generates original ARC-AGI-1-style tasks distribution-matched to the public eval set. observed · 2026-08-28

github.com/pathwaycom/arc-task-gen · Python · MIT (permissive) observed · 2026-08-28

Health v2 · maintenance only

56/100

  • Activity 97
  • Release rhythm 35
  • Longevity 2

Flags: no_releases young

How is this computed?

round(0.45*activity + 0.35*rhythm + 0.20*longevity); archived -> min(score, 10) — computed 2026-09-02. Adoption (stars, forks) is never an input.

  • gap_med: n/a
  • age_days: 29
  • days_rel: n/a
  • days_push: 22
  • n_releases_24m: 0

Full methodology

Adoption not part of the score

6665 stars · 45 forks observed · 2026-08-28

What it is AI-extracted, prompt v1, taxonomy v1, 2026-08-29, confidence not recorded

A Python tool that generates original ARC-AGI-1-style puzzle tasks distribution-matched to the public evaluation set. It produces tasks in the standard ARC JSON format, enabling private evaluation of frontier models on problems they have not seen before.

Use cases

  • generate fresh ARC-AGI-1-style tasks for model evaluation
  • create a private benchmark set to test for benchmark contamination
  • evaluate reasoning models on unseen few-shot rule induction problems
  • compare model performance on public vs newly generated ARC tasks
  • produce ARC-format tasks.json files compatible with existing evaluation harnesses

When to choose

  • you need uncontaminated ARC-AGI-1-style evaluation data for LLM or reasoning model benchmarks
  • you want to measure whether model performance on ARC reflects memorization vs genuine rule induction
  • you need tasks in standard ARC JSON format for an existing evaluation harness

When to avoid

  • you need general-purpose synthetic data generation unrelated to ARC-style grid puzzles
  • you want to train models on ARC tasks rather than evaluate them
  • you need a full ARC evaluation harness rather than just task generation

Facets

library · maturity active

data-generation machine-learning benchmarking artificial-intelligence machine-learning developer-tools python cli arc-agi benchmark-evaluation synthetic-tasks llm-evaluation reasoning-models few-shot-learning algorithms

1 source

Member repositories

RepositoryRoleHealth v2
pathwaycom/arc-task-genmain56

For agents

markdown · JSON · MCP: product_card(name="pathwaycom/arc-task-gen")

Data as of 2026-08-30T08:39:29.467469+00:00 · Report a problem