AI4Math-Auto-Research
AI4Math-Auto-Research contains 5 collected skills from VeryMath, with repository-level occupation coverage and site-owned skill detail pages.
Skills in this repository
Route AI4Math automated mathematical research tasks to normalized skill packages in this repository.
Use when a coding agent should clone, patch, set up, and supervise FrenzyMath Rethlas on a machine that already has OpenCode installed and configured.
Use when Codex needs to interactively deploy, configure, verify, or launch AI4Math Auto-Research with Agent Laboratory, including API-key handling, user research-topic intake, full local validation, and human review gates.
Use when Codex should act as a coding-agent-native mathematical problem discovery engine: turn fuzzy mathematical background, scattered notes, domain intuition, failed proof attempts, or immature theorem ideas into a ranked problem menu, conjecture lattice, evidence ledger, counterexample pressure, proof obligations, work orders, and a resumable research_state_packet. Use before theorem proving or formal verification when the user does not yet know which mathematical problem should be pursued.
Use when Codex should work as a coding-agent-native proof planning and review workflow: transform a candidate theorem, proof sketch, problem artifact, or proof_obligations into a proof blueprint, verifier-style report, repair hints, proof-obligation ledger patches, and a strict proof acceptance decision without treating API access as the default path.