AI4Math-Auto-Research
يحتوي AI4Math-Auto-Research على 5 من skills المجمعة من VeryMath، مع تغطية مهنية على مستوى المستودع وصفحات skill داخل الموقع.
Skills في هذا المستودع
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.