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Found 1,578 Skills
PR-backed and current-main optimization manual for the `MiniMaxAI/MiniMax-M2` series, including M2, M2.1, M2.5, M2.7, and M2.7-highspeed. Use when Codex needs to recover, extend, or audit MiniMax-specific optimizations, TP QK norm/all-reduce behavior, parser contracts, distributed runtime behavior, quantized loading, or backend-specific validation.
Full optimization workflow, sub-agent launch templates, agent communication contracts, default configurations, tuning strategy, and knowledge base update protocol. Use when: (1) starting an optimization cycle, (2) launching a Profiler or Designer sub-agent, (3) interpreting or formatting agent communication, (4) updating the knowledge base after a profiling or implementation iteration, (5) deciding default configurations or tuning strategy for a kernel.
Follow this sub-process for code optimization — handle tasks where 'behavior remains unchanged but structure changes' (structure / performance / readability). Shift single-module internal optimization from 'AI random refactoring' to 'first scan to generate a checklist, confirm each item with the user, execute step by step according to the method library, and obtain manual approval for each step'. Trigger scenarios: When the user mentions phrases like 'optimize / refactor / rewrite / split / poor performance / too long code' without any accompanying behavior changes. Do not handle new requirements (route to feature), bugs (route to issue), or cross-module architecture restructuring (route to architecture + decisions).
Ultra-lightweight channel for refactor processes - used when changes are clearly too small to go through the full scan → design → apply three-stage workflow. AI directly identifies 1-3 low-risk optimization points, confirms with the user once, modifies in-place using classic methods, and validates itself by running tests. No scan checklist, no design documentation, no multi-step human verification required. Trigger scenarios: User says "quick refactor", "small refactor", "simply optimize XX function", "modify directly", "skip the extra steps", and the scope of changes is clearly localized to a single function / single component with test coverage for self-validation.
Phase 3 of the issue workflow —— Fix code precisely according to confirmed root causes and solutions, verify the results, and document it in {slug}-fix-note.md. This is the final stage of the issue workflow —— no verification closure means the workflow is incomplete. Two entry points: the standard path is triggered from cs-issue-analyze (with existing {slug}-analysis.md), and the fast track is triggered directly from cs-issue-report (without {slug}-analysis.md, as the root cause was identified by AI through code reading during the report phase). Trigger scenarios: User says "Start fixing the bug", "Fix according to the analysis", "Start modifying the code". During the fix, only modify the files specified in the solution; do not make incidental optimizations or introduce new abstractions —— these actions will cause the scope to expand to an untraceable extent.
Prisma ORM expert for schema design, migrations, query optimization, relations modeling, and database operations. Use PROACTIVELY for Prisma schema issues, migration problems, query performance, relation design, or database connection issues.
Expert guidance for fast fine-tuning with Unsloth - 2-5x faster training, 50-80% less memory, LoRA/QLoRA optimization
Multi-cloud orchestration for ML workloads with automatic cost optimization. Use when you need to run training or batch jobs across multiple clouds, leverage spot instances with auto-recovery, or optimize GPU costs across providers.
Cloud laboratory platform for automated protein testing and validation. Use when designing proteins and needing experimental validation including binding assays, expression testing, thermostability measurements, enzyme activity assays, or protein sequence optimization. Also use for submitting experiments via API, tracking experiment status, downloading results, optimizing protein sequences for better expression using computational tools (NetSolP, SoluProt, SolubleMPNN, ESM), or managing protein design workflows with wet-lab validation.
CAPA system management for medical device QMS. Covers root cause analysis, corrective action planning, effectiveness verification, and CAPA metrics. Use for CAPA investigations, 5-Why analysis, fishbone diagrams, root cause determination, corrective action tracking, effectiveness verification, or CAPA program optimization.
Framer Motion performance optimization guidelines. This skill should be used when writing, reviewing, or refactoring React animations with Framer Motion to ensure optimal performance patterns. Triggers on tasks involving motion components, animations, gestures, layout transitions, scroll-linked effects, and SVG animations.
Debug database performance issues through query analysis, index optimization, and execution plan review. Identify and fix slow queries.