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Found 188 Skills
Save progress and generate a continuation prompt. Updates PRD status markers, captures git state, and writes checkpoint.md for the next session.
Save complete conversation as checkpoint. Only when user explicitly requests ("save session", "checkpoint this"). Use nmem t save to automatically import coding sessions.
Locate the latest checkpoint for a run id and provide a follow-up play/eval command. Use when asked to find a checkpoint.
Eino orchestration with Graph, Chain, and Workflow. Use when a user needs to build multi-step pipelines, compose components into executable graphs, handle streaming between nodes, use branching or parallel execution, manage state with checkpoints, or understand the Runnable abstraction. Covers Graph (directed graph with cycles), Chain (linear sequential), and Workflow (DAG with field mapping).
Track progress across sessions using SESSION.md with git checkpoints and concrete next actions. Converts IMPLEMENTATION_PHASES.md into trackable session state. Use when: resuming work after context clears, managing multi-phase implementations, or troubleshooting lost context.
Manages session state and context handoffs for multi-session projects using the Session Handoff Protocol. Creates and maintains SESSION.md to track phase progress, git checkpoints, and next actions across context clears. Integrates with project-planning skill to convert IMPLEMENTATION_PHASES.md into trackable session state. Use when starting new projects after planning, resuming work after context clear, or managing complex multi-phase implementations. Keywords: session management, SESSION.md, session handoff protocol, context handoff, multi-session projects, phase tracking, git checkpoints, session state tracking, resume work, context clear, phase progress tracking, implementation phases, verification stage, debugging stage, next action tracking, work continuity, session recovery, context management, phased implementation tracking
Create and work with Meta SAM 3 (facebookresearch/sam3) for open-vocabulary image and video segmentation with text, point, box, and mask prompts. Use when setting up SAM3 environments, requesting Hugging Face checkpoint access, generating inference scripts, integrating SAM3 into Python apps, fine-tuning with sam3/train configs, running SA-Co or custom evaluations, or debugging CUDA/checkpoint/prompt pipeline issues.
Expert blueprint for platformer games including precision movement (coyote time, jump buffering, variable jump height), game feel polish (squash/stretch, particle trails, camera shake), level design principles (difficulty curves, checkpoint placement), collectible systems (progression rewards), and accessibility options (assist mode, remappable controls). Based on Celeste/Hollow Knight design research. Trigger keywords: platformer, coyote_time, jump_buffer, game_feel, level_design, precision_movement.
Run the full spec-driven workflow automatically. Proposes, implements, verifies, reviews, and archives a change with one confirmation checkpoint.
Use this when you have a written implementation plan to execute in a separate session with review checkpoints.
High-performance web crawler for discovering and mapping website structure. Use when users ask to crawl a website, map site structure, discover pages, find all URLs on a site, analyze link relationships, or generate site reports. Supports sitemap discovery, checkpoint/resume, rate limiting, and HTML report generation.
Use when "training LLM", "finetuning", "RLHF", "distributed training", "DeepSpeed", "Accelerate", "PyTorch Lightning", "Ray Train", "TRL", "Unsloth", "LoRA training", "flash attention", "gradient checkpointing"