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AI Skills

Skills for AI agents — Claude skills, agent skills, cursor rules and MCP servers that teach Claude Code, Codex, Cursor and other agents new tricks.

12841 apps.

AI Skills, page 98

Ranked by popularity.

4851
I

ingest-url

Fetch a URL and distill its content into the Obsidian wiki

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4852
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jetson-diagnostic

Read-only Jetson health snapshot for identity, memory, GPU, thermal, power

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4853
J

jetson-headless-mode

Plan and apply safe Jetson headless-mode changes to reclaim GUI

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4854
J

jetson-inference-mem-tune

Pick the serving stack and per-runtime memory flags

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4855
J

jetson-llm-benchmark

Benchmark Jetson LLM/VLM serving performance across vLLM, llama.cpp

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4856
J

jetson-llm-serve

Stand up vLLM or SGLang serving on Jetson

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4857
J

jetson-memory-audit

Measure Jetson DRAM/NvMap usage and verify before/after memory reclamation

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4858
J

jetson-optimize-memory

Reclaim DRAM by disabling unused subsystems across MB1 BCT, MB2 BCT

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4859
J

jetson-package

Pick Jetson-compatible containers, vLLM runtime images

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4860
J

jetson-quick-start

Entry skill for Jetson / IGX BSP customization

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4861
L

laravel-best-practices

Apply this skill whenever writing, reviewing, or refactoring Laravel PHP code

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4862
L

launch-nemo-rl

Playbook for launching, monitoring, stopping

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4863
L

llm-wiki

Explain and apply the foundational LLM Wiki architecture

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4864
M

mcore-create-issue

Investigate a failing GitHub Actions run or job and create a GitHub issue

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4865
M

mcore-linting-and-formatting

Linting and formatting for Megatron-LM

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4866
M

mcore-run-on-slurm

How to launch distributed Megatron-LM training jobs on a SLURM cluster

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4867
M

mcore-split-pr

Split a PR into multiple PRs

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4868
M

mcore-testing

Test system for Megatron-LM

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4869
M

memory-bridge

Browse or compare wiki knowledge by originating AI tool

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4870
M

mermaid-visualizer

Transform text content into professional Mermaid diagrams for presentations

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4871
N

nemo-automodel-distributed-training

Guide for selecting and configuring distributed training strategies in NeMo

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4872
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nemo-automodel-launcher-config

Configure NeMo AutoModel job launches for interactive runs, Slurm clusters

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4873
N

nemo-automodel-model-onboarding

Guide for onboarding new model architectures into NeMo AutoModel

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4874
N

nemo-automodel-recipe-development

Create and modify NeMo AutoModel training and evaluation recipes

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4875
N

nemo-data-designer-plugin

Create a dataset, generate synthetic data, or build a data generation pipeline

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4876
N

nemo-evaluator-plugin

Evaluate models, datasets, and agents with the NeMo Evaluator plugin

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4877
N

nemo-mbridge-mlm-bridge-training

Run Megatron-LM (MLM) and Megatron Bridge training with mock or real data

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4878
N

nemo-mbridge-multi-node-slurm

Convert single-node scripts to multi-node Slurm sbatch jobs

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4879
N

nemo-mbridge-perf-activation-recompute

Validate and use selective and full activation recompute in Megatron Bridge

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4880
N

nemo-mbridge-perf-cpu-offloading

Validate and use CPU offloading in Megatron Bridge

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4881
N

nemo-mbridge-perf-cuda-graphs

Validate and use CUDA graph capture in Megatron Bridge

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4882
N

nemo-mbridge-perf-expert-parallel-overlap

Validate and use MoE expert-parallel communication overlap in Megatron-Bridge

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4883
N

nemo-mbridge-perf-hierarchical-context-parallel

Operational guide

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4884
N

nemo-mbridge-perf-megatron-fsdp

Operational guide for enabling Megatron FSDP in Megatron-Bridge

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4885
N

nemo-mbridge-perf-memory-tuning

Techniques for reducing peak GPU memory in Megatron Bridge

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4886
N

nemo-mbridge-perf-moe-comm-overlap

MoE expert-parallel communication overlap in Megatron Bridge

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4887
N

nemo-mbridge-perf-moe-dispatcher-selection

Choose the right MoE token dispatcher

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4888
N

nemo-mbridge-perf-moe-hardware-configs

Representative, point-in-time MoE training playbooks by hardware

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4889
N

nemo-mbridge-perf-moe-long-context

Long-context MoE training guidance for Megatron Bridge

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4890
N

nemo-mbridge-perf-moe-optimization-workflow

Evidence-gated workflow for MoE performance optimization in Megatron Bridge

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4891
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nemo-mbridge-perf-moe-vlm-training

Practical guidance for training MoE VLMs in Megatron Bridge

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4892
N

nemo-mbridge-perf-parallelism-strategies

Operational guide

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4893
N

nemo-mbridge-perf-sequence-packing

Validate and use packed sequences and long-context training in Megatron-Bridge

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4894
N

nemo-mbridge-perf-tp-dp-comm-overlap

Operational guide for enabling TP, DP

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4895
N

nemo-mbridge-recipe-recommender

Recommend and customize Megatron Bridge library and benchmark recipes

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4896
N

nemo-mbridge-resiliency

Resiliency features in Megatron Bridge including fault tolerance

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4897
N

nemo-retriever

Searching, extracting, ingesting, or querying a document collection

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4898
N

nemo-rl-auto-research

Autonomous NeMo-RL research agent workflow

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4899
N

nemo-rl-brev-etiquette

Brev instance operating guidance

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4900
N

nemo-rl-docs

Documentation conventions for NeMo-RL

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