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# Skill 仓库 描述 安装量
6901 diagnose vinvcn/mattpocock-skills-zh-cn
No SKILL.md available for this skill. View on GitHub
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6902 caveman vinvcn/mattpocock-skills-zh-cn
Respond terse like smart caveman. All technical substance stay. Only fluff die. Persistence ACTIVE EVERY RESPONSE. No revert after many turns. No filler drift. Still active if unsure. Off only: "stop caveman" / "normal mode". Default: full . Switch: /caveman lite|full|ultra . Rules Drop: articles (a/an/the), filler (just/really/basically/actually/simply), pleasantries (sure/certainly/of course/happy to), hedging. Fragments OK. Short synonyms (big not extensive, fix not "implement a solution for"...
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6903 zoom-out vinvcn/mattpocock-skills-zh-cn
I don't know this area of code well. Go up a layer of abstraction. Give me a map of all the relevant modules and callers.
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6904 write-a-skill vinvcn/mattpocock-skills-zh-cn
Writing Skills Process Gather requirements - ask user about: What task/domain does the skill cover? What specific use cases should it handle? Does it need executable scripts or just instructions? Any reference materials to include? Draft the skill - create: SKILL.md with concise instructions Additional reference files if content exceeds 500 lines Utility scripts if deterministic operations needed Review with user - present draft and ask: Does this cover your use cases? Anything missing or unclea...
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6905 measuring-product-market-fit refoundai/lenny-skills
Measuring Product-Market Fit Help the user assess and achieve product-market fit using frameworks from 46 product leaders. How to Help When the user asks about product-market fit: Understand their stage - Ask how many customers they have, what their retention looks like, and what signals they're seeing (or not seeing) Diagnose the situation - Determine if they're confusing vanity metrics with PMF, if they have PMF in a specific segment, or if they're clearly pre-PMF Apply the right framework - H...
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6906 cuopt-numerical-optimization-api-python nvidia/skills
cuOpt Numerical Optimization Skill (Python) Model and solve LP, MILP, and QP problems using NVIDIA cuOpt's GPU-accelerated solver. The Python API surface ( Problem , SolverSettings , solve ) is shared across all three problem classes — only the objective form and a few rules change. Before You Start Use a formulation summary (parameters, constraints, decisions, objective) if available; otherwise ask for decision variables, objective, and constraints. Then confirm problem type (LP / MILP / QP — s...
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6907 launch-marketing refoundai/lenny-skills
Launch Marketing Help the user plan and execute effective product launches using strategies from 26 product leaders. How to Help When the user asks for help with a product launch: Understand the launch type - Ask whether this is a company launch, funding announcement, major feature, or incremental release. Different types require different approaches Clarify goals - Determine the primary objective: customer acquisition, recruiting, fundraising, feedback, or partnership opportunities Assess readi...
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6908 product-led-sales refoundai/lenny-skills
Product-Led Sales Help the user implement product-led sales motions using frameworks from 2 product leaders. How to Help When the user asks for help with product-led sales: Understand the current state - Ask about their existing PLG motion and sales infrastructure Define the trigger criteria - Help them identify what signals indicate a user is ready for sales outreach Design the handoff - Create smooth transitions from self-serve to sales-assisted Align incentives - Ensure product and sales team...
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6909 community-building refoundai/lenny-skills
Community Building Help the user build and scale communities using frameworks from 18 product leaders who have built communities at Notion, Figma, WordPress, and more. How to Help When the user asks for help with community building: Identify the community type - Clarify if they need a user community, agency community, or partner community Find the atomic unit of sharing - Determine what community members would naturally want to show off Start with listening - Understand why early members are the...
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6910 building-with-llms refoundai/lenny-skills
Building with LLMs Help the user build effective AI applications using practical techniques from 60 product leaders and AI practitioners. How to Help When the user asks for help building with LLMs: Understand their use case - Ask what they're building (chatbot, agent, content generation, code assistant, etc.) Diagnose the problem - Help identify if issues are prompt-related, context-related, or model-selection related Apply relevant techniques - Share specific prompting patterns, architecture ap...
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6911 asc-crash-triage rudrankriyam/app-store-connect-cli-skills
asc crash triage Use this skill to fetch, analyze, and summarize TestFlight crash reports, beta feedback, and performance diagnostics. Workflow Resolve the app ID if not provided (use asc apps list ). Fetch data with the appropriate command. Parse JSON output and present a human-readable summary. TestFlight crash reports List recent crashes (newest first): asc testflight crashes list --app "APP_ID" --sort -createdDate --limit 10 Filter by build: asc testflight crashes list --app "APP_ID" --build...
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6912 design-engineering refoundai/lenny-skills
Design Engineering Help the user understand design engineering using frameworks from 2 product leaders who have built design engineering functions at companies like Snap, Captions, and Vercel. How to Help When the user asks for help with design engineering: Define the role - Clarify what design engineering means in their context (prototyping, production code, or both) Identify the need - Determine if the gap is between design and engineering handoffs, prototype fidelity, or shipping speed Assess...
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6913 okx-ai-guide okx/onchainos-skills
OKX.AI Guide The OKX.AI onboarding entry. Introduces OKX.AI (the Agent economic system), detects whether the current runtime can run OKX.AI, and routes the user into one of the three identity-registration flows — or, on an incompatible platform, tells them how to get a compatible one. Instruction Priority Tagged blocks indicate rule severity (higher wins on conflict): <NEVER> — Absolute prohibition. <MUST> — Mandatory step. <SHOULD> — Best practice. Scope & Boundary This skill owns: OKX.AI intro...
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6914 running-decision-processes refoundai/lenny-skills
Running Decision Processes Help the user run effective decision-making processes using frameworks from 65 product leaders. How to Help When the user asks for help with decision processes: Understand the decision type - Ask if this is reversible or irreversible, high-stakes or routine Identify the blockers - Determine what's preventing the decision from being made Structure the process - Recommend an appropriate framework for the decision at hand Enable commitment - Help them move from deliberati...
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6915 review alirezarezvani/claude-skills
Review Two-axis review of the diff between HEAD and a fixed point the user supplies: Standards — does the code conform to this repo's documented coding standards? Spec — does the code faithfully implement the originating issue / PRD / spec? Both axes run as parallel sub-agents so they don't pollute each other's context, then this skill aggregates their findings. The issue tracker should have been provided to you — run /setup-matt-pocock-skills if docs/agents/issue-tracker.md is missing. Process ...
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6916 skill-lookup f/awesome-chatgpt-prompts
Workflow Search for skills matching the user's request using search_skills Present results with title, description, author, and file list If the user picks a skill, retrieve it with get_skill to get all files Install by saving files to .claude/skills/{slug}/ and verify the SKILL.md exists Confirm installation and explain what the skill does and when it activates Example search_skills({"query": "code review", "limit": 5, "category": "coding"}) get_skill({"id": "abc123"}) Available Tools Use these...
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6917 product-operations refoundai/lenny-skills
Product Operations Help the user build and scale product operations functions using frameworks from 5 product leaders. How to Help When the user asks for help with product operations: Understand the pain points - Ask what's breaking down in their current product processes Assess organizational scale - Determine if they're at the stage where dedicated product ops makes sense Define the scope - Help them clarify what product ops should own vs. what PMs should retain Design the systems - Create pro...
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6918 startup-pivoting refoundai/lenny-skills
Startup Pivoting Help the user decide when and how to pivot their startup using frameworks and insights from 2 product leaders. How to Help When the user asks for help with pivoting: Assess the current state - Ask about their traction, how long they've been trying, and what they've learned Evaluate if possibilities are exhausted - Determine if they've truly tried everything or just one version of the idea Challenge pivot magnitude - Most founders pivot too little; help them consider if they need...
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6919 writing-north-star-metrics refoundai/lenny-skills
Writing North Star Metrics Help the user define their North Star metric using frameworks and insights from 27 product leaders. How to Help When the user asks for help with North Star metrics: Understand the value - Ask what specific value the product delivers to users (not revenue or internal activity) Test for simplicity - Ensure the metric can be understood and discussed by anyone in the company Check for actionability - Confirm teams can actually influence this metric through their work Add g...
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6920 scaffolding-oracle-to-postgres-migration-test-project github/awesome-copilot
Scaffolding an Integration Test Project for Oracle-to-PostgreSQL Migration Creates a compilable, empty xUnit test project with transaction management and seed data infrastructure for a single target project. Run once per project before writing tests. Workflow Progress: - [ ] Step 1: Inspect the target project - [ ] Step 2: Create the xUnit test project - [ ] Step 3: Implement transaction-rollback base class - [ ] Step 4: Implement seed data manager - [ ] Step 5: Verify the project compiles Step ...
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6921 product-taste-intuition refoundai/lenny-skills
Product Taste & Intuition Help the user develop product taste and intuition using frameworks from 10 product leaders. How to Help When the user asks for help with product taste: Understand their current exposure - Ask about the products they use and analyze regularly Identify gaps in their intuition - Determine where their product judgment feels weakest Suggest deliberate practice - Recommend specific activities to build taste over time Help them trust their gut - Guide them on when to rely on i...
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6922 scroll-experience sickn33/antigravity-awesome-skills
Scroll Experience Expert in building immersive scroll-driven experiences - parallax storytelling, scroll animations, interactive narratives, and cinematic web experiences. Like NY Times interactives, Apple product pages, and award-winning web experiences. Makes websites feel like experiences, not just pages. Role : Scroll Experience Architect You see scrolling as a narrative device, not just navigation. You create moments of delight as users scroll. You know when to use subtle animations and whe...
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6923 runpodctl runpod/skills
Runpodctl Manage GPU pods, serverless endpoints, templates, volumes, and models. Install curl -sSL https://cli.runpod.net | bash (any platform) or brew install runpod/runpodctl/runpodctl . Manual binaries, Windows/Linux steps, and the version caveat ( --model-reference + multi-volume need v2.4.0+ ): reference/install.md . Old runpodctl builds silently lack newer flags/behaviors (e.g. --model-reference doesn't exist before v2.4.0) and produce confusing downstream errors — and the Homebrew tap can...
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6924 oo-component-documentation github/awesome-copilot
OO Component Documentation Create new documentation for an object-oriented component or update an existing component documentation file by analyzing the current implementation. Determine the mode first Choose the workflow before writing anything: Use update mode when the user provides an existing documentation Markdown file, points to a docs path, or explicitly asks to refresh or revise existing documentation. Follow references/update-mode.md . Use create mode when the user provides a source fil...
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6925 pro tanweai/pua
PUA Pro — 自进化 + Platform 本 skill 是 /pua 核心的扩展层。角色切换请用 /pua:p7 /pua:p9 /pua:p10 。 自进化协议 "今天最好的表现，是明天最低的要求"——这不是旁白，这是机制。 读取 ~/.pua/evolution.md （详见 references/evolution-protocol.md ） 存在 → 加载基线 + 已内化模式。内化模式是默认义务，做了不标 [PUA生效]，不做则退化警告 不存在 → 首次启动，创建初始模板 任务完成时比对：超越 → 刷新基线 / 达标 → 保持 / 低于 → 退化警告（不降基线） 某行为重复 3+ 次会话 → 晋升为"已内化模式"（永久默认义务） Platform 层 会话启动前置检查 检查 ~/.pua/evolution.md ：加载自进化基线 检查 ~/.pua/builder-journal.md （Compaction 断点恢复）：存在且 <2h → [Calibration] 流程，恢复 pressure_level / failure_count / tried_appr...
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6926 social-media-image-sizes branding5/social-media-image-sizes
Social Media Image Sizes Check and resize images for 9 platforms / 60+ specs. Scripts mirror the logic at branding5.com/tools/social-media-cheat-sheet . Setup Run once after install: cd < skill-dir > npm install Check an image node scripts/check.js photo.jpg Outputs a ranked match list — perfect → close → usable → too small — with an inline node scripts/resize.js command for every non-perfect match. Filter by platform or match level: node scripts/check.js photo.jpg --platform instagram node scri...
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6927 shopify-development sickn33/antigravity-awesome-skills
Shopify Development Skill Use this skill when the user asks about: Building Shopify apps or extensions Creating checkout/admin/POS UI customizations Developing themes with Liquid templating Integrating with Shopify GraphQL or REST APIs Implementing webhooks or billing Working with metafields or Shopify Functions ROUTING: What to Build IF user wants to integrate external services OR build merchant tools OR charge for features: → Build an App (see references/app-development.md ) Show more Installs...
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6928 web-development tencentcloudbase/skills
When to use this skill Use this skill for Web frontend project development when you need to: Develop web frontend pages and interfaces Deploy static websites to CloudBase static hosting Integrate CloudBase Web SDK for database, cloud functions, and authentication Set up modern frontend build systems (Vite, Webpack, etc.) Handle routing and build configurations for static hosting Do NOT use for: Mini-program development (use miniprogram-development skill) Backend service development (use cloudrun...
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6929 nemo-mbridge-perf-parallelism-strategies nvidia/skills
Parallelism Strategy Selection Skill For stable background on each parallelism type, see: @docs/parallelisms.md @skills/nemo-mbridge-perf-parallelism-strategies/card.yaml Decision by Model Size Dense models Model size GPUs Recommended starting point < 1B 1-8 DP only 1-10B 8-16 TP=2-4 + DP 10-70B 16-64 TP=4-8 + PP=2-4 + DP 70-175B 64-256 TP=8 + PP=4-8 + DP 175-500B 256-1024 TP=8 + PP=8-16 + CP=2 + DP Show more Installs 552 Repository nvidia/skills GitHub Stars 1.3K First Seen May 29, 2026 Securit...
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6930 nemo-mbridge-perf-cpu-offloading nvidia/skills
CPU Offloading References Stable docs: @docs/training/cpu-offloading.md Structured metadata: @skills/nemo-mbridge-perf-cpu-offloading/card.yaml What It Is Two independent mechanisms to move data from GPU to CPU memory: Mechanism Config namespace What gets offloaded PP restriction Activation offloading model.cpu_offloading* Activations (and optionally weights) per transformer layer PP must be 1 Optimizer offloading optimizer.optimizer_cpu_offload Adam optimizer states (momentum + variance) via Hy...
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6931 nemo-mbridge-perf-activation-recompute nvidia/skills
Activation Recompute Stable docs: @docs/training/activation-recomputation.md Card: @skills/nemo-mbridge-perf-activation-recompute/card.yaml What It Is Activation recompute trades GPU compute for memory by discarding intermediate activations during the forward pass and recomputing them during backward. Megatron Bridge supports two granularities: Granularity What you specify What gets recomputed Memory savings Compute cost selective recompute_modules list (e.g. core_attn , mlp ) specific submodule...
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6932 nemo-mbridge-perf-moe-vlm-training nvidia/skills
MoE VLM Training Stable docs: @docs/training/moe-optimization.md Card: @skills/nemo-mbridge-perf-moe-vlm-training/card.yaml FSDP vs 3D Parallel Approach Strength Best fit FSDP Simplest path to a working multimodal run first bring-up, memory-first tuning, awkward PP boundaries 3D parallel Higher ceiling after tuning stable models with a clean PP layout and time for deeper sweeps For MoE VLMs, the practical workflow is usually: get the first reliable run with FSDP stabilize real-data input, recomp...
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6933 nemo-mbridge-multi-node-slurm nvidia/skills
Multi-Node Slurm Convert single-node uv run python -m torch.distributed.run commands into multi-node Slurm sbatch scripts with Enroot container support, and debug common multi-node failures. Two Approaches: srun-native vs uv run torch.distributed Approach ntasks-per-node Process spawning Best for srun-native (preferred) 8 Slurm spawns 8 tasks/node Conversion, inference, Bridge scripts uv run torch.distributed (legacy) 1 uv run python -m torch.distributed.run spawns 8 procs/node MLM pretrain_gpt....
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6934 nemo-mbridge-perf-moe-long-context nvidia/skills
MoE Long-Context Training Stable docs: @docs/training/moe-optimization.md Card: @skills/nemo-mbridge-perf-moe-long-context/card.yaml What Changes At Long Context Once sequence length moves well past the 4K-class regime, attention memory and activation residency become the dominant constraints. For MoE models, that usually means you need some combination of: context parallelism selective recompute lower precision CPU offload for optimizer state a dispatcher and PP layout that do not waste the sma...
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6935 nemo-mbridge-mlm-bridge-training nvidia/skills
MLM vs Bridge Training For how they differ, the arg mapping tables, gotchas, and translation script, see: @docs/megatron-lm-to-megatron-bridge.md First Answer Checklist For MLM-vs-Bridge correlation questions, always name these items up front: Bridge recipe: vanilla_gpt_pretrain_config . Bridge entry point: scripts/training/run_recipe.py . MLM entry point: 3rdparty/Megatron-LM/pretrain_gpt.py . Launch wrapper for both: uv run python -m torch.distributed.run . Fresh-run cleanup: rm -rf nemo_exper...
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6936 tilegym-adding-cutile-kernel nvidia/skills
Adding a cuTile Kernel to TileGym End-to-end workflow for adding a new operator (e.g., my_op ) with cuTile backend. Execution Rules MUST follow these rules strictly: Use TodoWrite to create the checklist below BEFORE writing any code Execute steps in order — do NOT skip ahead or combine steps Mark each todo as completed after finishing, in_progress when starting If a step is not applicable (e.g., no cuTile impl), mark it completed with a note, do NOT silently skip Each step MUST result in a file...
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6937 vss-deploy-detection-tracking-3d nvidia/skills
Purpose Deploy and operate the RTVI-CV-3D microservice as MV3DT ( MODE=mv3dt ) — per-camera DeepStream perception plus BEV Fusion over multiple calibrated cameras — on the bundled sample dataset, custom videos, or live RTSP, without the full warehouse agent / LLM / VLM stack. Instructions Work top-to-bottom: answer the routing questions (Q0–Q3) under Routing , then follow the reference for the chosen path. Detailed step-by-step procedures live in references/ (deploy, calibration chain, camera co...
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6938 nemo-mbridge-perf-expert-parallel-overlap nvidia/skills
MoE Expert-Parallel Overlap Skill References Stable docs: @docs/training/communication-overlap.md Structured metadata: @skills/nemo-mbridge-perf-expert-parallel-overlap/card.yaml What It Is Expert-parallel (EP) overlap hides the cost of token dispatch/combine all-to-all communication by running it concurrently with expert FFN compute. Optionally, delayed expert weight-gradient computation ( delay_wgrad_compute ) provides additional overlap by deferring wgrad to overlap with the next layer's forw...
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6939 nemo-mbridge-perf-hierarchical-context-parallel nvidia/skills
Hierarchical Context Parallel Skill This skill covers hierarchical context parallelism: nested context-parallel process groups used by cp_comm_type="a2a+p2p" and configured with hierarchical_context_parallel_sizes . For what hierarchical CP is, when to use it, and the decision tree ( a2a+p2p vs pure a2a vs p2p ), see: @docs/training/hierarchical-context-parallel.md @skills/nemo-mbridge-perf-hierarchical-context-parallel/card.yaml Enablement Minimal Bridge override: Show more Installs 551 Reposit...
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6940 vss-deploy-profile nvidia/skills
VSS Deploy Available Scripts Script Purpose Arguments scripts/normalize_resolved_yml.py Strip optional depends_on entries for services filtered out of resolved.yml before deploy. Path to resolved.yml scripts/probe_remote_models.sh Probe an OpenAI-compatible remote LLM/VLM endpoint and verify the selected model id. Base URL, optional expected model id Profile Routing Match the user's request to a profile, then load that profile's reference for sizing, services, env recipes, and debugging. Show mo...
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6941 vss-deploy-detection-tracking-2d nvidia/skills
Purpose Deploy, debug, and operate the RTVI-CV detection / tracking 2D microservice and drive its REST API. Prerequisites Active VSS deployment reachable on $HOST_IP (see vss-deploy-profile and references/ ). NGC credentials in $NGC_CLI_API_KEY and $NVIDIA_API_KEY for any image pulls. curl , jq , and Docker available on the caller. Instructions Follow the routing tables and step-by-step workflows below. Each section that ends in workflow , quick start , or flow is intended to be executed top-to-...
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6942 vss-deploy-dense-captioning nvidia/skills
Purpose Stand up the RT-VLM dense-captioning microservice on its own and exercise every endpoint it exposes (file upload, generate_captions, stream add/delete, chat-completions, Kafka topics). Prerequisites For standalone RT-VLM deployment: Docker, Docker Compose, NVIDIA Container Toolkit, and a visible GPU. NGC registry credentials in $NGC_CLI_API_KEY for docker login nvcr.io , image pulls, and local NGC model/artifact downloads. curl , jq , and any writable working directory for the standalone...
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6943 image-tryon starchild-ai-agent/official-skills
image-tryon Use this skill for all virtual try-on requests on Starchild. Covers: clothing try-on, accessory try-on, hairstyle preview, makeup preview, glasses try-on, hat try-on, shoes try-on, watch try-on. Core principle: call the provided script. Do not re-implement proxy/billing plumbing. Key difference from image-edit: try-on always requires two images — a person photo and a garment/item photo. 1. Quick start — clothing try-on (most common) Show more Installs 556 Repository starchild-ai-ag…l...
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6944 vss-setup-video-analytics-api nvidia/skills
Purpose Deploy the video-analytics-api REST service standalone with the user's chosen config, data-log bind, and Elasticsearch / Kafka connectivity. Instructions Follow the routing tables and step-by-step workflows below. Each section that ends in workflow , quick start , or flow is intended to be executed top-to-bottom. Detailed reference material lives in references/ . Examples Worked end-to-end examples are kept under evals/ (each *.json manifest contains a runnable scenario). Run a Tier-3 ev...
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6945 nemo-mbridge-perf-moe-optimization-workflow nvidia/skills
MoE Training Optimization Workflow Stable docs: @docs/training/moe-optimization.md Card: @skills/nemo-mbridge-perf-moe-optimization-workflow/card.yaml Source: Scalable Training of MoE Models with Megatron Core Quick Reference Think in terms of the paper's Three Walls: memory wall communication wall compute and host-overhead wall MoE tuning is iterative. Fixing one wall usually exposes the next one, so the best workflow is: fit first, scale second, profile third, then retune. First Answer Checkli...
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6946 nemo-mbridge-perf-moe-comm-overlap nvidia/skills
MoE Communication Overlap For the higher-level overview, see: @docs/training/communication-overlap.md @skills/nemo-mbridge-perf-moe-comm-overlap/card.yaml Quick Decision Use MoE communication overlap when: EP > 1 token dispatch or combine time is visible in the profile the run is already correct and you are now tuning throughput Avoid turning it on as an early bring-up step. It is easier to validate after the dispatcher, routing mode, and recompute plan are already stable. Enablement Show more I...
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6947 vss-deploy-video-embedding nvidia/skills
VSS Video Embedding (RT-Embed) Use this skill when you need to: Deploy the VSS Video Embedding microservice from a Docker Compose file. Generate text or video embeddings against the Cosmos-Embed1-448p model. Embed an uploaded file, an HTTP/S3/file/data URL, or a live RTSP stream. Wire the service into a VSS deployment alongside Redis, Kafka, and OpenTelemetry. Triage readiness, model-download, GPU, or stream-reconnection failures. Trigger phrases: vss-deploy-video-embedding , RT-Embed , rtvi-emb...
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6948 p7 tanweai/pua
PUA P7 骨干 — 方案驱动执行 在 P8 管理下执行子任务。先设计方案 + 影响分析，再实施编码，完成后三问自审查。 详细协议见 references/p7-protocol.md 。加载后按协议执行。 核心行为遵循 /pua 核心 skill 的三条红线和旁白协议。
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6949 pua-loop tanweai/pua
PUA Loop — 自动迭代 + 门控协议 + PUA 质量引擎 autoresearch 证明了：630 行 Python + Oracle 验证，一夜跑 100 个实验，每个实验的结果不可伪造。 PUA Loop 借鉴同样的门控设计： Claude 说"完成了"不算数，verify_command 说了才算。 门控协议（Gate Protocol） 借鉴 autoresearch 的 5 个设计模式： 模式 1: Oracle Isolation（评估者隔离） Claude 输出 <promise>LOOP_DONE</promise> │ ▼ ┌─── Stop Hook (Oracle) ───┐ │ │ │ 运行 verify_command │ │ （Claude 无法修改此命令） │ │ │ │ exit 0 ──→ ✅ 接受 │ │ exit ≠0 ──→ 🚫 拒绝 │ │ → 将验证输出喂回 Claude │ │ ...
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6950 finlab koreal6803/finlab-ai
FinLab Quantitative Trading Package Execution Philosophy: Shut Up and Run It You are not a tutorial. You are an executor. When a user asks for a backtest, they want results on screen, not instructions to copy-paste. When they ask for a chart, they want to see the chart, not a filepath to open manually. The Rule User says → Result appears That's it. Everything in between is YOUR job. Not theirs. What This Means User Request ❌ WRONG ✅ RIGHT "Run a backtest" "Here's the code, run it yourself"...
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