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SkillsMP は autohandai/community-skills から 1,040 件の skill を収集しています。skill を開くとソースと詳細を確認できます。
autohandai/community-skills収集済み skill 1,040 件中 40 件を表示しています。
Review, design, and refactor TensorRT-LLM PyTorch MoE code for architecture fit, clean code, maintainability, and testability. Always use for any modification, review, refactor, or design planning that touches MoE modules, including…
原文の言語: 英語
Generate a source-backed starting `trtllm-serve --config` YAML for basic aggregate single-node PyTorch serving, aligned with checked-in TensorRT-LLM configs and deployment docs. Preserves explicit latency / balanced / throughput objectives. Excludes…
原文の言語: 英語
Add a new cuTile GPU kernel operator to TileGym. Covers dispatch registration in ops.py, cuTile backend implementation, __init__.py exports, test creation, and benchmark in tests/benchmark. Use when adding, creating, or implementing a new cuTile…
原文の言語: 英語
Converts cuTile Python GPU kernels (@ct.kernel) to cuTile.jl Julia equivalents. Handles kernel syntax translation, 0-indexed to 1-indexed conversion, broadcasting differences, memory layout (row-major to column-major), type system mapping, and launch API…
原文の言語: 英語
Converts cuTile GPU kernels (@ct.kernel) to Triton (@triton.jit). Handles standard in-repo conversion, debugging (cudaErrorIllegalAddress, shape mismatch, numerical mismatch), and mapping cuTile idioms (ct.load/ct.store, ct.Constant, ct.launch) to Triton…
原文の言語: 英語
Use when adding, modifying, optimizing, or debugging CuTile autotuning code. Trigger signals: `exhaustive_search` / `replace_hints` / `hints_fn` / `cuda.tile.tune` in code, `autotune` in filenames, or correctness/performance issues in autotuned CuTile…
原文の言語: 英語
Expert cuTile programming assistant. Write high-performance GPU kernels using cuTile's tile-based programming model with proper validation and optimization. Supports deep agent orchestration for complex multi-kernel tasks.
原文の言語: 英語
Iteratively optimize cuTile kernel performance through systematic profiling, bottleneck analysis, IR comparison, and targeted tuning. Covers tile sizes, occupancy, autotune configs, TMA, latency hints, persistent scheduling, num_ctas, flush_to_zero, and…
原文の言語: 英語
Integrate TileGym kernels into Hugging Face `transformers` models by replacing the library's submodule(s) and certain class(es)' implementations, and patching certain class(es)' init/forward/load weight methods prior to instantiating models. Used when the…
原文の言語: 英語
Manage and monitor VSS alerts after the alerts profile is deployed. The deployment's mode (CV vs VLM real-time) is fixed at deploy time and determines the workflow — start/stop real-time alerts via the VSS Agent on a VLM deployment, onboard CV alerts by…
原文の言語: 英語
Deploy, debug, or tear down any VSS profile using a compose-centric workflow — config (dry-run) with env overrides, review resolved compose, then compose up. Use this skill when the user says "deploy vss", "deploy `profile`", "debug deploy", "verify…
原文の言語: 英語
Produce video analysis reports by discovering the deployed VSS agent, querying POST /generate for a timestamped captioned summary of the clip, then formatting the agent reply as the standard Video Analysis Report markdown.
原文の言語: 英語
Use this skill when working with the RTVI VLM or RT-VLM microservice API on VSS 3.1. Generate dense captions and alerts for stored video files and live RTSP streams via `/v1/generate_captions_alerts`; upload media via `/v1/files`; add and remove live streams…
原文の言語: 英語
Query video analytics data and metrics from Elastic search via the VA-MCP server (port 9901). This includes incidents, alerts, sensor data, and metrics. Use for any question about violations, alerts, incidents, object counts, speeds, occupancy, or anything…
原文の言語: 英語
Search video archives using natural language — find events, objects, actions, and people across recorded video using fusion search (Cosmos Embed1 semantic search + CV attribute search). Use when asked to search for something in video, find actions and events,…
原文の言語: 英語
Summarize a video by calling the VLM NIM or the Long Video Summarization (LVS) microservice directly. For short videos (under 60s) call the VLM's OpenAI-compatible chat completions endpoint; for long videos (60s or longer) call the LVS microservice. Use when…
原文の言語: 英語
Call the vss agent to run video understanding on video to answer a text question. Use when the user asks about video content, or about visual details that cannot be answered from conversation history, search hits, or metadata alone.
原文の言語: 英語
Query VIOS REST APIs: sensor list, recording timelines, video clip extraction, snapshot capture, add/delete sensors and streams
原文の言語: 英語
Generate video summary reports using the VSS video_search_frag extension with Long Video Summarization (LVS), Enterprise RAG knowledge retrieval, and human-in-the-loop parameter collection. Use when: user wants to generate a video summary, report, or analysis…
原文の言語: 英語
Use spring-boot-skills for production-grade Spring Boot agent guidance, modernization, testing, and operations.
原文の言語: 英語
Inventory COBOL estates and classify modernization go/no-go readiness with ATLAS toolkit discovery.
原文の言語: 英語
Reverse-engineer COBOL systems into structured requirements, business rules, and dependency maps with cobol-o-matic.
原文の言語: 英語
Modernize COBOL systems to Java Quarkus or .NET with Microsoft Legacy Modernization Agents workflows.
原文の言語: 英語
Plan and execute AI-assisted COBOL to Java migrations with LegacyBridge OSS COBOL.
原文の言語: 英語
Use AI assistance for IBM z/OS and mainframe modernization tasks from the mainframe-ai project.
原文の言語: 英語
Use the Mainframe AI-native Bash runtime and bundled skills for legacy system analysis automation.
原文の言語: 英語
SOC 2 Type II audit preparation involves designing, implementing, and demonstrating the operational effectiveness of controls aligned to the AICPA Trust Services Criteria (TSC) over a defined audit pe
原文の言語: 英語
UI/UX best practices for web interfaces. Use when reviewing animations, CSS, audio, typography, UX patterns, prefetching, or icon implementations. Covers 11 categories from animation principles to typography. Outputs file:line findings.
原文の言語: 英語
Configure AWS Verified Access to provide VPN-less zero trust network access to internal applications using identity and device posture verification with Cedar policy language.
原文の言語: 英語
Configuring Google Cloud Identity-Aware Proxy (IAP) to enforce per-request identity verification for Compute Engine, App Engine, Cloud Run, and GKE services using access levels, context-aware policies, and programmatic access with service accounts.
原文の言語: 英語
Configuring Zscaler Private Access (ZPA) to replace traditional VPN with zero trust network access by deploying App Connectors, defining application segments, configuring access policies based on user identity and device posture, and integrating with IdPs.
原文の言語: 英語
Deploying Cloudflare Access with Cloudflare Tunnel to provide zero trust access to self-hosted and private applications, configuring identity-aware access policies, device posture checks, and WARP client enrollment for VPN replacement.
原文の言語: 英語
Deploying Palo Alto Networks Prisma Access for SASE-based zero trust network access using GlobalProtect agents, ZTNA Connectors, security policy enforcement, and integration with Strata Cloud Manager for unified security management.
原文の言語: 英語
Deploy and configure Tailscale as a WireGuard-based zero trust mesh VPN with identity-aware access controls, ACLs, and exit nodes for secure peer-to-peer connectivity.
原文の言語: 英語
Implementing Google's BeyondCorp zero trust access model to eliminate implicit trust from the network perimeter, enforce identity-aware access controls using IAP, Access Context Manager, and Chrome Enterprise Premium for VPN-less secure application access.
原文の言語: 英語
Implement the CISA Zero Trust Maturity Model v2.0 across the five pillars of identity, devices, networks, applications, and data to achieve progressive organizational zero trust maturity.
原文の言語: 英語
Implementing device posture assessment as a zero trust access control by integrating endpoint health signals from CrowdStrike ZTA, Microsoft Intune, and Jamf into conditional access policies that enforce compliance before granting resource access.
原文の言語: 英語
Implementing microsegmentation using Akamai Guardicore Segmentation to map application dependencies, create granular network policies, visualize east-west traffic flows, and enforce least-privilege communication between workloads across data centers and cloud.
原文の言語: 英語
Implement NextDNS as a zero trust DNS filtering layer with encrypted resolution, threat intelligence blocking, privacy protection, and organizational policy enforcement across all endpoints.
原文の言語: 英語
Implementing zero trust access controls for SaaS applications using CASB, SSPM, conditional access policies, OAuth app governance, and session controls to enforce identity verification, device compliance, and data protection for cloud-hosted services.
原文の言語: 英語