「spa」の検索結果

Automate Confluence page creation, content search, space management, labels, and hierarchy navigation via Rube MCP (Composio). Always search tools first for current schemas.

日本語の概要は準備中です。原文の説明を表示しています。

Automate Bitbucket repositories, pull requests, branches, issues, and workspace management via Rube MCP (Composio). Always search tools first for current schemas.

日本語の概要は準備中です。原文の説明を表示しています。

Official NVIDIA-authored guidance for PhysicsNeMo ShardTensor domain parallelism — integrate domain parallelism into training/inference scripts (new or existing) with DDP or FSDP2, write and register shard patches to enable new layers/ops, and bootstrap multi-GPU correctness tests. Use when working with ShardTensor, scatter_tensor, domain parallelism, sequence/spatial sharding, ring attention, DeviceMesh + DDP/FSDP2 hybrid parallelism, or physicsnemo.domain_parallel. Do NOT use for generic PyTorch DDP/FSDP setup without domain parallelism, picking a PhysicsNeMo model or example (use physicsnemo-discover), or non-distributed training questions.

日本語の概要は準備中です。原文の説明を表示しています。

Validate and use MoE expert-parallel communication overlap in Megatron-Bridge, including overlap_moe_expert_parallel_comm, delay_wgrad_compute, and flex dispatcher backends such as DeepEP and HybridEP.

日本語の概要は準備中です。原文の説明を表示しています。

Brev instance operating guidance for NeMo-RL agents working in /home/ubuntu/RL with limited workspace disk, a larger /ephemeral volume, and optional /home/ubuntu/RL/.env secrets. Use when running nemo-rl-auto-research campaigns, experiments, training jobs, model or dataset downloads, shared cache-heavy commands, log-producing runs, checkpoint generation, W&B or Hugging Face authenticated workflows, or any workflow that may create large files on Brev.

日本語の概要は準備中です。原文の説明を表示しています。

Long-context MoE training guidance for Megatron Bridge. Covers CP sizing, selective recompute, dispatcher choices, and practical patterns from DSV3, Qwen3, and Qwen3-Next long-context experiments.

日本語の概要は準備中です。原文の説明を表示しています。

Use this skill when the user is doing hands-on NVMe-over-Fabrics storage-target work on a BlueField DPU or ConnectX NIC with DOCA STA — standing up a doca_sta DOCA Core context that accelerates the target-side NVMe-oF data path over RDMA, defining doca_sta_subsystem targets (NQN + namespaces) backed by local NVMe-PCI backend disks (doca_sta_be), checking device support via doca_sta_cap_is_supported, sizing the per-connection I/O queues, or debugging DOCA_ERROR_* from a STA call. Trigger even when the user does not say "DOCA STA" — typical implicit phrasings include "my NVMe-oF Connect never completes", "Identify Controller times out over RoCE", "16 I/O queues at depth 1024 — does this BlueField support that", "offload the nvmf target onto the DPU", or "DOCA_ERROR_IO_FAILED on an NVMe read". Refuse and route elsewhere for DOCA install, raw RDMA data movement, raw packet I/O, flow-rule programming, or initiator-side / host NVMe stack work — those belong to other skills.

日本語の概要は準備中です。原文の説明を表示しています。

Use this skill when the user is doing hands-on DOCA Flow DPA Provider work — exporting a `doca-flow` pipe or external resource (index-selector/memory) into BlueField DPA address space so a DPACC-built kernel can read counters, mutate hash-pipe entries, and update/read memory or index-selector resources inline with Flow. Covers per-port `doca_flow_dpa_ctx`, three queue types (general/resources-write/resources-read), the order-sensitive export handshake (`_export_prepare` → add entries → `_export` → `_get_device_addr`), and DPA-side device API. Trigger even when the user does not say "DOCA Flow DPA Provider" — implicit phrasings include "DPA kernel never sees entries in the exported pipe", "BAD_STATE from `_pipe_export`", "how do I disable a hash entry from a DPA kernel", "DPA memory read returns no value", or "DPA-side post keeps returning AGAIN". Refuse and route elsewhere for `doca-flow` pipe construction, generic host-side DPA (`doca-dpa`), or DPA-side kernel-writing — those belong to other skills.

日本語の概要は準備中です。原文の説明を表示しています。

DOCA-shipped Zero-Touch RoCE RTT congestion control (ZTR RTTCC) reference algorithm on a BlueField-3 DPA: deploy, tune and evaluate doca_pcc_dev_ztr_rttcc_algo through the shipped DOCA PCC sample. Trigger on "my RoCE-v2 flows aren't being throttled", "PCC sample isn't dispatching to my algo", "set-params returns fail", "algorithm loaded but counters are flat", "how do I pick the multipath PCC variant", or "do I need a custom CC algorithm on BF3", even without naming ZTR RTTCC. Your own algorithm through the host library belongs to doca-pcc; the doca_spcx_cc command line to doca-spcx-cc. Covers picking a variant (vanilla / PM / RX-rate / multipath / window-probeless) at DPACC build time, tuning host-set parameters, and DOCA_PCC_DEV_STATUS_FAIL from the algorithm. Refuse and route elsewhere for writing a custom PCC algorithm from scratch, read-only PCC counter inspection, or firmware-only pre-Programmable PCC.

日本語の概要は準備中です。原文の説明を表示しています。

Use this skill for MolMIM, NVIDIA's BioNeMo NIM microservice for small-molecule latent-space generation and optimization. Invoke for MolMIM, molecular embeddings, hidden states, latent decoding, sampling around a seed SMILES, CMA-ES guided molecule generation, QED or plogP optimization, hosted NVIDIA API calls, or local Docker deployment.

日本語の概要は準備中です。原文の説明を表示しています。

Private built-in CCB configuration skill for agentroles.ccb_self. Design, edit, validate, and prepare reloads for .ccb/ccb.config, role bindings, providers, windows, workspaces, tool windows, sidebar, and provider startup inputs. Use only inside ccb_self; non-self agents should delegate CCB config changes to ccb_self.

日本語の概要は準備中です。原文の説明を表示しています。

Diagnose CCB runtime, mounted daemon graph, tmux namespace and panes, provider context, queue/inbox/trace, replies/artifacts, config drift, and storage boundaries. Use when the user asks what is broken, which agent is stuck, whether CCB is mounted, why a reply did not arrive, or what to check first.

日本語の概要は準備中です。原文の説明を表示しています。

Queue processing with fresh context per phase. Processes N tasks from the queue, spawning isolated subagents to prevent context contamination. Supports serial, parallel, batch filter, and dry run modes. Triggers on "/ralph", "/ralph N", "process queue", "run pipeline tasks".

日本語の概要は準備中です。原文の説明を表示しています。

Dependency management for Golang projects — go.mod and go.sum, `go get` install and upgrade flows, Minimal Version Selection, conflict resolution with replace/exclude/retract, `govulncheck` scanning of the module tree, outdated dependency and binary size auditing, vendoring, `tool` directives, and go.work workspaces. Use when adding, removing, or upgrading Go dependencies, deciding whether to take on a package, resolving version conflicts, or auditing what a module pulls in. Covers choosing and upgrading dependency versions, not the surrounding tooling: do NOT use for fixing an exploitable vulnerability in code (→ See `samber/cc-skills-golang@golang-security` skill) or for wiring Dependabot/Renovate update bots into CI workflows (→ See `samber/cc-skills-golang@golang-continuous-integration` skill).

日本語の概要は準備中です。原文の説明を表示しています。

Golang semantic code intelligence via `gopls`, the official Go language server — go-to-definition, find references, call/implementation hierarchy, workspace symbol search, package API discovery, diagnostics, safe rename, refactors (extract/inline/fill/rewrite code actions), formatting, and generated tests. Reaches an agent via gopls's own MCP server (`go_*` tools), Claude Code's native `LSP` tool, or the `gopls` CLI. Use when navigating or refactoring Go code — jumping to a definition, finding call sites before a rename, understanding a file's or package's dependencies, running diagnostics after an edit, or extracting/inlining/renaming. Not for the published ecosystem — packages not in your `go.mod`, versions, licenses, importers — → See `samber/cc-skills-golang@golang-pkg-go-dev` skill (`godig`). Not for a whole-tree vulnerability audit → See `samber/cc-skills-golang@golang-security` skill (`govulncheck`).

日本語の概要は準備中です。原文の説明を表示しています。

Solves CTF challenges by performing first-pass triage, identifying the dominant category, and routing execution to the right specialized ctf-* skill. Use when the user gives you a challenge bundle, a remote service, a suspicious file, or only a vague challenge description and you must determine where to start. Do not use it when the category is already clear and a specialized skill can be invoked directly; this is the dispatcher and recon entrypoint, not the deepest reference for category-specific techniques.

日本語の概要は準備中です。原文の説明を表示しています。

Generate original one-ink or controlled two-ink editorial images from any theme, sentence, article idea, object, or reference photo. Always use this skill when the user asks for 单色海报、双色印刷、单色调视觉、蓝色/绿色孔版印刷、risograph、网点照片、复古或当代编辑排版、zine poster, monochrome editorial poster, duotone print, or asks to use the mono-color style. It uses an adaptive white, gray, or pale-beige substrate, no more than two printing inks, active negative space, terse human language, and strong serif/grotesk/mono typography without making retro styling the default or copying a source composition, wording, logo, or artwork. Produce both the final generation prompt and the generated raster image unless the user explicitly asks for prompt only.

日本語の概要は準備中です。原文の説明を表示しています。

Control the live Pebrel terminal workspace from Codex or Claude Code. Use whenever the user asks to split panes, open a tab or file, run a command in another pane, start or prompt Codex/Claude, delegate a task to another agent, read output, wait for an agent, or says 分屏、开一个 Codex/Claude、打开 README、在上面/下面/左边/右边操作、把这个任务派给 Codex/Claude、让 codex 去改、问问另一个 agent、看看它跑完了没. Run `pebrel env` to orient, then use the supported Runtime API immediately instead of scanning processes or source code.

日本語の概要は準備中です。原文の説明を表示しています。

Fetch GitHub issues, spawn sub-agents to implement fixes and open PRs, then monitor and address PR review comments. Usage: /gh-issues [owner/repo] [--label bug] [--limit 5] [--milestone v1.0] [--assignee @me] [--fork user/repo] [--watch] [--interval 5] [--reviews-only] [--cron] [--dry-run] [--model glm-5] [--notify-channel -1002381931352]

日本語の概要は準備中です。原文の説明を表示しています。

Fetch Evolutionary Conservation scores (phyloP, phastCons) and Transcription Factor Binding Sites (TFBS) from the UCSC Genome Browser. Use when analyzing whether genomic variants or regions are evolutionarily conserved, functionally important, or bounded by TF regulators across major projects (ENCODE, JASPAR, ReMap).

日本語の概要は準備中です。原文の説明を表示しています。

Use when you want to retrieve semi-quantitative protein expression and spatial localisation data from the Human Protein Atlas (HPA).

日本語の概要は準備中です。原文の説明を表示しています。

Query, search, and download data from the openFDA API for drugs, devices, foods, tobacco, cosmetics, animal and veterinary products, substances, and transparency data. Use for FDA adverse events, recalls, labeling, approvals, shortages, 510(k) clearances, NDC lookups, and any FDA safety or regulatory data query across all 28 API endpoints.

日本語の概要は準備中です。原文の説明を表示しています。

Teaching a customer how to choose before any candidates appear, when they ask what matters in a category, how two approaches to it differ, or where to begin. Not needed once the customer has named the thing they want, however considered the purchase (that is search work), nor for outfitting a space or an event (planning-goals).

日本語の概要は準備中です。原文の説明を表示しています。

Modern minimalist aesthetic with clean lines, intentional color palette, subtle interactions, and consistent spacing.

日本語の概要は準備中です。原文の説明を表示しています。