「ecto」の検索結果

Use this skill when the user is invoking the DOCA PCC Counters tool — the `pcc_counters.sh` bash script under the DOCA tools directory — to arm and read the fixed firmware/hardware PCC (Programmable Congestion Control) diagnostic counters (CNP, RTT, WRED-drop, etc.) on a ConnectX / BlueField device via mst + the mlx5 debugfs `diag_cnt` interface. The script takes two positional args — `set | query` and an mst device path — with no `--help` or subcommands. Trigger even without "pcc_counters.sh" or "PCC counters": "how do I read the CNP / RTT / WRED-drop counters", "PCC counter stuck at zero", "the script says Bad Device", or "is congestion control dropping packets on this port?". Route elsewhere for writing a custom PCC algorithm (doca-pcc), factory firmware PCC config, DOCA install, or fleet-wide CC tuning.

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Run and operate the DeepStream Multi-View 3D Tracking reference app, also known as MV3DT. Use when the user asks to set up prerequisites, run shipped MV3DT samples, run Multi-View 3D Tracking on custom synchronized MP4 datasets, import camera calibration, delegate missing calibration to AutoMagicCalib, inspect OSD or BEV visualization, consume MV3DT Kafka metadata, or clean up MV3DT run state in the DeepStream MV3DT app directory.

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Extract per-molecule embeddings from any encoder-bearing KERMT checkpoint. Use a local checkpoint or optionally download a pinned Hugging Face model bundle using HF_TOKEN if configured. Run containerized embedding extraction and write model bundles, per-readout .npy embeddings, canonical SMILES, and validity arrays to user-selected host directories.

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Continue KERMT pretraining on a custom SMILES corpus with a grover_base, cmim, or hybrid checkpoint. Use a local checkpoint or optionally download a pinned Hugging Face model bundle using HF_TOKEN if configured. Run containerized training and write model bundles, prepared data, logs, and checkpoints to user-selected host directories.

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Finetune a pretrained KERMT encoder on a labeled CSV. Validate the checkpoint and data, prepare features, and run containerized training. Use a local checkpoint or optionally download a pinned Hugging Face model bundle using HF_TOKEN if configured. Write model bundles, prepared data, logs, and trained models to user-selected host directories.

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。

Create a reviewable Agent Skill package from mature curated wiki pages. Use when turning verified vault knowledge into a reusable skill. Reads the vault and writes only to a review directory; it does not install skills.

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List, create, or switch named Obsidian wiki vault profiles under the global config directory. Use when changing the active vault, checking which vault is active, or managing multi-vault profiles.

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Compile-time dependency injection in Golang using google/wire — wire.NewSet, wire.Build, wire.Bind (interface→concrete), wire.Struct, wire.Value, wire.InterfaceValue, wire.FieldsOf, cleanup functions, //go:build wireinject injector files, and generated wire_gen.go. Apply when using or adopting google/wire, when the codebase imports `github.com/google/wire`, or when wiring an application graph at compile time via `wire.Build`. For runtime DI with reflection, see `samber/cc-skills-golang@golang-uber-dig` skill.

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Golang project layout and workspace setup — cmd/internal/pkg directory conventions, module and package naming, go.work workspaces, and essential configuration files. Use when starting a new Go project, organizing an existing codebase, setting up a monorepo with multiple packages, creating CLI tools with multiple main packages, or discussing package restructuring, package splits, or module splits. Not for restructuring existing code without a layout change (→ See `samber/cc-skills-golang@golang-refactoring` skill).

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Look up Y Combinator companies and batches from the public yc-oss API, a static JSON dataset refreshed daily: company profiles, batch rosters (e.g. W25, S24), companies by industry or tag, top companies, who is hiring, founder-diversity lists, and overall YC stats. Use this skill whenever the user asks about YC-backed startups, a YC batch, YC companies in a sector or tag or that are hiring, the Y Combinator portfolio, or startup and venture research that draws on YC data. Read-only.

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Fetch financial and market data with the yfinance Python library (Yahoo Finance). Use this skill whenever the user wants stock data: current quotes and price history, financial statements (income statement, balance sheet, cash flow), options chains, dividends and splits, earnings and analyst estimates, price targets and ratings, institutional and insider holdings, news, multi-ticker comparisons, stock screens, or sector and industry data. Use it even when the user gives only a ticker symbol (AAPL, MSFT, TSLA) and the intent has to be inferred. For earnings previews or recaps, estimate revisions, valuation, correlation, liquidity, or ETF premium analysis, prefer the dedicated skill.

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Analyze sell-side analyst estimates and how they are changing, using Yahoo Finance data (yfinance): EPS and revenue consensus by period, estimate ranges and dispersion, revision trends over 7/30/60/90 days and up/down revision breadth, growth estimates vs industry, sector, and the S&P 500, and historical estimate accuracy. Use this skill when the user wants more than a single estimate lookup: estimate revisions or momentum, EPS trend, consensus changes, forward or next-quarter and annual estimates, the bull vs bear estimate spread, or growth projections across periods.

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Analyze how stocks move together using Yahoo Finance price history (yfinance): find correlated peers for a ticker, measure correlation, beta, and spread between specific tickers, cluster a group into a correlation matrix, and track rolling or regime-dependent correlation. Use this skill whenever the user asks what moves with a stock, what else drops when it drops, related tickers or sympathy plays, sector or supply-chain peers, pair trading or hedging pairs, beta or relative performance, correlation matrices, co-movement, or rolling/realized correlation — including well-known pairs like AMD/NVDA, GOOGL/AVGO, or LITE/COHR. With a single ticker, assume the user wants its correlated peers.

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[omh] Provider credentials without exposure: prepare provider-profile metadata without reading secrets or calling providers. Use when the user says: provider-profile-posture, provider profile posture, provider profile readiness, secret presence confirmation, connector profile posture, 공급자 프로필 상태, 시크릿 존재 확인, 커넥터 준비 상태.

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[omh] Unsure whether Codex or Claude Code is ready: executor runtime readiness - compare Codex, Claude Code, Hermes coding, and oh-my runtimes by tools and handoff mode; use external-connector-readiness for a named plugin or API, and toolbelt-readiness for the whole capability inventory. Use when the user says: executor-runtime-readiness, executor readiness, runtime readiness, codex readiness, claude code readiness, hermes coding readiness, executor tools, missing tools.

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A shell for the web. Navigate URLs like directories, query pages with Unix-like commands. Activate on `websh` command, shell-style web navigation, or when treating URLs as a filesystem.

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。

Azure Data Lake Storage Gen2 SDK for Python. Use for hierarchical file systems, big data analytics, and file/directory operations. Triggers: "data lake", "DataLakeServiceClient", "FileSystemClient", "ADLS Gen2", "hierarchical namespace".

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Azure Storage File Share SDK for Python. Use for SMB file shares, directories, and file operations in the cloud. Triggers: "azure-storage-file-share", "ShareServiceClient", "ShareClient", "file share", "SMB".

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Build search applications using Azure AI Search SDK for JavaScript (@azure/search-documents). Use when creating/managing indexes, implementing vector/hybrid search, semantic ranking, or building agentic retrieval with knowledge bases.

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。

Create Zustand stores with TypeScript, subscribeWithSelector middleware, and proper state/action separation. Use when building React state management, creating global stores, or implementing reactive state patterns with Zustand.

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Azure File Share JavaScript/TypeScript SDK (@azure/storage-file-share) for SMB file share operations. Use for creating shares, managing directories, uploading/downloading files, and handling file metadata. Supports Azure Files SMB protocol scenarios. Triggers: "file share", "@azure/storage-file-share", "ShareServiceClient", "ShareClient", "SMB", "Azure Files".

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KQL language expertise for writing correct, efficient Kusto Query Language queries. Covers syntax gotchas, join patterns, dynamic types, datetime pitfalls, regex patterns, serialization, memory management, result-size discipline, and advanced functions (geo, vector, graph). USE THIS SKILL whenever writing, debugging, or reviewing KQL queries — even simple ones — because the gotchas section prevents the most common errors that waste tool calls and cause expensive retry cascades. Trigger on: KQL, Kusto, ADX, Azure Data Explorer, Fabric Real-Time Intelligence, EventHouse, Log Analytics, log analysis, data exploration, time series, anomaly detection, summarize, where clause, join, extend, project, let statement, parse operator, extract function, any mention of pipe-forward query syntax.

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Detect A/B compartments from Hi-C data using cooltools and eigenvector decomposition. Identify active (A) and inactive (B) chromatin compartments from contact matrices. Use when identifying A/B compartments from Hi-C data.

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。

Process multiple sequence files in batch using Biopython. Use when working with many files, merging/splitting sequences, or automating file operations across directories.

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。