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概要と使いどころ
Generate consistent UTM parameters, GA4 event naming, and conversion tracking specs following taxonomy best practices. Use when describing campaign structure, requesting UTM links, needing GA4 event names, or wanting to standardize tracking nomenclature across marketing channels. Platform: Google and Meta.
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。
Activate for OSS adoption work -- README conversion surfaces, quickstart, templates, release announcements, contributor funnel, story angles -- and any update to the maintained growth strategy at WIP/growth-strategy.md.
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。
Audit, diagnose, and safely operate connected Reddit Ads accounts through the NotFair MCP. Use for Reddit advertising, Reddit Ads performance, campaign or ad-group analysis, spend, conversions, targeting, audiences, pixels, budgets, bids, creative, campaign setup, or approved Reddit Ads changes.
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。
Audit, diagnose, and safely operate connected X Ads (Twitter Ads) accounts through the NotFair MCP. Use for X Ads performance, campaign or line-item analysis, spend, conversions, targeting, promoted posts, audiences, budgets, bids, creative, campaign setup, or approved X Ads changes.
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。
Manage Google Ads — performance, keywords, bids, budgets, negatives, campaigns, ads, search terms, QS, location targeting, bulk operations, experiments, asset management, portfolio bidding, offline conversions. Use for any mention of Google Ads, CPA, ROAS, ad spend, or campaign settings.
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。
Audit, diagnose, plan, and safely operate connected LinkedIn Ads accounts through the NotFair MCP, with an export-based fallback. Use for LinkedIn advertising, sponsored content, lead-generation forms, job-title or company targeting, campaign groups, creatives, conversions, lead quality, budgets, bids, or approved LinkedIn campaign changes.
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。
Audit, diagnose, and safely operate connected TikTok Ads accounts through the NotFair MCP. Use for TikTok advertising, Spark Ads, short-form video ads, campaign or ad-group analysis, spend, conversions, targeting, creative, budgets, bids, creator briefs, campaign setup, or approved TikTok Ads changes.
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。
Produce a read-only, evidence-based paid-media performance review across connected platforms or supplied exports. Use for weekly or monthly reports, scorecards, performance, CPA, ROAS, CTR, spend trends, pacing, or conversion-tracking health.
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 whenever the user asks for a PDF — generating a new one from scratch (reports, invoices, letters), extracting text/tables from an existing PDF, or filling in an existing PDF form. Does not cover converting an existing Word/PowerPoint/Excel file to PDF (that requires LibreOffice, not available in this environment — see file-conversion).
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。
Materials science toolkit. Crystal structures (CIF, POSCAR), phase diagrams, band structure, DOS, Materials Project integration, format conversion, for computational materials science.
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。
Convert existing plain or manual PyTorch training code into an NVFLARE federated job using Client API model exchange, local validation, and job export; use when the user names plain PyTorch or preliminary source inspection identifies one plain-PyTorch owner, and not for Lightning, other frameworks, deployment, POC/production lifecycle, or experiment workflows.
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。
Router for NVIDIA NuRec/NRE: USDZ rendering, NCore conversion, 3DGS, gRPC sensor sim, carline adaptation, PhysicalAI HF datasets. Do NOT use for SimReady or infra setup.
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。
Convert existing Hugging Face Transformers Trainer or TRL SFTTrainer training code into an NVFLARE federated job using flare.patch(trainer), local validation, and job export; use when the user names Hugging Face or preliminary source inspection identifies one Hugging Face owner, and not for manual PyTorch loops, Lightning, inference-only pipelines, deployment, or experiment workflows.
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 for agent-assisted Auto-FL optimization of an existing NVFLARE job in simulation, POC, or production. Do not use for code conversion, diagnosis-only work, or deployment setup.
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。
Compute federated statistics over tabular data (count, sum, mean, stddev, var, histogram, quantile, noise-protected min/max) and image data (count, failure_count, pixel-intensity histogram) across NVFLARE sites via FedStatsRecipe — automatic and non-interactive from the dataset, feature names (header or supplied), and optionally a README or notes declaring which statistics to compute; do not use for model training conversion, hierarchical statistics, deployment, POC/production lifecycle, or failed-job diagnosis.
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。
Internal NVFLARE conversion references and templates. Use only when another NVFLARE skill directs you to a shared workflow, policy, or asset.
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。
Plan, configure, and chain repo-native Nemotron customization steps into single-step or multi-step pipelines: curation, translation, SFT/PEFT (AutoModel or Megatron-Bridge), pretraining/CPT, RL alignment (DPO/RLVR/GRPO/RLHF), BYOB/MCQ benchmarks, checkpoint conversion, ModelOpt optimization, env profiles, and evaluation of trained checkpoints or existing/hosted endpoints. Use when a request names a Nemotron step or workflow, or asks to clean, translate, train, fine-tune, align, convert, optimize, evaluate, or compose these into a pipeline. Do NOT use for frontend/dashboard/visualization work, generic ML advice, billing/access, or non-Nemotron coding 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。
Serve and visually inspect a converted LeRobot dataset in the browser. Use for videos and state/action timelines; do not use for raw workflow HDF5 or incomplete conversion output.
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。
Convert workflow HDF5 recordings to LeRobot datasets for training or browser inspection. Use for conversion; do not use for replay, augmentation, or raw-data repair.
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。
Convert a grover_base checkpoint (encoder-only or encoder + vocab heads) into a hybrid checkpoint by adding a randomly-initialized cMIM decoder + latent_dist, then continue pretraining on the user's corpus as hybrid (vocab + contrast). Effectively kermt-continue-pretrain with a one-time ckpt-conversion step prepended.
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。
Used for header-only preflight of one DICOM series folder before conversion or inference. Not for de-identification or clinical clearance.
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。
Defensive Golang coding against accidental bugs — nil panics, typed-nil interfaces, `append` backing-array aliasing, silent int64-to-int32 truncation, float `==` comparison, `defer` inside loops, defensive copies of slices and maps, and usable zero values. Use when a Go program panics on a nil map write or nil pointer dereference, when reviewing code for nil-safety, numeric conversion overflow, or resource lifecycle, or when designing a type whose zero value must be safe. Not for designing concurrent access with goroutines, channels, or sync primitives (→ See `samber/cc-skills-golang@golang-concurrency` skill), not for exploitable vulnerabilities such as injection, weak crypto, or leaked secrets (→ See `samber/cc-skills-golang@golang-security` skill), and not for debugging an already-failing program (→ See `samber/cc-skills-golang@golang-troubleshooting` 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。
Explaining how the business is doing, meaning why a metric moved, which segment drove it, pace against a comparable, progress against goals the operator has stated, and questions over sales, traffic, conversion, and customers or this operation's equivalents that the snapshot alone does not answer. Not needed when the snapshot's headline figures and their change on the prior period answer the question, how a period went included.
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 creating animated demos (GIFs) for pull requests or documentation. Covers terminal recording with asciinema and conversion to GIF/SVG for GitHub embedding.
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。