244 件 ・ 関連度順
概要と使いどころ
Data-backed email marketing skill for AI agents. Use when building or running email automation, driving an ESP from an agent (MCP/connectors), diagnosing deliverability, writing or de-slopping email copy, directing AI email design, choosing a platform, or pulling benchmarks. Covers flows, segmentation, compliance, cold email, WhatsApp, SMS and RCS, and 19 industry playbooks.
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。
Filesystem RAG benchmarks: corpus/, train.json, evaluate_rag.py (RAGAS quality). Not for prod monitoring, latency/throughput benchmarking (use rag-perf), or evals outside this repo layout.
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。
Golang benchmarking, profiling, and performance measurement. Use when writing, running, or comparing Go benchmarks, profiling hot paths with pprof, interpreting CPU/memory/trace profiles, analyzing results with benchstat, setting up CI benchmark regression detection, or investigating production performance with Prometheus runtime metrics. Also use when the developer needs deep analysis on a specific performance indicator - this skill provides the measurement methodology, while `samber/cc-skills-golang@golang-performance` provides the optimization patterns.
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 the user asks to "analyze competitors" or "竞品分析"; benchmarks competitor keywords, content, backlinks, AI citations, and traffic share into strengths, weaknesses, and an action plan. Not for a pairwise topic-coverage gap map — use content-gap-analysis. 竞品分析/竞争对手
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。
Implement load testing, auto-scaling, and capacity planning for Claude API. Use when running performance benchmarks, planning for traffic spikes, or configuring horizontal scaling for Claude-powered services. Trigger with phrases like "anthropic load test", "claude scaling", "anthropic capacity planning", "scale claude api".
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。
Guides performance investigation, benchmarking, and optimization of the Grida Canvas web editor (TypeScript reducer, Immer, React hooks). Use when profiling reducer dispatch cost, diagnosing slow interactions (drag, resize, color change), writing or running editor benchmarks, instrumenting with PerfObserver, or optimizing the JS-side state management pipeline.
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。
Choose and audit startup metrics using Croll and Yoskovitz's "Lean Analytics". Use when the user mentions "what metrics should we track", "KPIs", "north star metric", "One Metric That Matters (OMTM)", "vanity metrics", "analytics dashboard", "DAU/MAU", "churn benchmark", or "measure product-market fit". Also trigger when choosing metrics for a startup or feature, auditing a dashboard for vanity metrics, setting metric targets and baselines, or instrumenting a product by business model and stage. Covers good-vs-vanity metrics, the One Metric That Matters, metrics by business model, the five startup stages, and benchmarks. For the build-measure-learn loop, see lean-startup. For fixing activation and retention, see improve-retention.
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。
Testing standards for LoongCollector: unit tests, e2e tests, benchmarks. Reference when writing or reviewing tests.
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。
Go testing patterns including table-driven tests, subtests, benchmarks, fuzzing, and test coverage. Follows TDD methodology with idiomatic Go practices.
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。
Establish project governing principles including dev guidelines, code quality standards, testing policies, UX requirements, performance benchmarks, and security constraints.
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。
Evaluation harness for testing agent and skill quality through structured benchmarks, regression tests, and quality scoring.
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。
Analyze weekly marketing campaign performance data across channels. Use when analyzing multi-channel digital marketing data to calculate funnel metrics (CTR, CVR) and compare to benchmarks, compute cost and revenue efficiency metrics (ROAS, CPA, Net Profit), or get budget reallocation recommendations based on performance rules.
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。
Read-only evo run reporting. Use when the user invokes /evo:report, asks what happened overnight, asks what improved recently, asks for the best/frontier candidates, asks for a quick score chart without opening the dashboard, or wants the scatter plot in chat output. Never run benchmarks, gates, Slurm commands, evo run, or ad-hoc verification scripts for report requests.
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。
Creates, edits and benchmarks skills; supersedes the official skill-creator plugin, so when both are listed, use this one. Use when the user wants to create or improve a skill or run skill evals, or to distill work into a skill even without saying "skill": 把这次 session 做成一个 skill / 把以前的对话沉淀到 skill 里 / 从我认可的样例里提炼我的喜好.
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。
Tests/benchmarks a third-party LLM endpoint (OpenAI- or Anthropic-compatible): availability, fidelity, speed, concurrency, protocol compliance, quality regression. Use before hand-rolling a curl loop, when onboarding a provider, or debugging "system prompt 不生效" / a tok/s claim — 测评/压测一个模型或渠道. Not for TTS/voice-clone supplier eval (use the audio 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。
Analyze weekly marketing campaign performance data across channels. Use when analyzing multi-channel digital marketing data to calculate funnel metrics (CTR, CVR) and compare to benchmarks, compute cost and revenue efficiency metrics (ROAS, CPA, Net Profit), or get budget reallocation recommendations based on performance rules.
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。
**WORKFLOW SKILL** - Evaluate AI agent skills using structured benchmarks with YAML specs, fixture isolation, and pluggable validators. USE FOR: run waza, waza help, run eval, run benchmark, evaluate skill, test agent, generate eval suite, init eval, compare results, score agent, agent evaluation, skill testing, cross-model comparison. DO NOT USE FOR: improving skill frontmatter (use waza dev), creating new skills from scratch (use skill-creator), token counting or budget checks (use waza tokens). INVOKES: Copilot SDK executor, mock engine, code/regex validators. FOR SINGLE OPERATIONS: use waza run directly for a single benchmark.
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。
Help users objectively assess where their product stands on the PMF spectrum by triangulating qualitative feedback, quantitative retention benchmarks, and organic growth signals.
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。
Apply CIS benchmarks and secure Linux servers. Configure SSH, manage users, implement firewall rules, and enable security features. Use when hardening Linux systems for production or meeting security compliance requirements.
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 and remediate CIS benchmark violations. Use automated tools to assess compliance and implement hardening recommendations. Use when meeting compliance requirements or implementing security baselines.
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。
Harden Windows servers per security baselines and CIS benchmarks. Configure Group Policy, Windows Defender, and security features. Use when securing Windows Server environments.
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。
Optimize MATLAB design files for GPU Coder to generate faster CUDA code. Iteratively profiles, rewrites, and benchmarks until performance targets are met or diagnostics are resolved. Use when asked to: optimize for GPU Coder, improve GPU codegen performance, profile generated GPU/CUDA code, profile GPU MEX, fix gpuPerformanceAnalyzer diagnostics, speed up GPU MEX, reduce GPU memory transfers, improve kernel parallelism, rewrite MATLAB for CUDA, or run gpuPerformanceAnalyzer.
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。
Shopify/DTC profit margin calculator for sellers. Calculate cost breakdowns including ad spend, CAC, payment processing fees, and 3PL costs. Includes LTV/CAC analysis and DTC-specific benchmarks. No API key required.
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。