「experiment」の検索結果

INVOKE THIS SKILL for LLM-as-judge evaluation workflows on Arize: creating/updating evaluators, running evaluations on spans or experiments, tasks, trigger-run, column mapping, and continuous monitoring. Use when the user says: create an evaluator, LLM judge, hallucination/faithfulness/correctness/relevance, run eval, score my spans or experiment, ax tasks, trigger-run, trigger eval, column mapping, continuous monitoring, query filter for evals, evaluator version, or improve an evaluator prompt.

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。

Throwaway experiments to validate an idea before build.

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。

Build comprehensive ML pipelines, experiment tracking, and model registries with MLflow, Kubeflow, and modern MLOps tools. Implements automated training, deployment, and monitoring across cloud platforms. Use PROACTIVELY for ML infrastructure, experiment management, or pipeline automation.

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。

When the user wants to plan, design, or implement an A/B test or experiment. Also use when the user mentions "A/B test," "split test," "experiment," "test this change," "variant copy," "multivariate test," or "hypothesis." For tracking implementation, see analytics-tracking.

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。

Rigorous benchmarking of multi-agent coordination systems: experiment design, statistical analysis, human evaluation protocols, and reproducible reporting. NOT FOR ML model evaluation (use llm-evaluation-harness), A/B testing for web products, survey design, or general data 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。

Refute-before-prove research discipline: automated counterexample sweeps before any formalization, meter-integrity audits for information-bound experiments, mutation-tested model checkers, pre-registered commit-or-cut gates for speculative directions, wrong-turn reporting, and numeric-claim provenance. Use when validating any new theorem, bound, equilibrium, or security claim; when building or trusting a checker, simulator, or experiment; or when deciding whether a speculative research direction lives or dies. NOT for exploratory brainstorming, product prioritization, writing style, or literature review.

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。

ECCを通じてNasiko CLIの導入状況を確認し、固定バージョンのインストールと管理対象の削除を、事前プレビューや利用者の同意を踏まえて進めるスキル。

• Nasiko CLIの導入状況を調べたいとき
• 検証済みバージョンの導入前確認
• ECC管理下のCLIを削除したいとき

W&B: log ML experiments, sweeps, model registry, dashboards.

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。

言語モデル内部の反応を少数の特徴に分解し、学習した概念を調べます。学習済みSAEの分析、自作SAEの訓練、特徴を使った出力調整と品質評価を案内します。

• 学習済みSAEで特徴を調べたいとき
• 特定のモデル層にSAEを訓練する
• 入力文ごとの特徴の反応を比較する

Throwaway experiments to validate an idea before build.

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。

A lab-meeting deck on gut-microbiome links to sleep quality — the design, the results, the caveats, and the next experiment. Built as a decision-grade academic research deck for lab group, PI.

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。

Turn messy user research notes, interviews, support tickets, surveys, and product context into an evidence-backed decision room: a single HTML artifact with an evidence ledger, theme map, confidence heatmap, opportunity matrix, decision memo, and experiment queue. Use when teams need to move from qualitative signals to product or design decisions without fabricating certainty.

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。

The original v1 taste-skill, preserved for projects depending on its exact behavior. The current default is `design-taste-frontend` (v2 experimental), which is a substantial rewrite. Use this v1 install name only if you need exact backward compatibility.

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。

Design and optimize upgrade screens, paywalls, and upsell modals. Useful for SaaS conversion design and pricing-page 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。

Virtual try-on — see how clothes look on a person via fal.ai's hosted try-on models. Useful for ecommerce, lookbooks, and styling 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。

Full-lifecycle AI music album production — concept, lyric drafting, track sequencing, and export. Useful for indie album experiments and brand soundtracks.

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。

Improve Archify diagram accuracy, visual quality and complete authoring speed with fewer repairs. Use for generation experiments or evaluating changes to layout, routing, diagnostics, authoring instructions and acceptance rules against actual diagrams and agent traces.

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。

Start a new OpenSpec change using the experimental artifact workflow. Use when the user wants to create a new feature, fix, or modification with a structured step-by-step approach. Also use when the user says "openspec new change" or "opsx new".

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。

Archive a completed OpenSpec change in the experimental workflow. Use when the user wants to finalize and archive a change after implementation is complete. Also use when the user says "openspec archive" or "opsx archive".

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 preparing, tagging, and publishing a Cline desktop app (apps/examples/desktop-app) release — stable (desktop-vX.Y.Z from main), beta (desktop-vX.Y.Z-beta.N from desktop-experimental, shipped as the side-by-side "Cline Beta" app), or nightly (artifact-only test build of main's HEAD, tagged desktop-nightly-<stamp> after it builds). Guides changelog drafting, version bumps in package.json + tauri.conf.json, tagging, and the desktop-publish GitHub workflow that builds, signs, notarizes, and updates the per-channel auto-update feed.

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, write, or manage Meta ads and assets: ad copy, campaigns, spend, reports, audiences, catalogs, product feeds, feed refresh schedules, experiments, and policy. Always load for any request to create or write an ad, or to advertise a product or service, even when no platform is named; this includes sensitive or restricted categories. Always load for any question asking what a Meta, Facebook, or Instagram advertising policy means, allows, prohibits, or requires, including a standalone policy-definition question with no account context. Those questions must use ads_policy_tool, never browser search or memory. Load for a specifically named catalog or feed with an upload or refresh-schedule request; use Ads reads to resolve ownership before writing. Generic unnamed feeds need context. Whether an image, claim or piece of copy may be used in an ad is ALWAYS a Meta Ads task — 'can I use this in an ad', 'is it allowed', 'is this against policy', and any rights, likeness, celebrity, logo or trademark question about advertising with an image, including a follow-up about one just generated. Those are ads-policy questions, not general legal ones. An ad request uses the campaign workflow unless explicitly only an image or organic post.

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。

Import a recorded Remotion Canvas Capture into a project without Studio interactions using the internal experimental-codemod command. Use when adding a capture file as an editable composition with cursor keyframes.

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。

When the user wants to set up a recurring, self-running marketing workflow — a repeatable loop an AI agent runs on a cadence (weekly, daily, on a trigger) rather than a one-off task. Also use when the user mentions 'marketing loop,' 'recurring marketing workflow,' 'automate my marketing,' 'marketing on autopilot,' 'weekly marketing review,' 'ad fatigue check,' 'content refresh loop,' 'churn watch,' 'ranking drop alert,' 'run my SEO,' 'SEO operator,' 'daily SEO agent,' 'run my outbound,' 'AI SDR,' 'reply triage,' 'always-on marketing,' 'marketing automation workflow,' or 'run this every week.' Use this to pick, adapt, and schedule an ongoing marketing loop that orchestrates the other marketing skills. For one-off marketing ideas, see marketing-ideas. For the experimentation loop specifically, see ab-testing.

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。

Experimental NotebookLM harness for listing notebooks, managing sources, asking questions, generating artifacts, and downloading outputs through an installed notebooklm CLI.

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。