「kage」の検索結果

Validate an Agent Skill package and choose the right instruction, capability, or lifecycle primitive before implementation.

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。

Focused interactive tutor for the Agent Skills Engineering path in AI Engineering from Scratch. Start or resume this route when a learner wants to create, discover, invoke, secure, evaluate, package, or port Agent Skills. Teaches one lesson per invocation and records evidence in AGENT-SKILLS-LEARNING.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。

Build data-driven 2D character rigs for local animation: parts, pivots, layers, constraints, views, and reusable rig packages.

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。

Capture matching 2x Remotion Studio timeline screenshots and make a before/after crop reveal in packages/brand. Use for timeline layout comparison videos, including recapturing a historical 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。

Guides for writing and editing Remotion documentation. Use when adding docs pages, editing MDX files in packages/docs, or writing documentation content.

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 Remotion Studio from packages/example and open it in the Codex browser. Use when the user invokes /studio or $studio, asks to launch the example Studio, or wants the Remotion Studio dev UI available locally.

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。

Upgrade Mediabunny and related @mediabunny packages across the Remotion repo. Use when asked to update Mediabunny to the latest version.

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。

Document Remotion skill placement. Use when adding, moving, or editing Remotion skills to decide whether a skill belongs in .agents/skills as an internal skill or packages/skills as a public 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。

Add a new effect to @remotion/effects, including implementation, package exports, docs, demos, preview images, Remotion skill updates, formatting, and builds.

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 the local @remotion/convert app and open it in the Codex browser. Use when the user invokes /convert or $convert, asks to launch convert.remotion.dev locally, or wants to inspect the Convert package UI.

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。

Add a browser WebCodecs bug to the Remotion Mediabunny WebCodecs bugs docs page. Use when given a Chromium, WebKit, or Firefox issue URL that should be tracked in packages/docs/docs/mediabunny/webcodecs-bugs.mdx, especially when needing to look up the issue title, filing date, reporter, and resolution state before editing the MDX table.

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。

Add a new Remotion bug entry to packages/bugs/api/[v].ts. Use when the user describes a bug and affected Remotion versions that should be surfaced through the bugs 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。

Upgrade Remotion, and related packages

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 wants to prepare or verify a Twenty app for npm or marketplace publication, including README/About copy, package metadata, defineApplication marketplace metadata, logos, screenshots, and public assets.

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 create, plan, or optimize a lead magnet for email capture or lead generation. Also use when the user mentions "lead magnet," "gated content," "content upgrade," "downloadable," "ebook," "cheat sheet," "checklist," "template download," "opt-in," "freebie," "PDF download," "resource library," "content offer," "email capture content," "Notion template," "spreadsheet template," "what should I give away for emails," "course as a skill," or "package our content as an agent skill." Use this for planning what to create and how to distribute it. For interactive tools as lead magnets, see free-tools. For writing the actual content, see copywriting. For the email sequence after capture, see emails.

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。

Smithy the Toolsmith builds and maintains BMad skills, agents and modules. Use when the user asks for Smithy or says "build a skill", "make an agent", "scaffold a skill", "turn my session logs into a skill", "fix this skill", "convert this prompt to a skill", "review this skill", "package a module", "validate my module" or "migrate my old module". Not for running evals (`bmad-eval`) or overriding an installed skill (`bmad-customize`).

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。

Command-line interface for Mubu - Canonical packaged entrypoint for the Mubu live bridge....

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。

Supports work with Outpost Bio's open microbiome foundation models - the Waypoint checkpoints (Waypoint-6m, Waypoint-45m, Waypoint-170m), the Atlas pretraining corpus, the Compass eight-task benchmark, or the `waypoint` CLI from the `waypoint-bio` package. Covers embedding microbiome samples, fine-tuning on taxonomic abundance data, benchmarking a checkpoint on Compass, pretraining a GPT-2 model on taxonomic abundance profiles, and converting MetaPhlAn, Kraken2, QIIME 2, or MGnify abundance tables into waypoint format.

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。

Builds, evaluates, and audits right-censored or competing-risk survival workflows with scikit-survival, including leakage-safe preprocessing, model selection, probability prediction, and censoring-aware metrics.

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。

Performs bulk RNA-seq differential expression analysis with PyDESeq2, including count validation, formula designs, explicit contrasts, Wald tests, FDR correction, coefficient-matched LFC shrinkage, and result visualization. Use for PyDESeq2 or Python DESeq2 workflows with biological replicates.

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 and audits editable scientific posters in macro-free PowerPoint (.pptx) from author-approved local content and assets. Used when the requested deliverable is a PowerPoint research/conference poster and exact physical, printer, accessibility, provenance, and package-security checks are 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。

Builds, simulates, transpiles, and executes quantum circuits with Qiskit and IBM Quantum Runtime. Use for Qiskit 2.x circuits and operators, V2 Sampler or Estimator primitives, target-aware transpilation, local or noisy simulation, IBM QPU execution, Runtime sessions or batches, error mitigation, and Qiskit ecosystem packages.

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。

Deep learning framework (PyTorch Lightning / lightning package). Organize PyTorch code into LightningModules, configure Trainers for multi-GPU/TPU, implement data pipelines, callbacks, logging (W&B, TensorBoard, MLflow), distributed training (DDP, FSDP, DeepSpeed), for scalable neural network training.

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。

Plans and audits use of ChicagoHAI HypoGeniC/HypoRefine for LLM-assisted hypothesis generation from labeled text datasets. Use for the `hypogenic` package, its task configs, hypothesis banks, or HypoBench datasets—not for manual hypothesis formulation or scientific validation.

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。