「aria」の検索結果

Use the fair-esm repository skill for protein language-model embeddings, ESMFold structure prediction, ESM-IF1 inverse folding, and zero-shot variant-effect 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。

Operate Tongyi DeepResearch and its WebAgent family: ReAct inference setup, rollout validation, benchmark evaluation, and variant routing.

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 denoising-diffusion-pytorch for PyTorch DDPM/DDIM image diffusion, 1D sequence diffusion, conditioning and guidance, and advanced diffusion variants.

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 CausalNex to learn causal structures, fit Bayesian networks, discretize features, generate synthetic graph data, and run inference, evaluation, and latent-variable 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 Chronos Forecasting for pretrained time-series forecasting, Chronos-2 covariates, data validation, fine-tuning, evaluation, and deployment planning.

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 the ALAE repository for Adversarial Latent Autoencoder data preparation, CUDA training, checkpoint-backed generation, latent editing, and legacy 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。

N-day / patch-diff workflow - given a CVE/advisory or a suspicious patch, diff pre- vs post-patch to locate the fixed bug, build a PoC for the unpatched version, and run variant analysis for a fresh bug. Triggers - "n-day", "patch diff", "diff the patch", "bindiff".

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, generate, write, or scaffold Terraform .tf HCL — resources, modules, providers, variables, outputs.

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。

Prepare the local environment for the Maestro smoke-test suite — verify tooling, select a device, collect the APK if needed, validate the .env file by variable name only, then hand the user the exact lab-store CLI command to run or run it on request.

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。

Generate screenshot coverage for screen-level Compose previews from the current diff or a specific target, check required visual and data variations, and produce a compact visual report

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。

End-to-end AI video production skill for agentic frameworks. Use when the user asks to make, edit, repurpose, caption, soundtrack, or export videos using HeyGen avatars, Seedance or ByteDance b-roll, OpenAI image generation and editing, AI UGC ads, Remotion, HyperFrames, screen recordings, FFmpeg, captions, ElevenLabs music, Suno, or social-video variants.

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 evolving aggregate invariants, value objects or domain events in an existing DDD-style Spring Boot 4 application, or when DDD is explicitly requested. Preserve existing API identifiers and architecture when changing domain behavior.

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 evolving aggregate invariants, value objects or domain events in an existing DDD-style Spring Boot 3 application, or when DDD is explicitly requested. Preserve existing API identifiers and architecture when changing domain behavior.

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。

Orchestrate autonomous AI development pipelines through your Kanban board (Asana, GitHub Projects, Linear). Manages multi-worker Claude Code dispatch, deterministic quality gates, adversarial review, per-task cost tracking, and crash-proof pipeline execution.

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, iterate, and scale paid ad creative for Google Ads, Meta, LinkedIn, TikTok, and similar platforms. Use when generating headlines, descriptions, primary text, or large sets of ad variations for testing and performance optimization.

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。

Advogado especialista em todas as areas do Direito brasileiro: familia, criminal, trabalhista, tributario, consumidor, imobiliario, empresarial, civil e constitucional.

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 designing an A/B or split test: define the hypothesis, control and variants, estimate sample size, verify tracking, and predeclare metrics and stopping 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。

Advogado criminalista especializado em Maria da Penha, violencia domestica, feminicidio, direito penal brasileiro, medidas protetivas, inquerito policial e acao penal.

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 new skills, modify and improve existing skills, and measure skill performance. Use when users want to create a skill from scratch, edit, or optimize an existing skill, run evals to test a skill, benchmark skill performance with variance analysis, or optimize a skill's description for better triggering accuracy.

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。

Manages privacy compliance for employee background checks including criminal record processing under Art. 10 GDPR, DBS checks (UK), national law variations, and reference verification. Applies proportionality and data minimisation to pre-employment screening, defines retention limits, and addresses role-based necessity assessments. Keywords: background check, criminal record, Art. 10, DBS, pre-employment screening, vetting, data minimisation, proportionality.

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。

OI-3 spike harness — the INLINE (non-forked) readability-guidance variant. Surfaces the shared readability standard into the calling skill's own context. Use only when a spike consumer skill invokes it.

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。

Surfaces Han's shared Human-Readable Output Standard — the readability rule and the writing-voice profile — into the calling skill's own context, so the caller drafts in voice and runs its self-check against the current standard sourced from one canonical copy. Use when a prose-producing skill needs the shared readability standard available in context before it drafts. Governs the shape of a written deliverable, where explanation-guidance governs what a run says to a person in a turn. Runs in the caller's context and hands control straight back; it does not produce a deliverable of its own, rewrite anything, or judge the caller's work. Does not run the adversarial rewrite pass — dispatch the readability-editor agent for that, or use edit-for-readability to rewrite an existing target. Does not cover explaining technical work to a reader who will not implement it — use explanation-guidance for that.

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。

Researches an open-ended question — options, possible solutions, prior art, trade-offs, or how something works — and produces a durable, evidence-backed, adversarially-validated report that recommends an option without committing the team to any artifact. Use when you want to research approaches, weigh options, survey prior art or the state of the art, or understand how something works before committing to a direction. Does not diagnose a bug, failure, or root cause — use investigate. Does not specify a feature — use plan-a-feature. Does not create or update a coding standard — use coding-standard. Does not compare two concrete artifacts for gaps — use gap-analysis. Does not assess an existing module's architecture — use architectural-analysis. Does not capture feedback on Han's own skills — use han-feedback.

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。

Designs the contract for an API change inside one codebase — a component's props, a function surface, URL or query parameters, an event payload, or a module boundary — through a discovery pass, an options document with one recommendation, a question round, and an adversarial validation round, with every element of the contract justified from one stated goal. Use when you want to design, shape, decide, or nail down an interface, contract, signature, or API change for a capability you can already describe, sized for roughly one pull request. Produces a design document and changes no code. Does not specify what a feature should do — use plan-a-feature. Does not plan delivery or sequencing — use plan-implementation. Does not assess the architecture of existing code — use architectural-analysis. Does not write the code — use tdd. Does not restructure existing code — use refactor. Runs its rounds without pausing for review; to review each round as it lands, use pairing.

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。