「custom」の検索結果

Analyze project and auto-configure agents, skills, rules, and guides

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。

Disciplined goal-to-execution workflow for any user task. Parses objective, asks only for materially missing requirements via ambiguity-gate, inspects repo via idea, plans via sdd-dev or deep-plan, executes safely under project conventions, verifies completion per R020, and reports changed files with evidence. Use when user invokes /goal <task>.

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。

Fix broken agent references and symlinks

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 Self Driving — autonomous release loop that processes all auto-dev-eligible GitHub issues until none remain, by repeatedly running /pipeline auto-dev then /homework.

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。

Spin up a working LiveAvatar demo from a curated catalog — clones the reference repo, installs dependencies, provisions the LiveAvatar account, and fills the env file, then hands off the parts only a human can do. Use when: (1) User wants to try, test, see, or demo LiveAvatar, (2) User asks what LiveAvatar demos or examples exist, (3) User wants a sales agent / lead-qualification avatar, (4) User wants a LiveKit agent driving a LiveAvatar avatar, (5) User wants an avatar joining their own LiveKit room, (6) User wants a speech-to-speech avatar, a GPT-Live demo, a language-learning or tutor avatar, a customer-support avatar, a poker coach / game-style avatar, or an avatar with on-screen visuals/overlays, (7) User says "run the LiveAvatar demo", "show me LiveAvatar", "get me started with LiveAvatar", or "clone the LiveAvatar example", (8) User is evaluating LiveAvatar and wants something running before writing their own integration.

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。

Inspect scoped Autodesk data, compare versioned BOMs, and prepare ownership-aware drafts or approved custom-property changes. Not for implicit PLM release, membership changes or CAD geometry editing.

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 interactive AI role-play training activities as self-contained HTML. Use when the user asks to generate a role-play, persona practice, sales simulation, customer conversation drill, compliance scenario, or any learner-vs-AI-character training exercise.

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。

Send communications through Openapi - SMS with custom sender and OTP (SMS v2), Italian certified e-mail (PEC/Legalmail), bulk certified mail (Massive REM), and physical mail via Poste Italiane (registered letters, telegrams, judicial acts). Use when the user wants to send a message, letter or certified communication.

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 publication-quality figures with matplotlib using the object-oriented Figure/Axes API, constrained_layout, rcParams customization, TrueType (Type-42) font embedding for journal submission, and CVD-safe palettes. Covers seaborn integration, common chart types, axis formatting, and the small gotchas that distinguish reproducible matplotlib from notebook scratch. Use when producing publication figures in Python — RNA-seq scatter, single-cell embeddings, generic biological plotting.

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 sequence logos from aligned DNA, RNA, or protein motifs using ggseqlogo (R), Logomaker (Python), or WebLogo with explicit bits vs probability encoding, background-frequency correction, custom alphabets, and multi-logo stacking. Use when visualizing motif PWMs (TF binding, splice sites, CRISPR spacers), aligned-position composition, or comparing two motif sets.

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 pooled sgRNA libraries for CRISPR knockout, interference (CRISPRi), activation (CRISPRa), Cas12a multiplex, base-editor, and prime-editor screens. Covers on-target scoring (Rule Set 2, Azimuth, DeepSpCas9, CRISPRon), off-target scoring (CFD, MIT), TSS-relative positioning for CRISPRi/a (Horlbeck, Dolcetto, Calabrese), PAM-variant chemistries, control-guide composition, oligo cloning architecture, and library QC. Use when choosing a genome-wide library (GeCKOv2 vs Avana vs Brunello vs TKOv3 vs Inzolia), designing a focused or paralog-focused custom library, picking CRISPRi vs CRISPRa TSS windows, deciding control-guide proportions, or diagnosing library skew and dropout in a freshly cloned pool.

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。

Predict RBP binding from RNA sequence using deep learning models (RBPNet sequence-to-signal, RNAProt RNN, GraphProt2 GCN with structure, DeepCLIP, DeepRiPe multi-modal CNN) for variant-effect prediction, in silico binding-site discovery, model interpretation, and transfer learning from CLIP and RBNS datasets. Use when computational prediction of RBP binding from sequence is needed, evaluating variant effects on binding without further wet-lab experiments, comparing model performance, or training a custom model on ENCODE eCLIP data.

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。

Master advanced AgentDB features including QUIC synchronization, multi-database management, custom distance metrics, hybrid search, and distributed systems integration. Use when building distributed AI systems, multi-agent coordination, or advanced vector search applications.

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。

비대한 커스텀 훅을 스코프별 서브 훅으로 분리, composer 패턴 적용, 전용 서브디렉토리 구조화

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。

비대한 React 컴포넌트를 스코프별 서브 컴포넌트로 분리, 시맨틱 HTML 적용, 전용 서브디렉토리 구조화

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。

Extract text, tables, and structured data from documents using prebuilt and custom models.

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。

Azure AI Document Intelligence SDK for .NET. Extract text, tables, and structured data from documents using prebuilt and custom models.

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 text and images for harmful content with customizable blocklists.

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。

Set up, audit, and debug analytics tracking implementation — GA4, Google Tag Manager, event taxonomy, conversion tracking, and data quality. Use when building a tracking plan from scratch, auditing existing analytics for gaps or errors, debugging missing events, or setting up GTM. Trigger keywords: GA4 setup, Google Tag Manager, GTM, event tracking, analytics implementation, conversion tracking, tracking plan, event taxonomy, custom dimensions, UTM tracking, analytics audit, missing events, tracking broken. NOT for analyzing marketing campaign data — use campaign-analytics for that. NOT for BI dashboards — use product-analytics for in-product event analysis.

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。

AI agent development workflow for building autonomous agents, multi-agent systems, and agent orchestration with CrewAI, LangGraph, and custom agents.

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 container-based Foundry Agents with Azure AI Projects SDK (ImageBasedHostedAgentDefinition). Use when creating hosted agents with custom container images in Azure AI Foundry.

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。

Save, load, update, delete, merge, and navigate entity objects using TMS Aurelius ORM (TObjectManager). Use when the user asks how to persist or retrieve data with Aurelius, manage object lifetime, work with associations or collections at runtime, handle transactions, use cached updates, or control concurrency. Does NOT cover query DSL or criteria/projections (those are in a separate skill). Triggers on requests like "save an entity with Aurelius", "load a customer from the database", "add items to a collection", "how do I update an object", "flush changes", "delete a record with Aurelius", "merge a transient object", "how do transactions work in Aurelius", "batch updates Aurelius".

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。

Run or resume a deliverable active-outreach workflow across lead discovery, screening, customer intel, and outreach email. Use when an operator or system pipeline needs durable run state, visible intermediate artifacts, evidence gates, report-bound human approval, and a final editable email draft that is never auto-sent.

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。

Normalize an OpenClaw lead bundle into a conservative lead-screening package with missing-field warnings, manual-review reasons, and customer-intel-ready payloads.

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。