「iste」の検索結果

Azure AI Agents Persistent SDK for .NET. Low-level SDK for creating and managing AI agents with threads, messages, runs, and tools.

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。

Discover RBP binding motifs from CLIP-seq peaks or single-nucleotide crosslink sites using HOMER, MEME/STREME, kpLogo, mCross (CL-position-registered motifs), PEKA (positional k-mer enrichment), RBPamp (affinity), and RNA Bind-n-Seq (RBNS) cross-validation. Use when characterizing RBP sequence specificity, registering motifs to crosslink positions, validating in vivo CLIP motifs against in vitro RBNS Kd, reconciling motif disagreements across tools, or correcting for the uracil crosslinking bias that contaminates raw CLIP motif logos.

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 this skill when selecting or replacing an ELD provider. Covers the FMCSA Registered ELD list, evaluation criteria, common provider removals from the registered list, and the 60-day transition rule.

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 this skill to maintain a compliant DOT accident register. Covers § 390.15 requirements, what's recorded, retention period.

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。

An innate exploratory drive that guarantees no graph node remains permanently invisible to an agent population. After a warm-up period (step > 3), each agent fires a coverage scan with probability |unseen_nodes| / |all_nodes|. When triggered, the agent teleports directly to the globally unseen node with the highest belief uncertainty, works it, and returns control to the normal action-selection loop. Probability is self-annealing: it starts near 1.0 when almost everything is unseen and decays toward 0.0 as coverage saturates, requiring no manual schedule. The mechanism is "innate" (hard-coded into the agent step loop) as distinct from the "adaptive" EFE path, which requires local neighbors and learned precision weights. Together they form a two-layer exploration architecture: adaptive for locally-guided foraging, innate for topological completeness.

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。

Saga patterns, compensating actions, and two-phase commit for distributed transactions. Activate on: distributed transaction, saga, compensating action, two-phase commit, eventual consistency, cross-service transaction. NOT for: single-database transactions (use database-connection-pool-manager), event sourcing (use cqrs-event-sourcing-architect).

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。

CQRS pattern, event stores, projections, eventual consistency. Activate on: CQRS, event sourcing, event store, read model, projection, aggregate, domain event, command handler. NOT for: message broker setup (use event-driven-architecture-expert), database optimization (use data-warehouse-optimizer).

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。

Epistemic logic for multi-agent perceptual systems — Kripke models, vision sets, public announcement as coordination primitive, and satisfiability-as-reconfiguration applied to agents with limited observability. From Charrier, Ouchet, Schwarzentruber's "Big Brother Logic" demonstration paper (ENS Rennes / IRISA).

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。

Track the full Toulmin epistemic ancestry of every claim produced by a multi-agent swarm. Each agent output is tagged with an argument chain (claim / data / warrant / relationship) derived from SwarmTracer spans and LineageEdge records, so operators can zoom into any sub-claim and see precisely which agents asserted it, what triggered each assertion, and how contradictions propagated or were synthesised away. The SwarmTracer pattern — wrapping the SwarmAgentExecutor to capture spans, record messages, and build a lineage graph — is the concrete runtime substrate. Argumentative lineage lifts that graph into the Toulmin vocabulary so reasoning provenance is both machine-queryable and human-interpretable.

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。

Expert in script-to-video production pipelines for Apple Silicon Macs. Specializes in hybrid local/cloud workflows, LoRA training for character consistency, motion graphics generation, and artist commissioning. Activate on 'AI video production', 'script to video', 'video generation pipeline', 'character consistency', 'LoRA training', 'cloud GPU', 'motion graphics', 'Wan I2V', 'InVideo alternative'. NOT for real-time video editing, video compositing (use DaVinci/Premiere), audio production, or 3D modeling (use Blender/Maya).

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 bounded applications and workflows for an always-on AI agent with episodic memory. Covers product ideas, persistence-dependent workflows, and constructed examples that make delegation, interruption, evidence, and opt-out explicit. Activate on: "what can an always-on agent do", "persistent agent use cases", "agent applications", "proactive agent ideas", "what to build with episodic memory", "always-on agent product", "personal AI assistant ideas", "/always-on-agent-applications". NOT for: building the architecture (use always-on-agent-architecture), designing inputs (use always-on-agent-inputs), safety and privacy (use always-on-agent-safety).

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。

Local SEO analysis covering Google Business Profile optimization, NAP consistency, citation health, review signals, local schema markup, location page quality, multi-location SEO, and industry-specific recommendations. Detects business type (brick-and-mortar, SAB, hybrid) and industry vertical. Use when user says "local SEO", "Google Business Profile", "GBP", "map pack", "local pack", "citations", "NAP consistency", "service area", or "multi-location".

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 Platform List: Arman's own register of large platform-level work he chose not to start yet. Use when the reminder hook says a row is due, when Arman says to add, snooze, kill, or finish a row, when you own a row, or when you think something belongs there. NOT for ordinary tasks, defects, or handoffs.

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。

Guide the user through starting a new web application project — elicit requirements (MoSCoW scoping), create architecture and requirements documents, break work into tasks, and register them as a GitHub Project kanban board. Use when the user says "新しいWebアプリを作りたい", "Webアプリの立ち上げを手伝って", "start a new web app project", "プロジェクトの要件を整理したい", or "GitHub Projectにタスクを登録したい".

This skill should be used when the user asks to "既存プロジェクトのタスクを整理して", "技術的負債をIssue化して", "このコードベースを改善するタスクを洗い出して", "GitHub Projectに健全化タスクを登録して", "break down what needs to be fixed in this project", "surface tech debt as issues", or "create a project board for cleanup work". Diagnoses pain points and codebase health of an existing project, then registers improvement tasks as GitHub Issues and a Project Board.

Thread-safe data persistence in Swift using actors — in-memory cache with file-backed storage, eliminating data races by design.

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 Agents Persistent SDK for .NET. Low-level SDK for creating and managing AI agents with threads, messages, runs, and tools.

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 Agents Persistent SDK for Java. Low-level SDK for creating and managing AI agents with threads, messages, runs, and tools.

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-assisted label triage for NVIDIA/NemoClaw issues and PRs. Reads triage-instructions.md at runtime for consistent label guidance. Supports single-item mode (give it a number) and batch mode (fetches up to 50 unlabeled open items). On approval, applies labels and an optional triage comment via gh CLI, then logs the session to the daily-rhythm activity folder. Trigger keywords - triage, label issues, suggest labels, batch triage, triage issue, triage PR, label this, what labels.

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。

Tracks complex, multi-session work using the Beads issue tracker and dependency graphs, and provides persistent memory that survives conversation compaction. Use when work spans multiple sessions, has complex dependencies, or needs persistent context across compaction cycles. Trigger with phrases like "create task for", "what's ready to work on", "show task", "track this work", "what's blocking", or "update status".

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。

World-Class Risk Management Playbook. Use for: business continuity planning (BCP), disaster recovery (DR), scenario planning, fraud prevention & detection, reputational risk management, geopolitical risk assessment, insurance & risk transfer, crisis communication, enterprise risk management (ERM), risk registers, BIA, RTO/RPO, ISO 22301, ISO 31000, COSO ERM, NIST CSF, DORA, operational resilience, three lines of defence, risk appetite, internal controls, segregation of duties, synthetic identity fraud, deepfake fraud, AML/CFT, KYC, sanctions screening, social listening, vendor risk, geopolitical exposure mapping, parametric insurance, cyber insurance, D&O, KRIs, risk dashboards. Trigger when discussing ANY risk management, business continuity, disaster recovery, fraud prevention, reputational risk, geopolitical risk, insurance strategy, crisis management, operational resilience, or enterprise risk topic. If in doubt, use this 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。

Audit code for memory leaks and disposable issues. Use when reviewing event listeners, DOM handlers, lifecycle callbacks, or fixing leak reports. Covers addDisposableListener, Event.once, MutableDisposable, DisposableStore, and onWillDispose 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。

Persistent AI companion with long-term memory, project context awareness, and multi-session continuity across any LLM.

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。

Systematically remove malware, backdoors, and attacker persistence mechanisms from infected systems while ensuring complete eradication and preventing re-infection.

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。