「structured」の検索結果

Audit technical SEO across crawlability, indexability, security, URLs, mobile, Core Web Vitals, rendering, structured data, and IndexNow. Exclude content strategy and backlinks.

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。

Detect, validate, or generate Schema.org JSON-LD for a supplied page or entity. Use only when structured data or rich-result markup is requested.

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。

OpenTelemetry-backed tracing, structured logs, metrics with rollups, alerts, sampling, and baggage for the engine — emit and query telemetry through `engine::*` functions and react to logs with a `log` trigger.

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。

Explain how a public GitHub repository is built using GitDiagram's architecture diagram. Use when the user asks how a GitHub repository or open-source project is structured or organized, wants an architecture or system diagram of a repo, or is starting work in an unfamiliar codebase hosted on GitHub.

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。

Show the architecture of a public GitHub repository with GitDiagram (gitdiagram.com) - a written explanation, its main components and source paths, how they connect, and a Mermaid diagram. Use when the user wants to understand, map, visualize or get an overview of a GitHub repository or open-source project's architecture, structure or data flow, or asks for an architecture diagram of a repo, e.g. "/gitdiagram fastapi/fastapi" or "how is vercel/next.js structured?".

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。

This skill should be used when long-running agent sessions need context compression, structured summarization, compaction, token-per-task optimization, or durable handoff summaries that preserve decisions, files, risks, and next actions.

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。

This skill should be used for project-level decisions about LLM-powered systems: whether an LLM is the right primitive for the task at hand, the shape of a multi-stage batch or agent pipeline, token and cost estimation, choosing between single-agent and multi-agent at the project level, structured output design for downstream parsing, and structuring agent-assisted iteration. Use this when the unit of work is a whole project or a multi-stage pipeline. Route individual tool design to tool-design and individual skill-loading or context-budget tactics to context-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。

Generate a structured paper outline from review conclusions and experiment results. Use when user says \"写大纲\", \"paper outline\", \"plan the paper\", \"论文规划\", or wants to create a paper plan before writing.

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。

Draft a structured grant proposal from research ideas and literature. Supports KAKENHI (Japan), NSF (US), NSFC (China, including 面上/青年/优青/杰青/海外优青/重点), ERC (EU), DFG (Germany), SNSF (Switzerland), ARC (Australia), NWO (Netherlands), and generic formats. Use when user says "write grant", "grant proposal", "申請書", "write KAKENHI", "科研費", "基金申请", "写基金", "NSF proposal", or wants to turn research ideas into a funding application.

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 deterministic publication-quality architecture, workflow, and pipeline diagrams from structured JSON (FigureSpec) into editable SVG. Use when user says "架构图", "workflow 图", "pipeline 图", "确定性矢量图", "figure spec", "draw architecture", or needs precise, editable, publication-ready vector diagrams. Preferred over AI illustration for formal architecture/workflow figures.

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 a structured paper outline from review conclusions and experiment results. Use when user says "写大纲", "paper outline", "plan the paper", "论文规划", or wants to create a paper plan before writing.

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。

Automate Capsule CRM operations -- manage contacts (parties), run structured filter queries, track tasks and projects, log entries, and handle organizations -- using natural language through the Composio MCP 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。

Query and filter Datadog logs from the shell using the Composio CLI. Run scoped log searches, pivot across services/environments, and export structured JSON for downstream agents instead of click-driving the Datadog 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。

Generate PPTX presentations, DOCX documents, XLSX spreadsheets, and PDF reports from structured JSON input using PaperJSX.

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 conversations and decisions into structured Notion pages; use when turning chats/notes into wiki entries, how-tos, decisions, or FAQs with proper linking.

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。

Research across Notion and synthesize into structured documentation; use when gathering info from multiple Notion sources to produce briefs, comparisons, or reports with citations.

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。

Author Quarkdown (.qd) documents, a Markdown-superset typesetting language that compiles to HTML, PDF, or plaintext. Use when the user wants to write or edit .qd files, produce typeset output (articles, reports, slides, books, wikis, notes, static sites) beyond what plain Markdown offers, or share structured plans in a presentation-ready format. Quarkdown adds function calls (`.func {arg}`), variables, layouts, math, diagrams, and document types (plain/paged/slides/docs).

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。

Investigate an OpenShell problem and create a structured issue with technical findings for human disposition.

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。

Coordinate several coding agents in parallel through Superset, each in its own workspace, with follow-ups, progress reads, dependency tracking, and structured results. Use when the user asks to delegate, parallelize, fan out, or split up coding work across agents, workspaces, or hosts, hand work between agents, or monitor workers, including "spin up agents for each of these", "run these in parallel", "what are my workers doing". Not for ordinary single-agent workspace, task, or automation management.

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。

Compiles any research input — PDF papers, GitHub repositories, experiment logs, code directories, or raw notes — into a complete Agent-Native Research Artifact (ARA) with cognitive layer (claims, concepts, heuristics), physical layer (configs, code stubs), exploration graph, and grounded evidence. Use when ingesting a paper or codebase into a structured, machine-executable knowledge package, building an ARA from scratch, or converting research outputs into a falsifiable, agent-traversable form.

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 researchers through structured ideation frameworks to discover high-impact research directions. Use when exploring new problem spaces, pivoting between projects, or seeking novel angles on existing work.

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 guidance for GRPO/RL fine-tuning with TRL for reasoning and task-specific model 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。

Use when challenging ideas, plans, decisions, or proposals using structured critical reasoning. Invoke to play devil's advocate, run a pre-mortem, red team, or audit evidence and assumptions.

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 writing Spark jobs, debugging performance issues, or configuring cluster settings for Apache Spark applications, distributed data processing pipelines, or big data workloads. Invoke to write DataFrame transformations, optimize Spark SQL queries, implement RDD pipelines, tune shuffle operations, configure executor memory, process .parquet files, handle data partitioning, or build structured streaming analytics.

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。