「deep」の検索結果

Research companies, competitors, funding, news, leadership, and market context with Exa Agent and advanced search. Use when researching companies, competitor analysis, market research, or building company lists. Writes findings the caller can fold into brand/competitors.md or brand/landscape.md. Prefer this over ad-hoc web search for company deep dives. Distinct from competitive-intel (full brand competitive file methodology) - this skill is the Exa research engine those foundation skills should call.

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Deep Single-Candidate Scoring — evaluate one candidate across 5 dimensions (skills match, experience relevance, culture fit signals, growth potential, red flags) with final 0-100 score and hire/no-hire signal

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。

Learn how to install and migrate to Jetpack Navigation 3, and how to implement features and patterns such as deep links, multiple backstacks, scenes (dialogs, bottom sheets, list-detail, two-pane, supporting pane), conditional navigation (such as logged-in navigation vs anonymous), returning results from flows, integration with Hilt, ViewModel, Kotlin, and view interoperability.

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用前端渲染生成图片 —— 不依赖模型的多模态能力，任何能写 HTML/CSS 的模型 (DeepSeek / Claude / Kimi / GPT 等) 都能用。 当用户要「生成/做/画一张图」且属于以下任意一种时使用：头像、图标、公众号封面、 OG 分享图、Banner/横幅、小红书封面、知识卡片、金句卡、代码片段图、数据卡、 功能发布图、对比图、步骤图、视频封面/缩略图、幻灯片单页、活动海报、名片、 二维码卡、配图、题图、缩略图、poster、cover、thumbnail、banner、avatar。 也用于：批量出多个尺寸/多平台的同一张图；把一段文字/数据/代码变成图； 给文章配图；做一套风格统一的系列图。 支持指定视觉风格，共 32 套：手绘/涂鸦/白板、黑板、水彩、拼贴/剪贴、博物图鉴、 瑞士国际主义、杂志编辑部、报纸、工程蓝图、档案手稿/打字机、包豪斯、装饰艺术 Art Deco、 双色印刷 Riso、粗野主义、孟菲斯、美漫波普、像素 8-bit、千禧 Y2K、蒸汽波、霓虹赛博朋克、 街头海报/喷漆、日式侘寂、中式水墨、国潮/新中式、终端 CLI、极光渐变、玻璃拟态、 奢侈品黑金、极简产品、电影海报、复古未来 70s、极简线条。 用户没指定时主动报 3~4 个候选让他选；说了库里没有的风格就按四步法拆成 token。 产出一个可预览的画板工作台页面，多种画幅并排展示，点按钮即可导出 PNG (页内零依赖导出 + 本机 Chrome 精确出图两条通道)。 不适用：需要照片级真实内容的图（人像、风景、材质渲染）—— 那需要真正的图像模型。

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。

Makers 开发专家团 AI Agent 工程师 Skill — Claude Agent SDK、 OpenAI Agents SDK、LangGraph、DeepAgents、CrewAI 框架集成， SSE 流式响应、conversation store、EdgeOne Makers Agent Runtime。 触发词：AI Agent、聊天机器人、LLM 应用、多 Agent 系统、 Claude SDK、OpenAI Agents、LangGraph、CrewAI、SSE 流式、 智能助手、AI 推理端点。

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 a project-local paper dossier should produce graph delta JSON proposals and run through the human-gated delta loop.

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 an agent to create or update a project-local source/paper note from a PDF, URL, arXiv, DOI, manual source, or Zotero item.

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。

Gathers information from multiple sources in parallel, compares what they say, flags where they agree or conflict, and delivers a clean synthesis with a confidence rating for each finding. Useful for making evidence-backed decisions, when evaluating competing claims, during due diligence on a vendor or market, and for building research briefs before strategy sessions. Use when the user says "research this", "synthesize multiple sources", "compare sources", "research report", "what does the evidence say", "gather information on", or "deep dive into".

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 you need deep host + certificate reconnaissance for an IP or need to run a Censys search query. Returns services, TLS certificates, ASN, and location. Free tier is severely limited (250 queries/month) — use sparingly. Retrieval only.

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 you need authoritative classification, threat-name, MITRE ATT&CK mapping, dynamic-analysis or sandbox results on a file hash, or when you need network threat intelligence for a URL/domain/IP from ReversingLabs Spectra Analyze (A1000). Returns verdict, risk score, AV detection ratio, threat name, behavioural tags, and pivot candidates (parent containers, extracted files, related samples by family). Commonly invoked by /hash-investigation and /malware-analysis. Other agents/skills can chain this for deeper malware enrichment beyond VirusTotal.

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 a user asks to check, identify, or characterize a file hash (MD5, SHA-1, SHA-256). Chains VirusTotal and OTX, optionally triggers /malware-analysis for deeper behavioral review. Returns detection signals, malware family, behavioral tags, and pivot candidates (communicating IPs, dropped files). Invoked by /cti-orchestrator when the target is a hash.

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。

Web application testing principles. E2E, Playwright, deep audit strategies.

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。

Deploy applications to Render by analyzing codebases, generating render.yaml Blueprints, and providing Dashboard deeplinks. Use when the user wants to deploy, host, publish, or set up their application on Render's cloud platform.

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。

Find deepening opportunities in a codebase, informed by the domain language in CONTEXT.md and the decisions in docs/adr/. Use when the user wants to improve architecture, find refactoring opportunities, consolidate tightly-coupled modules, or make a codebase more testable and AI-navigable.

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 specialized AI agents with optimized system prompts using the official 4-phase SOP methodology from Desktop .claude-flow, combined with evidence-based prompting techniques and Claude Agent SDK implementation. Use this skill when creating production-ready agents for specific domains, workflows, or tasks requiring consistent high-quality performance with deeply embedded domain knowledge.

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 installing Anthropic's Claude Science on a geo-blocked machine (e.g. China) or running it without a Claude account. Downloads the binary from the unblocked downloads.claude.ai CDN, sets up the claude-science-api-bridge local proxy to route requests to ANY OpenAI- or Anthropic-compatible API (Volcengine, DeepSeek, Kimi, Zhipu, OpenAI, local Ollama/vLLM), and applies a no-login patch so no Claude Pro/Max subscription is 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。

MATLAB R2026a workflow for signal processing, DSP, image processing, computer vision, lidar, medical imaging, deep learning, and AI-assisted reproducible experiments. Use for filters, spectrograms, wavelets, object detection, segmentation, classification, training, inference, and generated 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。

Review a pull request or contribution deeply, explain it tutorial-style for a maintainer, and produce a polished report artifact such as HTML or Markdown. Use when asked to analyze a PR, explain a contributor's design decisions, compare it with similar systems, or prepare a merge recommendation.

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。

Idiomatic Go - package and interface design, error wrapping, table-driven tests, generics, the modern standard library (slices/maps/cmp/errors.Join), current syntax, and logging discipline. Use when writing, reviewing, or refactoring any Go code, especially code drifting toward Java/Spring shapes (deep layer trees, generic repositories, heavy frameworks) - even if the user never says "idiomatic". Distilled from spf13/go-skills and adapted to this repo.

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。

Search, screen, deeply read, synthesize, and publish recent research papers for a user-specified topic, window, count, quality/attention balance, and language. Use for evidence-anchored literature digests, cross-paper comparisons, original-language excerpts, Chinese explanations, guided Feishu setup, or Feishu research reports.

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 planning a source-grounded method overview, architecture, pipeline, system/data-flow, mechanism, or agent-workflow figure for a CS or deep-learning paper. Produces an editable figure brief before image generation or manual redrawing; not for plots, tables, or general prose.

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 exploring, continuing, or accepting a deep-learning or computer-science research idea. Converts claims into pilot-first experiment matrices covering diagnostics, failure analysis, authorized execution, evaluation, and paper-story viability.

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 a lightweight pre-release readiness review of Atlassian Forge apps across manifest/module wiring, architecture, runtime compatibility, dependency posture, tests, deploy readiness, and obvious security, cost, or reliability smells. Use when the user asks "review my Forge app", "pre-deploy check", "is this app ready to ship", "review manifest", "general app review", "release readiness", or asks for a broad quality pass. Do not use for deep security audits/SAST/exploitability review, cost optimization, or diagnosing a known broken app; route those to forge-security-review, forge-cost-optimizer, or forge-debugger respectively.

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。

Choose responsibility for substantial work before deep execution: keep one responsibility's coupled parts in a single lane, and hand a bounded or independent lane to a worker when clean context, an unknown cause, independent review, or coordinator attention materially improves the outcome.

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。