「deep」の検索結果

Add field definitions to existing research outline.

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。

Add items (research objects) to existing research outline.

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。

When the user wants to monitor competitor apps on an ongoing basis — tracking metadata changes, keyword shifts, screenshot updates, rating trends, or new features. Use when the user mentions "competitor monitoring", "track competitors", "competitor alert", "competitor changed their title", "watch a competitor app", "competitor weekly report", "competitive intelligence", or "what changed in competitor's listing". For a one-time deep competitive analysis, see competitor-analysis. For market-wide chart movements, see market-movers.

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 external compatibility between two DSH (DeepSeek Harness) versions and detect reverts, producing an upgrade-report directory; compares git tags with a source checkout, or published npm packages without one. Use whenever the user asks to check/compare/audit two DSH versions or whether upgrading is safe — e.g. "more changes or reverts in dsh-vX -> dsh-vY", "compare the breaking changes" — even with only two version numbers and no source location. Read-only outside the report directory; npm mode installs in isolation with --ignore-scripts.

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。

开发、维护、分发和验证 DeepSeek Harness (DSH) 插件的执行型 Skill。覆盖 host/client 形态判断、bundle/profile 契约、Service 与函数插件、工具、HTTP、持久化、slot、Conversation Node、客户端构建、HMR、GitHub 安装和真实组合验证。

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 multiple DeepSeek Harness plugin Skills across inspection, migration, runtime debugging, heavy dependencies, testing, naming, and release. Use for a guided lifecycle workflow, a pre-run capability menu, or several DSH plugin operations with one status report. Preserve the user's selected scope and existing authorization across stages.

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。

Package, publish, and distribute DeepSeek Harness (DSH) plugins — npm pack artifact validation, GitHub/npm/hub release-track selection, tarball overrides installs for the unpublished cohort (0.1.2-alpha.*), and CI/release gates with rollback. Use when publishing a plugin, packing a tarball, wiring a plugin into a profile/hub, or installing an alpha version that is not on npm; show a plan and obtain user confirmation before any publish action.

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 users through creating, updating, debugging, and validating Agent Skills for AI agents. Use when the user wants to create, write, author, design, troubleshoot, validate, or improve a Skill, or needs help with SKILL.md, frontmatter, or skill structure.

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 or edit images from text and local files, image URLs, or data URLs through image API. Use when the user asks to create an image, generate from one or more reference images, combine styles or elements across references, or edit a marked region while blending the result into the original scene.

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 complete, beginner-friendly explanation of an entire code repository as a set of markdown files. Maps the repo structure with `treecap` (installing it if missing), studies the actual source, then writes a `CODE_EXPLANATION/` folder containing an `OVERVIEW.md` plus numbered deep-dive files (01_architecture.md, 02_models.md, ...) that explain how the code is built, what it does, and how the pieces fit together — illustrated with real code excerpts. Use this skill whenever the user wants to understand, document, onboard onto, or get a walkthrough of a codebase: phrases like "explain this repo", "explain the code", "code explanation", "walk me through this codebase", "help me understand how this is built", "document the architecture", or "what does this project do" — even if they don't say the word "skill". Prefer this over ad-hoc summaries whenever the goal is a durable, written explanation of a whole 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。

Run inference on Fireworks AI — direct, through the Leanmcp AI Gateway proxy (aigateway.leanmcp.com) for observability, or via LiteLLM / the OpenAI SDK / raw HTTP. Covers the endpoint-and-key matrix for each route, serverless vs dedicated deployments and their cold starts, browsing and filtering the model catalogue, reasoning models that return content:null with the answer in reasoning_content, function calling, concurrency and load testing, and runner scripts where many models share one protocol with a --use-proxy toggle. Use this skill whenever the user mentions Fireworks, FIREWORKS_API_KEY, api.fireworks.ai, fireworks_ai/ model ids, accounts/fireworks/models/..., a Fireworks deployment id, the Leanmcp gateway or LEANMCP_API_KEY, app.leanmcp.com observability, or gpt-oss / kimi / glm / qwen / deepseek served on Fireworks; wants to route LLM calls through a proxy for logging or cost tracking; is debugging empty responses, 404s, scope errors, cold starts, or "the gateway isn't working"; wants to pick a Fireworks model with tool calling; or wants to sweep several models over one benchmark. Reach for it even on vague asks like "why is this model returning nothing" or "set up inference for these models" when Fireworks is in play.

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。

Comprehensive security and correctness audit of a branch's changes. Use for thermo nuclear, thermonuclear, or deep review requests, or branch/PR diff audits focused on bugs, breaking changes, security issues, devex regressions, and feature-gate leaks.

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 an extremely strict maintainability review for abstraction quality, giant files, and spaghetti-condition growth. Use for a thermo-nuclear code quality review, thermonuclear review, deep code quality audit, or especially harsh maintainability review.

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。

Control deep thinking mode. Default enabled. For very simple tasks (simple reminders, greetings, quick queries), can temporarily disable to speed up response. Auto-restores to enabled after completion.

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。

NGS analysis toolkit. Used for BAM to bigWig conversion, quality control (correlation, PCA, fingerprint plots), heatmaps/feature plots (TSS, peaks), suitable for ChIP-seq, RNA-seq, ATAC-seq visualization.

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。

Quickly judges whether a biomedical paper is worth deep reading by screening for question fit, design quality, sample adequacy, methodological novelty, and reproducibility value.

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 evaluating investments through Zhang Lei / Hillhouse Capital's long-term research-driven value lens: deep research, do time's friend, invest in great companies, and actively help them grow.

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 evaluating stocks through Deng Xiaofeng's cycle-and-industry lens: deep industry research, cycle position awareness, supply-demand dynamics, and buying leaders at cycle bottoms.

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 evaluating Benjamin Graham-style deep value: net-nets, working capital bargains, margin of safety, statistical cheapness, and balance-sheet protection.

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 evaluating Li Lu-style value investments: circle of competence, long-term compounding, deep research, conservative downside, China/global quality businesses, and concentrated ownership.

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 evaluating Michael Burry-style contrarian, asymmetric, unpopular trades: deep mispricing, short theses, complex assets, forced consensus errors, and catalyst-driven downside/upside.

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 build academic-style .docx output: journal / conference / thesis chapters carrying formal citation style (APA, Chicago, IEEE, MLA), numbered equations, figure & table cross-references, footnotes/endnotes, bibliography, or multi-column journal layout. Trigger on: 'research paper', 'journal paper', 'conference paper', 'manuscript', 'thesis', 'APA', 'MLA', 'Chicago', 'IEEE two-column', 'bibliography', 'hanging indent', 'citation style', 'abstract + keywords', 'equation numbering', 'cross-reference', paper with footnotes/endnotes. Output is a single .docx.

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。

Findings-first code review workflow for AI coding agents. Use when the user asks to review uncommitted changes, commits in a date range, or a branch compared to the main branch / PR-style diff. Focuses on bugs, regressions, correctness risks, missing tests, security/data-safety issues, and other behavior-changing defects.

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 the user is building a fundraising / investor pitch deck — seed, Series A / B / C, convertible note, SAFE round, strategic raise. Trigger on: 'pitch deck', 'investor deck', 'Series A deck', 'Series B deck', 'Series C deck', 'fundraising deck', 'seed pitch', 'VC deck', 'raising capital', 'term sheet presentation'. Output is a single .pptx. This skill is a scene layer on top of officecli-pptx — inherits every pptx v2 rule (visual floor, grid, palettes, connector canon, Delivery Gate). DO NOT invoke for a generic board review, sales deck, all-hands, or product launch — route those to officecli-pptx base.

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。