「deep sea」の検索結果

Deep analysis of Amazon niche markets by keyword, covering monopoly level, brand concentration, new product success rate, and market opportunity score. Trigger when the user mentions niche market analysis, keyword market research, monopoly assessment, brand concentration analysis, new product success rate, market demand score, competitive landscape, Amazon sub-market exploration, niche market analysis, keyword market, monopoly level, brand concentration, new product success rate, market opportunity score, competitive landscape, Nexscope data. Even if the user does not explicitly mention "niche market", if their need involves evaluating the competitive landscape, brand density, or opportunity potential of the Amazon market at the keyword dimension level, this skill should also be triggered.

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Deep analysis of Amazon niche markets by product ASIN, covering monopoly level, brand concentration, new product success rate, and market opportunity score. Trigger when the user mentions niche market analysis by ASIN, ASIN market research, ASIN niche lookup, monopoly assessment, brand concentration analysis, new product success rate, market demand score, competitive landscape, Amazon sub-market exploration, ASIN niche analysis, niche by ASIN, monopoly level, brand concentration, new product success rate, market opportunity score, competitive landscape, Nexscope data. Even if the user does not explicitly mention "niche market" or "ASIN", if their need involves evaluating the competitive landscape, brand density, or opportunity potential of the niche segment a specific product ASIN belongs to, this skill should also be triggered.

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。

Internal guidance for composing prompts that Pi runs (DeepSeek by default) handle reliably for coding, review, diagnosis, and research tasks

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。

GitHub OSS向け README.md の作成・改善・レビューを支援する。What/Why/How to start/Help/Maintainers の軸で情報を整理し、最短で動かせる Quickstart と docs への導線を構成する。 READMEの新規作成、既存READMEの再構成、READMEレビュー、ドキュメント分割の判断時に使用する。 トリガー：「READMEを作って」「READMEを改善して」「Quickstartを追加して」 「GitHub向けREADMEテンプレ」「READMEをレビューして」などのREADME関連リクエスト。

Reads and analyzes academic papers (arXiv preprints, conference / journal PDFs, Zotero items) at three configurable depths: quick skim (2 min), standard read (10 min), or deep analysis (30 min). Produces structured digests covering problem, method, key innovation, results, limitations, reproducibility, hidden assumptions, and connections to the user's other work. Use when the user shares an arXiv link, PDF, or paper title and asks to read / summarize / digest / TL;DR / analyze / review / critique / explain / break down a paper, asks about a paper's contributions / methods / results / equations / figures, wants to compare two papers side by side, or needs a reading note for their records.

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 AI analyst for buying B2B software. Investigates what vendors claim, checks the evidence, surfaces contradictions and unanswered questions, and produces a shareable Decision Brief with the questions to ask before you buy. Quick Eval by default; Deep Eval on request. Use when asked to evaluate, compare, vet, or research B2B software vendors.

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DRAFT. Build anonymizable host-prep one-pagers for must-meet guests at an in-person event: rank, enrich, light research, warm-intro angles, PDF pack. Not installed by deepline skills. No real customer data in repo samples.

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 create competitor comparison or alternative pages for SEO and sales enablement. Also use when the user mentions 'alternative page,' 'vs page,' 'competitor comparison,' 'comparison page,' '[Product] vs [Product],' '[Product] alternative,' or 'competitive landing pages.' Covers four formats: singular alternative, plural alternatives, you vs competitor, and competitor vs competitor. Emphasizes deep research, modular content architecture, and varied section types beyond feature tables.

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Value investing analysis using Graham (NCAV/net-net/defensive-investor) and Buffett (economic moat/ROE/FCF) methodologies. Covers single-stock diagnostics and batch screening for both Graham cigar-butt and Buffett quality-compounder criteria. Runs cross-statement reconciliation before scoring. Data from Longbridge CLI first, MCP fallback, WebSearch only for genuine gaps. Triggers: "格雷厄姆", "巴菲特", "捡烟蒂", "烟蒂股", "NCAV", "净流动资产", "护城河", "价值投资", "安全边际", "深度价值", "撿煙蒂", "煙蒂股", "淨流動資產", "護城河", "安全邊際", "Graham", "Buffett", "cigar butt", "net-net", "NCAV screen", "moat", "value investing", "margin of safety", "deep value", "quality compounder", "價值投資", "深度價值", "防御型投资者", "防禦型投資者"

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When the user wants to deeply understand their ideal customer before writing copy — pains, desires, inner monologue, and language. Also use when the user mentions "empathy engine", "know your target", "customer pain points", or asks to research their audience before writing Blitz Copy.

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Research an issue deeply and present all context to the user. but the user writes the code. The LLM investigates code paths, finds relevant files, explains patterns, and identifies constraints. The user thinks through the approach and implements it. Use when ready to start working on an issue after oss-prep-to-contribute. Not for writing tests or documentation as a standalone contribution. Use oss-write-tests or oss-write-docs for those.

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当用户要写出高质量 Goal Prompt，把模糊、战略性、多步骤、证据不足、持续/自动化或容易跑偏的请求整理成可执行、可验证、可暂停的目标契约时使用。适用于写 goal、优化任务提示词、明确 done/success criteria、deep research 后定战略、大改前 inventory、修复跑偏计划、识别可委托的重复 workflow、为 Codex 或 Claude Code 准备执行任务；默认一次性交付只生成 Goal Prompt，只有存在真实后续迭代需求时才追加 Loop Prompt，不执行 goal 或 loop，也不创建自动化。

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。

Sync high-value dev knowledge (skills, decisions, lessons) into Google NotebookLM for cloud recall, podcasts, and flashcards. Pairs with Dockit/deep-search. Use for NotebookLM, nlm, knowledge base, skill sync, or cross-machine AI memory.

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Conversational design ideation agent that researches trends, explores visual directions, and refines ideas through adaptive questioning — then produces a rich PRD document and auto-generates Stitch screens. Your design buddy that thinks deeply before designing.

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Query the project knowledge base. Wraps the research-librarian agent. The librarian reads the shelf-index, identifies the 2-4 most relevant library files for the question, deep-reads only those, and returns structured evidence with citations. Stateless — reads the index fresh on every query.

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Scrape web pages to clean markdown using Firecrawl v2 — handles JS-heavy pages, site crawls, URL mapping, document parsing (PDF/DOCX/XLSX), LLM-powered extraction, autonomous agent scraping, and post-scrape browser interaction (Interact API). Free keyless mode available for search/scrape/parse/interact (no API key needed). Prefer over WebFetch for quality and completeness. Triggers on scrape URL, fetch page, crawl site, extract content, parse document, web to markdown, DeepWiki, Firecrawl.

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。

Deep cross-domain synthesis engine for the vault. Triggers on "synthesize X", "what do I know about X", "connect ideas about X", "cross-domain analysis of X", "map everything in the vault about X". Searches comprehensively, surfaces non-obvious patterns and tensions, then challenges the user to generate original thought. The vault should surprise you — if synthesis only confirms what you already think, it failed.

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Operator-side inventory of experiment PRs for auditing a Senpai research track. It outputs merged winners, a compact results table, and full details for deep dives.

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

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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。

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。

Deep API security assessment beyond surface scanning. Covers the full OWASP API Security Top 10 (2023): Broken Object Level Authorization (BOLA / IDOR), Broken Authentication, Broken Object Property Level Authorization (mass assignment + excessive data exposure), Unrestricted Resource Consumption, Broken Function Level Authorization (BFLA / vertical privilege escalation), Unrestricted Access to Sensitive Business Flows, Server-Side Request Forgery via API parameters, Security Misconfiguration, Improper Inventory Management (shadow/zombie/deprecated endpoints, v1/v2 drift), and Unsafe Consumption of third-party APIs. Works across REST, GraphQL, gRPC, SOAP, and MCP servers. Discovers APIs from OpenAPI/Swagger specs, GraphQL introspection, gRPC reflection, .well-known endpoints, JS bundles, and traffic capture. Uses kiterunner, ffuf, schemathesis, restler-fuzzer, openapi-fuzzer, graphql-cop, clairvoyance, batchql, inql, jwt_tool, postman, mitmproxy, and manual http(action="request", ...) payloads. Every technique includes actual payloads, commands, and verification logic. Chains from /pentester or /codebase when API endpoints are discovered, chains into /web-exploit when classic injection points are found in API parameters, chains into /post-exploit when RCE is achieved, and chains into /ai-redteam when an LLM/AI endpoint is discovered (chat APIs, completion endpoints, RAG search, agentic tool-use, MCP servers).

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。

Curate, review, or repair ai-gene-review ModuleReview YAML documents under modules/, including pathway/module boundary setting, parts and variant modeling, annoton-level molecular functions, representative UniProt/PTN grounding, module deep-research provenance, validation, rendering, and project batch updates.

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。