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概要と使いどころ
Deprecated alias. This skill was renamed to `deepline-scoring`. Use when a user or script still invokes `/niche-signal-discovery`: immediately load and follow the `deepline-scoring` skill instead. Triggers: ICP analysis, niche signals, won vs lost analysis, differential signals, signal discovery, ICP signal report, account scoring signals, lead scoring, first-party signals, buyer signals.
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 for Deepline GTM work that searches, enriches, scores, collects signals, or automates a workflow: find companies or people, enrich a CSV, find emails or LinkedIn, compare providers, build a waterfall, create a webhook or cron, or write a Play. For live information work, run a small heterogeneous experiment, exploit the observed winner, and reopen misses. Skip pure copywriting and non-GTM research.
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。
Convert a Clay table configuration into local Deepline scripts. Handles extraction (MCP or script), documentation, action mapping, script generation, and parity validation against Clay ground truth.
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 validating deep references
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。
Multi-source deep research using firecrawl and exa MCPs. Searches the web, synthesizes findings, and delivers cited reports with source attribution. Use when the user wants thorough research on any topic with evidence and 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。
High-precision semantic search and content retrieval via Exa API. Use when: (1) Deep research requiring semantic understanding, (2) Code documentation and examples lookup, (3) Company/professional research, (4) AI-powered comprehensive research tasks, (5) URL content extraction with structured output. Triggers: "research", "find papers", "code examples", "company info", "LinkedIn profiles", "deep analysis". Differentiator: Exa excels at semantic/neural search while grok-search is better for real-time news and general web content.
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。
End-to-end research workflow skill for investment analysts and policy researchers. Three scope modes the user picks at trigger time — light (4-5 page decision memo, ~15 min, 0 charts), medium (12-15 page topic brief, ~1 h, 6-10 charts), heavy (flagship report 30-40 pages / 15k+ words, ~2-3 h, 25-35+ charts, multi-stage workflow, multi-LLM, PDF + Word + WeChat + HTML derivations). Reports default to English; the AI replies in the user's chat language. Battle-tested on real macro/policy/equity reports (e.g. Saudi Vision 2030 deep-dive). Triggers when user types /analyst-research, /flagship-research, or describes needs like "research report", "topic analysis", "investment research", "做研报", "投研报告", "主题分析", "深度分析", "policy assessment", "industry deep-dive". Not for: pure news commentary (use topic-brief), slide decks (use deckster-slide-generator), one-shot Q&A.
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。
Advanced multi-agent reasoning system for complex questions requiring maximum accuracy. Uses adaptive technique selection, adversarial validation, multi-agent debate, and deep analysis. Trigger phrases "ai board", "expert panel", "deep analysis", "maximum accuracy", "thorough reasoning". Use for critical medical decisions, theological questions, philosophical analysis, complex technical problems, high-stakes decisions, or any question requiring 95%+ confidence.
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。
Score deep research agents on benchmark tasks using factual verification, report-quality scoring, and process evaluation before model or workflow changes ship.
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 DeepAgents to build long-running task agents with a batteries-included harness for planning, tools, and workflow 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。
深挖一组 subreddit 的"社区研究"技能。给一个品牌或项目,先摸清相关(自家品牌+竞品)的 subreddit:爬规则原文、爬高赞帖逐帖学、找共性、产出"能不能提品牌/能不能发链接/要不要披露"的逐社区政策矩阵。用于任何新品牌/新项目上 Reddit 前的社区尽调。触发词:"研究 subreddit""摸清社区规则""Reddit 社区尽调""subreddit deep research""某品牌相关的 sub"。
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 a topic to support a decision, three ways: draft a research prompt for the user to run in their own tool (ChatGPT, Gemini, Grok, Perplexity, …), turn a finished research report into a short summary with cited sources that other skills can use directly, or run the research here with parallel web searches. Built-in research types: market, domain, technical, competitive, user-voice, academic-lit; also supports choosing between candidates, and custom types via overrides. Use when the user says "deep recon", "research this", "draft a research prompt", "process this research report", "market research", "domain research", "technical research", "competitor research", "literature review", or "help me choose between"
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。
Push the LLM to reconsider, refine, and improve its recent output. Use when user asks for deeper critique or mentions a known deeper critique method, e.g. socratic, first principles, pre-mortem, red team
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。
Navigation in React Native — both React Navigation v7 (classical, modular) and Expo Router (file-based, Expo 49+). Stack, tab, drawer navigators, deep linking, typed navigation, modal presentation, authentication flow patterns. Use this skill to: - Pick navigation lib based on what's installed (@react-navigation/* vs expo-router). - Configure typed routes with ParamList types or Expo Router's generated types. - Set up deep linking (URL schemes, Universal Links, App Links). - Build authentication flow with conditional navigators. - Use modal presentation correctly. Do NOT use this skill for: - Project structure (see rn-conventions). - Platform-specific differences (see rn-platform-specific). - State / storage (see rn-state-and-storage). - Testing navigation (see rn-testing).
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 format-controlled research reports with evidence tracking, citations, and iterative review. This skill should be used when users request a research report, literature review, market or industry analysis, competitive landscape, policy or technical brief, or require a strict report template and section formatting that a single deepresearch pass cannot reliably enforce.
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。
Fix and verify iOS Universal Links, TestFlight deeplinks, AASA files, Expo Router callback URLs, associated domains, and sign-in returnTo flows in NowStack Mobile apps.
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 characterising a malware sample, the user asks "what does this binary do?" / "analyse this hash deeply", or `/hash-investigation` flags a novel sample warranting deeper review. Static + dynamic methodology, behavioural indicators, sandbox interpretation.
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 root cause analysis using the 5 Whys and Fishbone techniques. Use when systematic debugging hasn't found the cause, or for complex systemic issues. Keywords: root cause, why, underlying, fundamental, systemic, deep, origin
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。
Wire dependency-cruiser into a TypeScript repo so each package is a deep module, with implementation hidden in subfolders and reachable only through its entry-point files. User-invoked.
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。
Initialize or migrate to nested CLAUDE.md structure for progressive disclosure. Claude auto-loads CLAUDE.md from any directory it enters, so nested files get discovered automatically. Use when setting up a new project's agent config, refactoring a bloated CLAUDE.md, or adding progressive disclosure to an existing repo. Triggers on: '/agent-init-deep', 'setup progressive disclosure', 'refactor claude.md', 'split claude.md', 'claude.md is too big'.
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 review — random exploration + cross-agent review, alternating. Finds integration bugs that self-review misses. Run every 30–60 min during active implementation.
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 code review after beads have landed — random exploration + cross-agent review, alternating. Use every 30–60 min during active implementation, or after any epic lands.
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 provides guidance for using DeepWiki MCP to explore GitHub repository documentation. Use when researching repository structure, understanding library APIs, asking questions about open-source projects, or exploring documentation for any GitHub repository.
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 enables GitHub repository documentation exploration using DeepWiki API directly via curl. Use when researching repository structure, understanding library APIs, or asking questions about open-source projects. MCP server not 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。