Guides architectural decisions for Deep Agents applications. Use when deciding between Deep Agents vs alternatives, choosing backend strategies, designing subagent systems, or selecting middleware approaches.
한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.
2.5천건 · 관련도순
Guides architectural decisions for Deep Agents applications. Use when deciding between Deep Agents vs alternatives, choosing backend strategies, designing subagent systems, or selecting middleware approaches.
한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.
Implements agents using Deep Agents. Use when building agents with create_deep_agent, configuring backends, defining subagents, adding middleware, or setting up human-in-the-loop workflows.
한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.
Reviews Deep Agents code for bugs, anti-patterns, and improvements. Use when reviewing code that uses create_deep_agent, backends, subagents, middleware, or human-in-the-loop patterns. Catches common configuration and usage mistakes.
한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.
Interview a user to discover a concrete GTM problem or manual task, recommend the right installed Deepline skill, prebuilt Play, recipe, or tool, confirm the plan and org, then start the chosen workflow. Use only when the user explicitly invokes deepline-start.
한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.
Use when the user wants a last30days-style pre-research pass in Deepline: discover the critical public, private, CRM, workflow, social, and web data sources for a research/enrichment job; compare provider coverage; estimate Deepline credit cost; recommend the source plan before building or running the workflow; or build custom language/messaging from buyer, competitor, community, and CRM evidence. Triggers: pre-research, source discovery, provider strategy, research data sources, ScrapeCreators, X/Twitter data, Reddit comments, public and private datasets, CRM data, workflow data, custom language, messaging language, pain language.
한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.
Use this skill when building, enriching, auditing, or uploading B2B paid ads audiences to Google Customer Match, Meta/Facebook Custom Audiences, or LinkedIn Matched Audiences. Triggers on phrases like '/deepline-ads-audience', '/deepline-ads-audiences', 'upload this audience', 'create custom audiences', 'personal email hashes', 'increase Facebook match rate', 'Google ads audience', 'Meta audience', 'FB audience', or any workflow that turns CRM/customer/contact data into paid ads upload lists. Skip for outbound prospecting sequences, cold email, or pure campaign copywriting.
한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.
Use this skill when answering business analytics, RevOps, GTM metric, pipeline, revenue, funnel, customer, or warehouse questions with Deepline. Triggers on phrases like 'query Snowflake', 'analyze pipeline', 'total ACV', 'break down by quarter', 'use the semantic layer', 'run a semantic query', or any use of snowflake_get_semantic_layer / snowflake_run_semantic_query. Skip prospecting, enrichment, contact finding, outbound, or personalization workflows; use deepline-gtm for those.
한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.
Retired. Reporting feedback and sharing a session are documented by the CLI itself: run `deepline feedback send --help` and `deepline sessions send --help`. Kept only so installed CLIs that still list this skill keep syncing.
한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.
Convert deep research output (Claude Research, ChatGPT Deep Research, Gemini, Codex — any long-form MD/Word/text) into a consulting-quality HTML report: pyramid structure, numbers promoted to KPIs/charts, comparisons turned into framework tables, citations preserved. Use when the user provides research/investigation results and says レポートにして/HTMLにまとめて/資料にして/きれいにして, mentions ディープリサーチの結果/調査結果/リサーチ結果, or asks to research a topic AND deliver a report. NEVER invents numbers or facts not present in the source (盛らない原則).
한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.
Use when the user asks for a deep, exhaustive, multi-pass, or variance-reducing repository-wide or scoped-path Codex Security scan. Run repeated complete independent Standard scans with the Codex Security deep-scan tool, which aggregates their validated findings and prepares the canonical artifacts; then complete the same scan once. Do not use for PRs, commits, branch diffs, or working-tree diffs.
한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.
Deep exploration and synthesis workflow with dynamic planning and hub-and-spoke coordination. Use for deep analysis, codebase understanding, or thorough investigation of a focus area.
한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.
Multi-step autonomous research methodology for deep investigation tasks with structured synthesis
한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.
Package codebases into LLM-optimized markdown, and run the Deep Think Authority pipeline (context-builder → Deep Think review → structured AUTHORITY → Flash/Antigravity implementation agent). Use when generating project context, preparing Deep Think reviews, or binding a weaker coding agent to a senior reasoning pass.
한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.
Deep research powered by Exa. Use for lead generation, literature reviews, deep dives, competitive analysis, or any query where one search falls short, including phrases like 'research this', 'find everything about', 'find me all', or 'deep dive on'.
한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.
Enhance an existing marketing plan with parallel research. Use when the agent has a draft plan (brand strategy, campaign brief, content calendar, launch plan) that needs strengthening with real data. Triggers on 'deepen this plan', 'strengthen this strategy', 'research gaps in my plan', 'make this plan better', 'this plan is too surface level', 'add research to this', 'validate this plan', 'back this up with data', or when a plan exists but lacks audience data, competitive positioning, or keyword strategy. Make sure to use this whenever someone has an EXISTING plan that feels thin or unresearched — even if they just say 'is this plan good enough?' or 'what's missing here?', they likely need deepening. This skill ENHANCES existing plans — it does not create new ones. If no plan exists, route to /brainstorm or /launch-strategy first.
한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.
Shared vocabulary for designing deep modules. Use when the user wants to design or improve a module's interface, find deepening opportunities, decide where a seam goes, make code more testable or AI-navigable, or when another skill needs the deep-module vocabulary.
한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.
Deep linking patterns - Universal Links (iOS), App Links (Android), URI schemes, expo-linking API, React Navigation linking config, Expo Router automatic linking, AASA/assetlinks.json setup, deferred deep links, testing
한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.
Complete PortSwigger deep-dive with exact payloads for every lab variant including zero-day techniques
한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.
Complete PortSwigger deep-dive with exact payloads for every lab variant including zero-day techniques
한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.
Complete PortSwigger deep-dive with exact payloads for every lab variant including zero-day techniques
한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.
Complete PortSwigger deep-dive with exact payloads for every lab variant including zero-day techniques
한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.
Complete PortSwigger deep-dive with exact payloads for every lab variant including zero-day techniques
한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.
Complete PortSwigger deep-dive with exact payloads for every lab variant including zero-day techniques
한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.
Complete PortSwigger deep-dive with exact payloads for every lab variant including zero-day techniques
한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.