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deep-research

Use when the user needs multi-source research with citation tracking, evidence persistence, and structured report generation. Triggers on "deep research", "comprehensive analysis", "research report", "compare X vs Y", "analyze trends", or "state of the art". Not for simple lookups, debugging, or questions answerable with 1-2 searches.

한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.

aiskillstore/marketplace
설치 방법 보기

포함된 파일(5)

  • SKILL.md4.2 KB
  • .gitignore264 B
  • README.md4.8 KB
  • requirements.txt579 B
  • skill-report.json23.6 KB

SKILL.md(원문)

설치하기 전에 에이전트에게 전달되는 지시 내용을 확인할 수 있습니다.

Deep Research

Core Purpose

Deliver citation-tracked research reports through a structured pipeline with evidence persistence, source identity management, claim-level verification, and progressive context management.

Autonomy Principle: Operate independently. Infer assumptions from context. Only stop for critical errors or incomprehensible queries. Surface high-materiality assumptions explicitly in the Introduction and Methodology rather than silently defaulting.

Decision Tree

Request Analysis
+-- Simple lookup? --> STOP: Use WebSearch
+-- Debugging? --> STOP: Use standard tools
+-- Complex analysis needed? --> CONTINUE

Mode Selection
+-- Initial exploration --> quick (3 phases, 2-5 min)
+-- Standard research --> standard (6 phases, 5-10 min) [DEFAULT]
+-- Critical decision --> deep (8 phases, 10-20 min)
+-- Comprehensive review --> ultradeep (8+ phases, 20-45 min)

Default assumptions: Technical query = technical audience. Comparison = balanced perspective. Trend = recent 1-2 years.

Workflow Overview

PhaseNameQuickStdDeepUltra
1SCOPEYYYY
2PLAN-YYY
3RETRIEVEYYYY
4TRIANGULATE-YYY
4.5OUTLINE REFINEMENT-YYY
5SYNTHESIZE-YYY
6CRITIQUE--YY
7REFINE--YY
8PACKAGEYYYY

Note: Phases 3-5 operate as an evidence loop per section (retrieve → evidence store → refine outline → draft → verify claims → delta-retrieve if needed), not as strict sequential gates.

Execution

On invocation, load relevant reference files:

  1. Phase 1-7: Load methodology.md for detailed phase instructions
  2. Phase 8 (Report): Load report-assembly.md for progressive generation
  3. HTML/PDF output: Load html-generation.md
  4. Quality checks: Load quality-gates.md
  5. Long reports (>18K words): Load continuation.md

Templates:

Scripts:

  • python scripts/validate_report.py --report [path]
  • python scripts/verify_citations.py --report [path]
  • python scripts/md_to_html.py [markdown_path]

Output Contract

Required sections:

  • Executive Summary (200-400 words)
  • Introduction (scope, methodology, assumptions)
  • Main Analysis (4-8 findings, 600-2,000 words each, cited)
  • Synthesis & Insights (patterns, implications)
  • Limitations & Caveats
  • Recommendations
  • Bibliography (COMPLETE - every citation, no placeholders)
  • Methodology Appendix

Output files (all to ~/Documents/[Topic]_Research_[YYYYMMDD]/):

  • Markdown (primary source of truth)
  • sources.jsonl — stable source registry with canonical IDs
  • evidence.jsonl — append-only evidence store with quotes and locators
  • claims.jsonl — atomic claim ledger with support status
  • run_manifest.json — query, mode, assumptions, provider config
  • HTML (McKinsey style, auto-opened)
  • PDF (professional print, auto-opened)

Quality standards:

  • 10+ sources, 3+ per major claim (cluster-independent, not just count)
  • All factual claims cited immediately [N] with evidence backing in evidence.jsonl
  • Claim-support verification mandatory: no unsupported factual claims pass delivery
  • No placeholders, no fabricated citations
  • Prose-first (>=80%), bullets sparingly

When to Use / NOT Use

Use: Comprehensive analysis, technology comparisons, state-of-the-art reviews, multi-perspective investigation, market analysis.

Do NOT use: Simple lookups, debugging, 1-2 search answers, quick time-sensitive queries.

리뷰

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한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.

aiskillstore/marketplace4432026년 10월 23일 업데이트

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한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.

aiskillstore/marketplace4432026년 10월 23일 업데이트

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한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.

aiskillstore/marketplace4432026년 10월 23일 업데이트

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Browser automation for AI agents via inference.sh. Navigate web pages, interact with elements using @e refs, take screenshots, record video. Capabilities: web scraping, form filling, clicking, typing, drag-drop, file upload, JavaScript execution. Use for: web automation, data extraction, testing, agent browsing, research. Triggers: browser, web automation, scrape, navigate, click, fill form, screenshot, browse web, playwright, headless browser, web agent, surf internet, record video

한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.

aiskillstore/marketplace4432026년 10월 23일 업데이트

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한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.

aiskillstore/marketplace4432026년 10월 23일 업데이트

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한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.

aiskillstore/marketplace4432026년 10월 23일 업데이트

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