insight68/skills/deep-research

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Conduct enterprise-grade research with multi-source synthesis, citation tracking, and verification. Use when user needs comprehensive analysis requiring 10+ sources, verified claims, or comparison of approaches. Triggers include "deep research", "comprehensive analysis", "research report", "compare X vs Y", or "analyze trends". Do NOT use for simple lookups, debugging, or questions answerable with 1-2 searches.

Install

npx vskill@latest install insight68/skills/deep-research

SKILL.md

Deep Research

<!-- STATIC CONTEXT BLOCK START - Optimized for prompt caching --> <!-- All static instructions, methodology, and templates below this line --> <!-- Dynamic content (user queries, results) added after this block -->

Core System Instructions

Purpose: Deliver citation-backed, verified research reports through 8-phase pipeline (Scope → Plan → Retrieve → Triangulate → Synthesize → Critique → Refine → Package) with source credibility scoring and progressive context management.

Context Strategy: This skill uses 2025 context engineering best practices:

  • Static instructions cached (this section)
  • Progressive disclosure (load references only when needed)
  • Avoid "loss in the middle" (critical info at start/end, not buried)
  • Explicit section markers for context navigation

Decision Tree (Execute First)

Request Analysis
├─ Simple lookup? → STOP: Use WebSearch, not this skill
├─ Debugging? → STOP: Use standard tools, not this skill
└─ 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)
Execution Loop (per phase)
├─ Load phase instructions from [methodology](./reference/methodology.md#phase-N)
├─ Execute phase tasks
├─ Spawn parallel agents if applicable
└─ Update progress
Validation Gate
├─ Run `python scripts/validate_report.py --report [path]`
├─ Pass? → Deliver
└─ Fail? → Fix (max 2 attempts) → Still fails? → Escalate

Workflow (Clarify → Plan → Act → Verify → Report)

AUTONOMY PRINCIPLE: This skill operates independently. Infer assumptions from query context. Only stop for critical errors or incomprehensible queries.

1. Clarify (Rarely Needed - Prefer Autonomy)

DEFAULT: Proceed autonomously. Derive assumptions from query signals.

ONLY ask if CRITICALLY ambiguous:

  • Query is incomprehensible (e.g., "research the thing")
  • Contradictory requirements (e.g., "quick 50-source ultradeep analysis")

When in doubt: PROCEED with standard mode. User will redirect if incorrect.

Default assumptions:

  • Technical query → Assume technical audience
  • Comparison query → Assume balanced perspective needed
  • Trend query → Assume recent 1-2 years unless specified
  • Standard mode is default for most queries

2. Plan

Mode selection criteria:

  • Quick (2-5 min): Exploration, broad overview, time-sensitive
  • Standard (5-10 min): Most use cases, balanced depth/speed [DEFAULT]
  • Deep (10-20 min): Important decisions, need thorough verification
  • UltraDeep (20-45 min): Critical analysis, maximum rigor

Announce plan and execute:

  • Briefly state: selected mode, estimated time, number of sources
  • Example: "Starting standard mode research (5-10 min, 15-30 sources)"
  • Proceed without waiting for approval

3. Act (Phase Execution)

All modes execute:

  • Phase 1: SCOPE - Define boundaries (method)
  • Phase 3: RETRIEVE - Parallel search execution (5-10 concurrent searches + agents) (method)
  • Phase 8: PACKAGE - Generate report using template

Standard/Deep/UltraDeep execute:

  • Phase 2: PLAN - Strategy formulation
  • Phase 4: TRIANGULATE - Verify 3+ sources per claim
  • Phase 4.5: OUTLINE REFINEMENT - Adapt structure based on evidence (WebWeaver 2025) (method)
  • Phase 5: SYNTHESIZE - Generate novel insights

Deep/UltraDeep execute:

  • Phase 6: CRITIQUE - Red-team analysis
  • Phase 7: REFINE - Address gaps

Critical: Avoid "Loss in the Middle"

  • Place key findings at START and END of sections, not buried
  • Use explicit headers and markers
  • Structure: Summary → Details → Conclusion (not Details sandwiched)

Progressive Context Loading:

  • Load methodology sections on-demand
  • Load template only for Phase 8
  • Do not inline everything - reference external files

Anti-Hallucination Protocol (CRITICAL):

  • Source grounding: Every factual claim MUST cite a specific source immediately [N]
  • Clear boundaries: Distinguish between FACTS (from sources) and SYNTHESIS (your analysis)
  • Explicit markers: Use "According to [1]..." or "[1] reports..." for source-grounded statements
  • No speculation without labeling: Mark inferences as "This suggests..." not "Research shows..."
  • Verify before citing: If unsure whether source actually says X, do NOT fabricate citation
  • When uncertain: Say "No sources found for X" rather than inventing references

Parallel Execution Requirements (CRITICAL for Speed):

Phase 3 RETRIEVE - Mandatory Parallel Search:

  1. Decompose query into 5-10 independent search angles before ANY searches
  2. Launch ALL searches in single message with multiple tool calls (NOT sequential)
  3. Quality threshold monitoring for FFS pattern:
  • Track source count and avg credibility score
  • Proceed when threshold reached (mode-specific, see methodology)
  • Continue background searches for additional depth
  1. Spawn 3-5 parallel agents using Task tool for deep-dive investigations

Example correct execution:

[Single message with 8+ parallel tool calls]
WebSearch #1: Core topic semantic
WebSearch #2: Technical keywords
WebSearch #3: Recent 2024-2025 filtered
WebSearch #4: Academic domains
WebSearch #5: Critical analysis
WebSearch #6: Industry trends
Task agent #1: Academic paper analysis
Task agent #2: Technical documentation deep dive

❌ WRONG (sequential execution):

WebSearch #1 → wait for results → WebSearch #2 → wait → WebSearch #3...

✅ RIGHT (parallel execution):

All searches + agents launched simultaneously in one message

4. Verify (Always Execute)

Step 1: Citation Verification (Catches Fabricated Sources)

bash
python scripts/verify_citations.py --report [path]

Checks:

  • DOI resolution (verifies citation actually exists)
  • Title/year matching (detects mismatched metadata)
  • Flags suspicious entries (2024+ without DOI, no URL, failed verification)

If suspicious citations found:

  • Review flagged entries manually
  • Remove or replace fabricated sources
  • Re-run until clean

Step 2: Structure & Quality Validation

bash
python scripts/validate_report.py --report [path]

8 automated checks:

  1. Executive summary length (50-250 words)
  2. Required sections present (+ recommended: Claims table, Counterevidence)
  3. Citations formatted [1], [2], [3]
  4. Bibliography matches citations
  5. No placeholder text (TBD, TODO)
  6. Word count reasonable (500-10000)
  7. Minimum 10 sources
  8. No broken internal links

If fails:

  • Attempt 1: Auto-fix formatting/links
  • Attempt 2: Manual review + correction
  • After 2 failures: STOP → Report issues → Ask user

5. Report

CRITICAL: Generate COMPREHENSIVE, DETAILED markdown reports

File Organization (CRITICAL - Clean Accessibility):

1. Create Organized Folder in Documents:

  • ALWAYS create dedicated folder: ~/Documents/[TopicName]_Research_[YYYYMMDD]/
  • Extract clean topic name from research question (remove special chars, use underscores/CamelCase)
  • Examples:
  • "psilocybin research 2025" → ~/Documents/Psilocybin_Research_20251104/
  • "compare React vs Vue" → ~/Documents/React_vs_Vue_Research_20251104/
  • "AI safety trends" → ~/Documents/AI_Safety_Trends_Research_20251104/
  • If folder exists, use it; if not, create it
  • This ensures clean organization and easy accessibility

2. Save All Formats to Same Folder:

Markdown (Primary Source):

  • Save to: [Documents folder]/research_report_[YYYYMMDD]_[topic_slug].md
  • Also save copy to: ~/.claude/research_output/ (internal tracking)
  • Full detailed report with all findings

HTML (McKinsey Style - ALWAYS GENERATE):

  • Save to: [Documents folder]/research_report_[YYYYMMDD]_[topic_slug].html
  • Use McKinsey template: mckinsey_template
  • Design principles: Sharp corners (NO border-radius), muted corporate colors (navy #003d5c, gray #f8f9fa), ultra-compact layout, info-first structure
  • Place critical metrics dashboard at top (extract 3-4 key quantitative findings)
  • Use data tables for dense information presentation
  • 14px base font, compact spacing, no decorative gradients or colors
  • Attribution Gradients (2025): Wrap each citation [N] in <span class="citation"> with nested tooltip div showing source details
  • OPEN in browser automatically after generation

PDF (Professional Print - ALWAYS GENERATE):

  • Save to: [Documents folder]/research_report_[YYYYMMDD]_[topic_slug].pdf
  • Use generating-pdf skill (via Task tool with general-purpose agent)
  • Professional formatting with headers, page numbers
  • OPEN in default PDF viewer after generation

3. File Naming Convention: All files use same base name for easy matching:

  • research_report_20251104_psilocybin_2025.md
  • research_report_20251104_psilocybin_2025.html
  • research_report_20251104_psilocybin_2025.pdf

Length Requirements (UNLIMITED with Progressive Assembly):

  • Quick mode: 2,000+ words (baseline quality threshold)
  • Standard mode: 4,000+ words (comprehensive analysis)
  • Deep mode: 6,000+ words (thorough investigation)
  • UltraDeep mode: 10,000-50,000+ words (NO UPPER LIMIT - as comprehensive as evidence warrants)

How Unlimited Length Works: Progressive file assembly allows ANY report length by generating section-by-section. Each section is written to file immediately (avoiding output token limits). Complex topics with many findings? Generate 20, 30, 50+ findings - no constraint!

Content Requirements:

  • Use template as exact structure
  • Generate each section to APPROPRIATE depth (determined by evidence, not word targets)
  • Include specific data, statistics, dates, numbers (not vague statements)
  • Multiple paragraphs per finding with evidence (as many as needed)
  • Each section gets focused generation attention
  • DO NOT write summaries - write FULL analysis

Writing Standards:

  • Narrative-driven: Write in flowing prose. Each finding tells a story with beginning (context), middle (evidence), end (implications)
  • Precision: Every word deliberately chosen, carries intention
  • Economy: No fluff, eliminate fancy grammar, unnecessary modifiers
  • Clarity: Exact numbers embedded in sentences ("The study demonstrated a 23% reduction in mortality"), not isolated in bullets
  • Directness: State findings without embellishment
  • High signal-to-noise: Dense information, respect reader's time

Bullet Point Policy (Anti-Fatigue Enforcement):

  • Use bullets SPARINGLY: Only for distinct lists (product names, company roster, enumerated steps)
  • NEVER use bullets as primary content delivery - they fragment thinking
  • Each findings section requires substantive prose paragraphs (3-5+ paragraphs minimum)
  • Example: Instead of "• Market size: $2.4B" write "The global market reached $2.4 billion in 2023, driven by increasing consumer demand and regulatory tailwinds [1]."

Anti-Fatigue Quality Check (Apply to EVERY Section): Before considering a section complete, verify:

  • [ ] Paragraph count: ≥3 paragraphs for major sections (## headings)
  • [ ] Prose-first: <20% of content is bullet points (≥80% must be flowing prose)
  • [ ] No placeholders: Zero instances of "Content continues", "Due to length", "[Sections X-Y]"
  • [ ] Evidence-rich: Specific data points, statistics, quotes (not vague statements)
  • [ ] Citation density: Major claims cited within same sentence

This is the start of the file. Read the full SKILL.md on GitHub.

Security

  • Security scanPassed, 98 of 100Pattern checks on the skill's files.
  • Model reviewPassed

Quality evaluation

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Source

Popularity

Repository stars
4
7-day trend score
8

Stars and forks are for the whole GitHub repository, not this skill alone. Refreshed 13 May 2026, 5 months ago.

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