Deep Research

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

├─ 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:

Decompose query

into 5-10 independent search angles before ANY searches

Launch ALL searches in single message

with multiple tool calls (NOT sequential)

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

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)

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

python scripts/validate_report.py

--report

[

path

]

8 automated checks:

Executive summary length (50-250 words)

Required sections present (+ recommended: Claims table, Counterevidence)

Citations formatted [1], [2], [3]

Bibliography matches citations

No placeholder text (TBD, TODO)

Word count reasonable (500-10000)

Minimum 10 sources

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

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

If ANY check fails:

Regenerate the section before moving to next.

Source Attribution Standards (Critical for Preventing Fabrication):

Immediate citation

Every factual claim followed by [N] citation in same sentence

Quote sources directly

Use "According to [1]..." or "[1] reports..." for factual statements

Distinguish fact from synthesis

:

✅ GOOD: "Mortality decreased 23% (p<0.01) in the treatment group [1]."

❌ BAD: "Studies show mortality improved significantly."

No vague attributions

:

❌ NEVER: "Research suggests...", "Studies show...", "Experts believe..."

✅ ALWAYS: "Smith et al. (2024) found..." [1], "According to FDA data..." [2]

Label speculation explicitly

:

✅ GOOD: "This suggests a potential mechanism..." (analysis, not fact)

❌ BAD: "The mechanism is..." (presented as fact without citation)

Admit uncertainty

:

✅ GOOD: "No sources found addressing X directly."

❌ BAD: Fabricating a citation to fill the gap

Template pattern

"[Specific claim with numbers/data] [Citation]. [Analysis/implication]." Deliver to user: Executive summary (inline in chat) Organized folder path (e.g., "All files saved to: ~/Documents/Psilocybin_Research_20251104/") Confirmation of all three formats generated: Markdown (source) HTML (McKinsey-style, opened in browser) PDF (professional print, opened in viewer) Source quality assessment summary (source count) Next steps (if relevant) Generation Workflow: Progressive File Assembly (Unlimited Length) Phase 8.1: Setup

Extract topic slug from research question

Create folder: ~/Documents/[TopicName]Research[YYYYMMDD]/

mkdir -p ~/Documents/ [ folder_name ]

Create initial markdown file with frontmatter

File path: [folder]/research_report_[YYYYMMDD]_[slug].md

Phase 8.2: Progressive Section Generation CRITICAL STRATEGY: Generate and write each section individually to file using Write/Edit tools. This allows unlimited report length while keeping each generation manageable. OUTPUT TOKEN LIMIT SAFEGUARD (CRITICAL - Claude Code Default: 32K): Claude Code default limit: 32,000 output tokens (≈24,000 words total per skill execution) This is a HARD LIMIT and cannot be changed within the skill. What this means: Total output (your text + all tool call content) must be <32,000 tokens 32,000 tokens ≈ 24,000 words max Leave safety margin: Target ≤20,000 words total output Realistic report sizes per mode: Quick mode: 2,000-4,000 words ✅ (well under limit) Standard mode: 4,000-8,000 words ✅ (comfortably under limit) Deep mode: 8,000-15,000 words ✅ (achievable with care) UltraDeep mode: 15,000-20,000 words ⚠️ (at limit, monitor closely) For reports >20,000 words: User must run skill multiple times: Run 1: "Generate Part 1 (sections 1-6)" → saves to part1.md Run 2: "Generate Part 2 (sections 7-12)" → saves to part2.md User manually combines or asks Claude to merge files Auto-Continuation Strategy (TRUE Unlimited Length): When report exceeds 18,000 words in single run: Generate sections 1-10 (stay under 18K words) Save continuation state file with context preservation Spawn continuation agent via Task tool Continuation agent: Reads state → Generates next batch → Spawns next agent if needed Chain continues recursively until complete This achieves UNLIMITED length while respecting 32K limit per agent Initialize Citation Tracking: citations_used = [] # Maintain this list in working memory throughout Section Generation Loop: Pattern: Generate section content → Use Write/Edit tool with that content → Move to next section Each Write/Edit call contains ONE section (≤2,000 words per call) Executive Summary (200-400 words) Generate section content Tool: Write(file, content=frontmatter + Executive Summary) Track citations used Progress: "✓ Executive Summary" Introduction (400-800 words) Generate section content Tool: Edit(file, old=last_line, new=old + Introduction section) Track citations used Progress: "✓ Introduction" Finding 1 (600-2,000 words) Generate complete finding Tool: Edit(file, append Finding 1) Track citations used Progress: "✓ Finding 1" Finding 2 (600-2,000 words) Generate complete finding Tool: Edit(file, append Finding 2) Track citations used Progress: "✓ Finding 2" ... Continue for ALL findings (each finding = one Edit tool call, ≤2,000 words) CRITICAL: If you have 10 findings × 1,500 words each = 15,000 words of findings This is OKAY because each Edit call is only 1,500 words (under 2,000 word limit per tool call) The FILE grows to 15,000 words, but no single tool call exceeds limits Synthesis & Insights Generate: Novel insights beyond source statements (as long as needed for synthesis) Tool: Edit (append to file) Track: Extract citations, append to citations_used Progress: "Generated Synthesis ✓" Limitations & Caveats Generate: Counterevidence, gaps, uncertainties (appropriate depth) Tool: Edit (append to file) Track: Extract citations, append to citations_used Progress: "Generated Limitations ✓" Recommendations Generate: Immediate actions, next steps, research needs (appropriate depth) Tool: Edit (append to file) Track: Extract citations, append to citations_used Progress: "Generated Recommendations ✓" Bibliography (CRITICAL - ALL Citations) Generate: COMPLETE bibliography with EVERY citation from citations_used list Format: [1], [2], [3]... [N] - each citation gets full entry Verification: Check citations_used list - if list contains [1] through [73], generate all 73 entries NO ranges ([1-50]), NO placeholders ("Additional citations"), NO truncation Tool: Edit (append to file) Progress: "Generated Bibliography ✓ (N citations)" Methodology Appendix Generate: Research process, verification approach (appropriate depth) Tool: Edit (append to file) Progress: "Generated Methodology ✓" Phase 8.3: Auto-Continuation Decision Point After generating sections, check word count: If total output ≤18,000 words: Complete normally Generate Bibliography (all citations) Generate Methodology Verify complete report Save copy to ~/.claude/research_output/ Done! ✓ If total output will exceed 18,000 words: Auto-Continuation Protocol Step 1: Save Continuation State Create file: ~/.claude/research_output/continuation_state_[report_id].json { "version" : "2.1.1" , "report_id" : "[unique_id]" , "file_path" : "[absolute_path_to_report.md]" , "mode" : "[quick|standard|deep|ultradeep]" , "progress" : { "sections_completed" : [ list of section IDs done ] , "total_planned_sections" : [ total count ] , "word_count_so_far" : [ current word count ] , "continuation_count" : [ which continuation this is , starts at 1 ] } , "citations" : { "used" : [ 1 , 2 , 3 , ... , N ] , "next_number" : [ N+ 1 ] , "bibliography_entries" : [ "[1] Full citation entry" , "[2] Full citation entry" , ... ] } , "research_context" : { "research_question" : "[original question]" , "key_themes" : [ "theme1" , "theme2" , "theme3" ] , "main_findings_summary" : [ "Finding 1: [100-word summary]" , "Finding 2: [100-word summary]" , ... ] , "narrative_arc" : "[Current position in story: beginning/middle/conclusion]" } , "quality_metrics" : { "avg_words_per_finding" : [ calculated average ] , "citation_density" : [ citations per 1000 words ] , "prose_vs_bullets_ratio" : [ e.g. , "85% prose" ] , "writing_style" : "technical-precise-data-driven" } , "next_sections" : [ { "id" : N , "type" : "finding" , "title" : "Finding X" , "target_words" : 1500 } , { "id" : N+ 1 , "type" : "synthesis" , "title" : "Synthesis" , "target_words" : 1000 } , ... ] } Step 2: Spawn Continuation Agent Use Task tool with general-purpose agent: Task( subagent_type="general-purpose", description="Continue deep-research report generation", prompt=""" CONTINUATION TASK: You are continuing an existing deep-research report. CRITICAL INSTRUCTIONS: 1. Read continuation state file: ~/.claude/research_output/continuation_state_[report_id].json 2. Read existing report to understand context: [file_path from state] 3. Read LAST 3 completed sections to understand flow and style 4. Load research context: themes, narrative arc, writing style from state 5. Continue citation numbering from state.citations.next_number 6. Maintain quality metrics from state (avg words, citation density, prose ratio) CONTEXT PRESERVATION: - Research question: [from state] - Key themes established: [from state] - Findings so far: [summaries from state] - Narrative position: [from state] - Writing style: [from state] YOUR TASK: Generate next batch of sections (stay under 18,000 words): [List next_sections from state] Use Write/Edit tools to append to existing file: [file_path] QUALITY GATES (verify before each section): - Words per section: Within ±20% of [avg_words_per_finding] - Citation density: Match [citation_density] ±0.5 per 1K words - Prose ratio: Maintain ≥80% prose (not bullets) - Theme alignment: Section ties to key_themes - Style consistency: Match [writing_style] After generating sections: - If more sections remain: Update state, spawn next continuation agent - If final sections: Generate complete bibliography, verify report, cleanup state file HANDOFF PROTOCOL (if spawning next agent): 1. Update continuation_state.json with new progress 2. Add new citations to state 3. Add summaries of new findings to state 4. Update quality metrics 5. Spawn next agent with same instructions """ ) Step 3: Report Continuation Status Tell user: 📊 Report Generation: Part 1 Complete (N sections, X words) 🔄 Auto-continuing via spawned agent... Next batch: [section list] Progress: [X%] complete Phase 8.4: Continuation Agent Quality Protocol When continuation agent starts: Context Loading (CRITICAL): Read continuation_state.json → Load ALL context Read existing report file → Review last 3 sections Extract patterns: Sentence structure complexity Technical terminology used Citation placement patterns Paragraph transition style Pre-Generation Checklist: Loaded research context (themes, question, narrative arc) Reviewed previous sections for flow Loaded citation numbering (start from N+1) Loaded quality targets (words, density, style) Understand where in narrative arc (beginning/middle/end) Per-Section Generation: Generate section content Quality checks: Word count: Within target ±20% Citation density: Matches established rate Prose ratio: ≥80% prose Theme connection: Ties to key_themes Style match: Consistent with quality_metrics.writing_style If ANY check fails: Regenerate section If passes: Write to file, update state Handoff Decision: Calculate: Current word count + remaining sections × avg_words_per_section If total < 18K: Generate all remaining sections + finish If total > 18K: Generate partial batch, update state, spawn next agent Final Agent Responsibilities: Generate final content sections Generate COMPLETE bibliography using ALL citations from state.citations.bibliography_entries Read entire assembled report Run validation: python scripts/validate_report.py --report [path] Delete continuation_state.json (cleanup) Report complete to user with metrics Anti-Fatigue Built-In: Each agent generates manageable chunks (≤18K words), maintaining quality. Context preservation ensures coherence across continuation boundaries. Generate HTML (McKinsey Style) Read McKinsey template from ./templates/mckinsey_report_template.html Extract 3-4 key quantitative metrics from findings for dashboard Use Python script for MD to HTML conversion: cd ~/.claude/skills/deep-research python scripts/md_to_html.py [ markdown_report_path ] The script returns two parts: Part A ({{CONTENT}}): All sections except Bibliography, properly converted to HTML Part B ({{BIBLIOGRAPHY}}): Bibliography section only, formatted as HTML CRITICAL: The script handles ALL conversion automatically: Headers: ## →