Fetches financial-deep-research from eng0ai/eng0-template-skills and configures it for Cursor.
3
Select Cursor when prompted
The CLI shows a list of agents. Use arrow keys and space to select Cursor:
◆ Which agents do you want to install to?
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│ ── Universal (.agents/skills) ────────────────
│ · Cline · Codex · Goose · Windsurf
│ ●Cursor(selected)
│ · Cursor · Aider · Continue
4
Verify installation
Confirm successful installation by checking the skill directory location:
.cursor/skills/financial-deep-research
Restart Cursor to activate financial-deep-research. Access via /financial-deep-research in your agent's command palette.
⚠
Security Notice
We perform automated surface-level scans (Gen AI Scanner, Socket, Snyk) during installation. These checks detect common vulnerabilities but do not guarantee complete security. Always review skill source code and verify the publisher's reputation before production use.
Skills execute code in your environment. Always review source, verify the publisher, and test in isolation before production.
Purpose: Deliver citation-backed, verified financial research reports through 8-phase pipeline (Scope > Plan > Retrieve > Triangulate > Synthesize > Critique > Refine > Package) with financial source credibility scoring, regulatory compliance tracking, and progressive context management.
Financial Focus: This skill specializes in:
Market analysis and investment research
Due diligence and competitive benchmarking
Regulatory compliance and risk assessment
Financial modeling support and valuation analysis
Earnings analysis and financial statement review
Sector/industry deep dives
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 stock quote? -> STOP: Use WebSearch, not this skill
|-- Basic company lookup? -> STOP: Use WebSearch, not this skill
|-- Debugging code? -> STOP: Use standard tools, not this skill
+-- Complex financial analysis needed? -> CONTINUE
Mode Selection
|-- Quick market check? -> quick (3 phases, 2-5 min)
|-- Standard analysis? -> standard (6 phases, 5-10 min) [DEFAULT]
|-- Investment decision? -> deep (8 phases, 10-20 min)
|-- Due diligence/M&A? -> 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., "analyze the thing")
Place critical financial metrics dashboard at top (extract 3-4 key metrics: market cap, P/E, revenue growth, etc.)
Use data tables for dense financial information
14px base font, compact spacing, no decorative gradients or colors
OPEN in browser automatically after generation
PDF (Professional Print - ALWAYS GENERATE):
Save to: [Documents folder]/financial_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:
financial_report_20251104_aapl_analysis.md
financial_report_20251104_aapl_analysis.html
financial_report_20251104_aapl_analysis.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)
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 analyses with many findings? Generate 20, 30, 50+ findings - no constraint!
›Access to product documentation and roadmap tools (Jira, Notion, etc.)
›Understanding of product management frameworks (RICE, Jobs-to-be-Done, etc.)
›Stakeholder contact information and communication channels
Time Estimate
30-60 minutes to see productivity improvements
Steps
1Install product management skill
2Start with user story generation for known feature
3Progress to competitive analysis: research 2-3 competitors
4Use for roadmap prioritization: apply RICE/ICE scoring
5Draft stakeholder communications and refine based on feedback
6Build template library for recurring PM tasks
7Share effective prompts with product team
Common Pitfalls
⚠Not validating competitive research—verify facts before sharing
⚠Accepting user stories without involving engineering team
⚠Over-relying on frameworks without qualitative judgment
⚠Not customizing outputs to company culture and communication style
⚠Skipping stakeholder validation of generated requirements
Best Practices
✓ Do
+Validate research and competitive analysis with real data
+Collaborate with engineering when generating technical requirements
+Customize frameworks and templates to your company context
+Use skill for first drafts, refine with stakeholder input
+Document successful prompt patterns for PM tasks
+Combine AI efficiency with human judgment and intuition
✗ Don't
−Don't publish competitive analysis without fact-checking
−Don't finalize user stories without engineering review
−Don't make prioritization decisions solely on AI scoring
−Don't skip customer validation of generated requirements
−Don't ignore company-specific context and culture
💡 Pro Tips
★Provide context: company goals, constraints, customer feedback
★Ask for alternatives: 'Show 3 ways to prioritize this roadmap'
★Request stakeholder-specific formatting: 'Executive summary vs. engineering spec'
★Use skill for 70% generation + 30% customization to company needs
When to Use This
✓ Use when
Use for user story writing, competitive research, roadmap prioritization, stakeholder communication, and PRD drafting. Best for reducing repetitive documentation and research work.
✗ Avoid when
Avoid for strategic product vision (requires deep customer empathy), pricing decisions (needs market and financial expertise), or when face-to-face customer discovery is more valuable than speed.
Learning Path
1Basic: user stories, feature specs, status updates
