Fin Guru Research
- 17 installs
- 316 repo stars
- Updated August 1, 2026
- aojdevstudio/finance-guru
fin-guru-research is a skill that executes market research workflows covering market intelligence, sector analysis, security research, and competitive intelligence with temporal validation.
About
A skill that runs structured market research workflows for Finance Guru. It scopes objectives, collects intelligence with temporal qualifiers, validates sources, flags stale market and economic data, and synthesizes findings with confidence levels for downstream quant or strategy work. A developer uses it to produce a validated, source-cited research summary.
- Structured market research workflow with source and temporal validation
- Covers market intelligence, sector, security, and competitive research
- Flags stale data and requires timestamped, tagged source citations
Fin Guru Research by the numbers
- 17 all-time installs (skills.sh)
- Ranked #731 of 1,106 Finance & Trading skills by installs in the Skillselion catalog
- Data as of Aug 2, 2026 (Skillselion catalog sync)
fin-guru-research capabilities & compatibility
- Capabilities
- research · web search
- Use cases
- research · web search · trading
- Pricing
- Free
What fin-guru-research says it does
Execute comprehensive market research workflows. Covers market intelligence gathering, sector analysis, security research, and competitive intelligence with temporal validation.
ALL web searches MUST include temporal qualifiers using current date context
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| Installs | 17 |
|---|---|
| repo stars | ★ 316 |
| Last updated | August 1, 2026 |
| Repository | aojdevstudio/finance-guru ↗ |
What it does
Run structured, source-validated market research and package findings for downstream financial analysis.
Who is it for?
Gathering and validating timestamped market intelligence to hand off to quant or strategy work.
Skip if: Running the statistical models themselves or executing trades.
When should I use this skill?
When you need scoped, source-validated market or sector research with temporal awareness.
What you get
A research summary with confidence levels, flagged data gaps, and timestamped sources ready for handoff.
- Market research summary
- source citations
- handoff package for quant/strategy
By the numbers
- 6-step workflow
- 8 technical screening patterns
- economic data flagged after 30 days
Files
Research Workflow Skill
Execute structured market research with source validation and temporal awareness.
Workflow Steps
1. Scope Definition — Clarify research objectives, timeframe, and deliverable format 2. Data Collection — Gather intelligence from multiple sources with temporal qualifiers 3. Source Validation — Flag market data older than same-day, economic data older than 30 days 4. Analysis — Apply analytical frameworks to collected data 5. Synthesis — Produce research summary with confidence levels and data gaps 6. Handoff — Package findings for downstream analysis (quant, strategy)
Tools Integration
screener_cli.py— Multi-pattern technical screening (8 patterns)moving_averages_cli.py— Trend identification (SMA/EMA/WMA/HMA)momentum_cli.py— Confluence analysis (RSI, MACD, Stochastic, Williams %R, ROC)volatility_cli.py— Regime analysis and opportunity assessmentdata_validator_cli.py— Data integrity verification (100% quality required)itc_risk_cli.py— Market-implied risk scores for supported tickers
Requirements
- ALL web searches MUST include temporal qualifiers using current date context
- Separate verified data from assumptions with confidence levels
- Cite all sources with START/END tags and precise timestamps
- Flag data gaps relevant to downstream analysis
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How does it handle data freshness?
It flags market data older than same-day and economic data older than 30 days, and requires temporal qualifiers on all web searches.
What screening tools does it use?
screener_cli.py for multi-pattern technical screening (8 patterns), plus moving-average, momentum, and volatility CLIs.