full stack stock research scorecard

The problem

Investment decisions often rely on fragmented data, leading to biased trades or missed risks. Developers and traders struggle to synthesize business quality, financial fundamentals, and technical price action into a single, objective framework.

What it does

• Evaluates competitive moats and management capital allocation to determine business quality.
• Audits financial health by calculating debt ratios, margin stability, and valuation multiples against industry peers.
• Identifies entry and exit zones using moving averages, momentum oscillators, and volume confirmation.
• Synthesizes market sentiment from analyst ratings, institutional flows, and options market data.
• Generates a structured scorecard with weighted ratings across six dimensions for objective decision-making.

Why this beats prompting it yourself

General prompts often ignore the tension between fundamentals and technicals. This skill enforces a rigorous six-point inspection that prevents tunnel vision, ensuring you don't buy a great company at a bad price or a strong chart with a weak balance sheet.

Use cases

• Conducting deep-dive due diligence on a new ticker before committing capital.
• Comparing multiple stocks in the same sector to find the best risk-adjusted opportunity.
• Reviewing existing portfolio holdings to determine if a trend reversal warrants a sell.
• Developing a structured entry plan with specific stop-loss and profit-taking targets.

Known limitations

Requires access to real-time or historical market data tools to populate metrics. Returns a neutral score when data is unavailable rather than speculating.