A SEC filing research prompt pack for source-aware stock research

A developer has created a prompt pack for source-aware stock research that requires AI models to cite specific SEC filings, dates, and exact excerpts for every claim. The workflow enforces a non-negotiable rule that answers must include source type, publication date, exact text, confidence level, and what remains unknown, with a built-in checklist of red flags that force human review. The project, called Tomorrow Terminal, aims to combine filings, financials, market data, and crowd discussion into a single company profile without allowing AI to invent confidence or make predictions.

Who this is for Use this when you want to understand a company from primary sources without letting an AI model invent confidence. The goal is not to decide whether a stock is good or bad. The goal is to build a cleaner research trail from SEC filings, financial statements, market data, news, and crowd discussion. Non-negotiable rule Every answer must include: - Source type, for example 10-K, 10-Q, 8-K, S-1, earnings release, transcript, news article, or company page - Filing or publication date - Exact excerpt or table row used - A short explanation of why it matters - Confidence level - What is still unknown If the model cannot cite the source, it should say so and stop. 10 minute first-pass workflow - Identify the business - Read the company description, segment note, and latest risk factors. - Output a one-paragraph plain-English business model. - Find what changed - Compare the latest 10-Q or 10-K against the prior period. - Focus on revenue, gross margin, cash flow, debt, customer concentration, and share count. - Check liquidity and dilution risk - Pull cash, debt, operating cash flow, recent financing, shelf registrations, warrants, and ATM programs. - Read management's own warnings - Extract the 5 to 10 risk factors most directly tied to revenue, survival, regulation, or financing. - Separate facts from narrative - Create two columns: verified facts and management claims. - Inspect market and crowd context - Summarize recent news, Reddit, and StockTwits discussion as attention context only. - Do not treat crowd excitement as evidence of business quality. - Write the research memo - Summarize what is known, what changed, what could matter next, and what needs human review. Prompt 1: source-grounded company snapshot Prompt 2: compare this filing to the prior one Prompt 3: risk factor triage Prompt 4: liquidity and dilution checklist Prompt 5: management claim audit Prompt 6: crowd discussion sanity check Prompt 7: final research memo template Red flags that should force a human review - The model cites a filing but cannot quote the excerpt - The model mixes quarterly and annual numbers without labeling them - The model treats adjusted EBITDA as cash flow - The model ignores share count changes - The model makes a recommendation from social sentiment - The model summarizes a risk factor without checking whether it changed - The model uses news as proof when the primary filing says something narrower Clean output checklist Before sharing a research note, verify: - Every major claim has a source - Dates are visible - Excerpts are short and exact - Unknowns are listed instead of guessed - Crowd chatter is clearly labeled as chatter - The conclusion does not become financial advice Why I made this I have been working on Tomorrow Terminal, a source-aware stock research workflow that combines filings, financials, market data, news, Reddit, and StockTwits into one company profile. This prompt pack is the manual version of the standard I want AI research tools to meet: useful summaries, visible evidence, and no magic predictions. Research only. Not financial advice.