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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.
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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.
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10 minute first-pass workflow
Identify the business
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Read the company description, segment note, and latest risk factors.
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Output a one-paragraph plain-English business model.
Find what changed
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Compare the latest 10-Q or 10-K against the prior period.
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Focus on revenue, gross margin, cash flow, debt, customer concentration, and share count.
Check liquidity and dilution risk
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Pull cash, debt, operating cash flow, recent financing, shelf registrations, warrants, and ATM programs.
Read management's own warnings
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Extract the 5 to 10 risk factors most directly tied to revenue, survival, regulation, or financing.
Separate facts from narrative
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Create two columns: verified facts and management claims.
Inspect market and crowd context
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Summarize recent news, Reddit, and StockTwits discussion as attention context only.
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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.
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Prompt 1: source-grounded company snapshot
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Prompt 2: compare this filing to the prior one
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Prompt 3: risk factor triage
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Prompt 4: liquidity and dilution checklist
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Prompt 5: management claim audit
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Prompt 6: crowd discussion sanity check
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Prompt 7: final research memo template
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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
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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
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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.