These are meant to be copied directly into your AI agent. Buzzberg provides bounded market context; the agent writes the read.
Buzzberg also exposes these as MCP prompts/resources in supported clients. Ask your agent: List Buzzberg workflows
or
Use the Buzzberg ticker deep dive prompt for SIVE..
Older clients can still copy the prompts below manually.
Ticker deep dive
Narrative quality check
Use Buzzberg to deep dive SIVE.
Who is talking about it, what is the core bull thesis,
what are the strongest bear risks or missing arguments,
and is this early discovery, building momentum, or crowded?
Best for deciding whether a ticker has real narrative momentum or just noise.
Research posts
Extract alpha from research
Use Buzzberg research posts from the last 24h.
Find the strongest new alpha ideas, second-order beneficiaries,
repeated evidence, weak assumptions, and tickers worth a deeper dive.
Quote short examples.
Uses posts tagged as research, not every tweet or every source item.
Stock lists
Turn stock lists into a watchlist
Use Buzzberg stock-list posts from the last 7 days.
Which tickers appear across multiple lists, what theme links them,
which are fresh vs crowded, and which 10 should I research next?
Good for turning author watchlists, baskets, and ranked lists into research candidates.
Portfolio updates
Track what authors changed
Use Buzzberg portfolio-update posts from the last 7 days.
What did speakers add, trim, close, or size up?
Separate actual portfolio moves from generic commentary.
Useful when the action matters more than the macro explanation.
24h Twitter/X
Top-speaker market TLDR
Use Buzzberg to give me today's top-speaker market brief.
What are the main themes, crowded trades, new tickers, and disagreements?
Quote examples.
Useful for finding what high-signal market accounts are suddenly talking about.
YouTube TLDRs
First and second-order effects
Use Buzzberg to find first-order and second-order effects from this week's
YouTube market discussions.
Which tickers benefit directly, which suppliers or competitors are second-order plays,
and what risks are speakers worried about?
Good after earnings, macro prints, or big AI-infrastructure moves.
Newsletters
Substack thesis extraction
Use Buzzberg to build a 7-day newsletter thesis map.
Show the strongest ticker narratives, key evidence, weak claims,
and what changed this week.
Separate hard data from vibes. Quote examples.
Turns long-form writing into a fast thesis map.
Narrative map
Why the market cares
Use Buzzberg to map the SIVE narrative.
Combine top-speaker trade ideas, YouTube TLDRs, newsletter TLDRs,
sentiment, and recent source snippets.
Separate catalysts, evidence, repeated claims, and open questions.
Turns Buzzberg's source layers into a research memo, not just a ticker table.
Leaderboards
Most buzzed tickers
Use Buzzberg to find the most mentioned tickers in the last 24h and 7d.
Which names are newly accelerating, which are already crowded,
and which have strong sentiment but low attention?
Useful for watchlist generation before the market opens.
Charts
Sentiment vs price
Use Buzzberg to build a 30d sentiment vs price read for NVDA.
Compare daily mentions, average sentiment, and price.
Does sentiment lead price, confirm the move, or lag after the move?
Good for spotting attention spikes, exhaustion, and narrative ignition.
Mentions history
Mindshare vs price
Use Buzzberg to build a 90d mentions vs price read for SIVE.
Show daily mention spikes, sentiment on those days, and price reaction.
Which days look like narrative ignition or narrative exhaustion?
Uses daily Buzzberg mention history, sentiment history, and cached closes.
Contrarian scan
Where smart speakers disagree
Use Buzzberg to scan for tickers with the biggest sentiment disagreement this week.
Show the bull camp, bear camp, strongest quotes, and what would prove each side wrong.
Finds volatile setups where the argument matters more than the headline.
Speaker history
How an author changed views
Use Buzzberg to show Serenity's all-time trade ideas with thesis.
Limit it to 100 ideas and keep at most 5 ideas per day.
Which tickers did she mention most, what was her first idea,
where did she flip direction, and how have her views changed?
Uses structured Buzzberg trade ideas, not raw tweet export.
Author x ticker
One speaker, one ticker
Use Buzzberg to analyze all trade ideas from Serenity about SIVE.
Show the first mention, latest mention, direction changes, thesis evolution,
and whether confidence increased or faded.
Good for understanding conviction before asking the agent for a chart.
First idea
Where a story started
Use Buzzberg to find Serenity's first recorded SIVE trade idea.
Use oldest-first speaker trade ideas with limit 1, then check recent SIVE ideas.
Did the thesis repeat, strengthen, or flip?
Useful for separating early discovery from late momentum.
Fresh alpha
Top-speaker idea radar
Use Buzzberg to find first/flip trade ideas from top-50 speakers over 24h and 7d.
Separate true new tickers from crowded repeats.
Which ideas deserve a deeper ticker read?
Fast path from market noise to a bounded research queue.
Keyword mining
Repeated words and hidden themes
Use Buzzberg Twitter data from top-50 speakers.
How many times did they mention "bottleneck", "power", "AI capex", and "memory"?
Quote examples and map each theme to tickers.
Useful when the trade is in the vocabulary before it is in the price.