Research a fast-moving topic across Reddit, X, YouTube, Hacker News, prediction markets, and the web, then synthesize a recency-weighted brief with confidence labels. Triggers on "what's the latest on X", "brief me on X", "what are people saying about X", cross-platform sentiment checks, and any request for a current-state research brief.
./install.sh recency-brief-researchname: recency-brief-research description: Research a fast-moving topic across Reddit, X, YouTube, Hacker News, prediction markets, and the web, then synthesize a recency-weighted brief with confidence labels. Triggers on "what's the latest on X", "brief me on X", "what are people saying about X", cross-platform sentiment checks, and any request for a current-state research brief.
Turn "what is happening with X right now" into a brief a reader can defend: every claim dated, sourced, and labeled with how much to trust it. The differentiator is the method, not the lane count: source triage, explicit recency weighting, and confidence labels applied from real research practice. Without those three, a multi-platform sweep is just a pile of links.
Write one concrete sentence for what the brief must answer. Note the topic's clock speed, because it sets the recency scale:
Pick a mode. Flash reads fewer pages and skips the refutation pass; Standard is the default; Deep adds a refutation query per key claim and a gaps section.
Cover all six lanes. Run the per-lane query for the topic, and record per-lane results before synthesizing. Verified access recipes live in references/platform-recipes.md.
| Lane | Route | What it is good for | |---|---|---| | Web | browser.search per facet, then open the pages | Primary docs, news, official statements | | Reddit | search engine site:reddit.com, sort=new; open threads in the browser | Practitioner experience, edge cases, sentiment | | X | search engine site:x.com; x.com/search in the browser | Fastest signal, announcements, rumor mill | | YouTube | search engine site:youtube.com; check upload date + channel | Demos, explainers, interviews | | HN | Algolia API: https://hn.algolia.com/api/v1/search?query=<q>&tags=story | Technical read, skepticism, primary comments | | Markets | Polymarket https://gamma-api.polymarket.com/public-search?q=<q>; Kalshi /trade-api/v2/events | What money believes; treat as bettor sentiment, not truth |
Never synthesize from snippets alone. Snippets pick which pages to open; opened pages supply the facts.
For every item you keep, record: platform, author type (official, journalist, practitioner, anonymous), evidence class (data, document, eyewitness, bare claim), date, and stance (neutral, opinion, promotional). Engagement (upvotes, likes, volume) is a weak signal only: it measures attention, not accuracy. One viral post is still one source.
Score each kept item: item_score = recency_weight x source_weight x independence_factor.
references/weighting.md. Fresh items dominate; stale items only supply background.Run the numbers with bin/recency_weight.py when the item list is long. Eyeball them when it is short. Either way, show the weights in the brief so the reader sees why a claim ranks where it does.
Every headline claim gets one label, using the criteria in references/weighting.md:
Tag the epistemic level too: FACT (verified from a primary source), INFERENCE (your reasoning, shown), OPINION (whose, and on what basis), RUMOR (unverified, spreading). Never present RUMOR as FACT.
Lead with the answer and its confidence, then the evidence. Reconcile numbers: agreement gets a consensus value; disagreement gets the range plus the spread's cause. State the strongest argument against your conclusion. List what you could not establish. Timestamp every probability and price from prediction markets; they move.
The brief must contain, in order:
publisher key 2e43c913833850e6d80f939677e3de76e806d47785c0f1caaca90f9d18c98e1e
No ratings yet — be the first to rate it.