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Help me understand why this metric changed. Data: {{data}} What else I know (releases, campaigns, tracking changes, seasons): {{context}} 1. Describe exactly what changed: which metric, how much, from when, and which segments moved and which did not. 2. Check measurement first: could tracking changes, bot traffic, definition changes, time zones or incomplete recent data explain it? 3. List up to four explanations, most likely first, each with the evidence for and against it from the data and context. 4. For each, the quickest check to confirm or rule it out, naming the cut of data or report to look at. 5. What I should do now, and what I should wait to decide until the checks are done. State as fact only what the data shows; label everything else as a hypothesis. Do not treat a correlation in timing as proof of cause, and do not assume figures, exchange rates, dates or user behaviour that the data and context do not give. Calculations from the data are fine if you show them.

Write launch copy for this product. Product and what it does: {{product}} Who it is for: {{audience}} Proof I can point to (users, results, quotes), if any: {{proof}} Write: 1. Product Hunt tagline, under 60 characters, saying what it does for whom. 2. Product Hunt description, under 260 characters. 3. Maker's first comment: why I built it, what it does differently, what it does not do yet, and one question for readers. 4. One post for X (under 280 characters) and one for LinkedIn (under 1,300 characters). Rules: plain words a customer would use; no hype words such as revolutionary, game-changing or seamless; no emoji walls. Use only the proof I gave; if I gave none, do not imply traction. Show each limit's character count.

Help me judge whether this study should change my decision. Study (abstract, excerpt or summary): {{study}} My decision and context: {{decision}} 1. The claim: what the study says it found, in one or two sentences, using its own measures. 2. The evidence: design (experiment, observational, survey…), who was studied, how many, for how long, and what was compared. Say what the text does not report. 3. Strength: what the design can and cannot show, especially cause versus correlation, and any obvious bias or conflict of interest in the text. 4. Fit: how similar the study's setting is to mine, and what differs. 5. For my decision: what it supports, what it does not, and what I should check or measure myself before relying on it. Use only what the text says; if something is not reported, say so instead of assuming it. Do not cite other studies unless I ask.