研究 App 趋势，但不让机器人写帖

Before the first analysis, ask me one round of setup questions covering:
- the app category to monitor;
- the relevant countries or languages;
- the sources you can genuinely access;
- the available product or business metrics;
- the frequency and date range of each analysis;
- the decision this research is supposed to inform.

Save those answers as the working scope. Never assume that a source has been consulted. If a source is unavailable, state that explicitly in every affected analysis.
Your role ends with the hypothesis and the test protocol. Do not write or publish content from the analysis unless I make a separate request.

Build the research pack for [CATEGORY], across [COUNTRIES/LANGUAGES], during [DATE RANGE].

Begin by listing the sources you consulted, the sources that were unavailable, and the limits of your visibility. Look for NEW items since the previous analysis, along with formats whose status has changed.

For every signal you keep, include:
- the date and a source link;
- the account, app, and market involved;
- the creative mechanism you observed;
- the metric that is genuinely available;
- whether the signal is isolated or repeated;
- its status: alive, fading, dead, or insufficient evidence.

Always separate views, downloads, revenue, and retention. Never infer conversion from views alone, and never turn one isolated post into proof of a market.

Evaluate four dimensions—traction, conversion, defensibility, and freshness—only when you can provide a source and a written justification. Use n/a whenever evidence is missing.

For the most promising mechanism, explain:

1. why it could convert rather than merely attract attention;
2. which alternative explanation could produce the same signal;
3. which piece of data would distinguish between the two interpretations.

End with ONE experiment for the following week: one hypothesis, one variable to change, and one signal that will determine whether the experiment worked.

Do not invent any number, app name, CPM, revenue figure, or score. If something cannot be verified, write “unsourced” or “n/a”.

Review this pack as a skeptical fact-checker.

Remove every number without a source, every app outside the date range, and every score without a justification. Clearly separate observations from inferences. If several hypotheses remain, keep only the one whose experiment would reduce the most uncertainty.