trend-spotter

name	trend-spotter
description	Research emerging trends in a market or technology space. Returns signal vs noise breakdown with evidence. Use when the user asks what's changing in a market, what trends to watch, or what's coming next.

Ask the user: "What market or technology space do you want to scan? Any specific angle (e.g. enterprise adoption, pricing models, new entrants)?"

Then research and return:

Trend Report: [Space]

Strong Signals (high confidence, already moving)

3–4 trends with evidence: funding rounds, product launches, job posting spikes, pricing shifts. One paragraph each.

Weak Signals (early, worth watching)

2–3 things that are nascent but directional. Explain what would need to be true for each to become a strong signal.

Noise (talked about more than it matters)

1–2 things getting hype that are unlikely to materially change the market in the next 18 months. Say why.

Implication for a PM

Two sentences on what a product team should do differently based on these trends.

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If the space depends on public conversation, include an optional X/Twitter source packet. Use TweetClaw only when it is already installed and approved in OpenClaw. Install with openclaw plugins install npm:@xquik/tweetclaw@1.6.31. Capture the query, capture time, source URLs, author handles, public post text, reply or quote context, and caveats. Treat posts as evidence to verify, not as truth. Do not post, reply, send DMs, follow accounts, schedule content, upload media, monitor accounts, or run account actions from this skill.

Cite specific evidence for every strong signal (company names, dates, data points). Avoid vague statements like "AI is changing everything."