Getting it into your agent
One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.
npx skills add asoiso/trend-radar --skill trend-alertgit clone --depth 1 https://github.com/asoiso/trend-radarWrote this? Show the measurements
A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.
[](https://agentmods.dev/skills/asoiso/trend-radar/trend-alert)<a href="https://agentmods.dev/skills/asoiso/trend-radar/trend-alert"><img src="https://agentmods.dev/badge/skills/asoiso/trend-radar/trend-alert/github.svg" alt="Measured on agentmods" height="20"></a>Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.
<a href="https://agentmods.dev/skills/asoiso/trend-radar/trend-alert"><img src="https://agentmods.dev/badge/skills/asoiso/trend-radar/trend-alert.svg" alt="Reviewed on agentmods" width="80" height="20"></a>What it costs to keep this loaded
Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5.1 | $0.00087 | $0.02367 |
| Opus 5 | $0.00044 | $0.01184 |
| Sonnet 5 | $0.00017 | $0.00473 |
| Haiku 4.5 | $0.00009 | $0.00237 |
Grade A, and why
trend-alert scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 12d ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
How it starts
The opening of the file, as written. The whole thing — 160 lines — stays where its author put it; the contents beside it link to each section on GitHub.
trend-alert
Anomaly detection on a watchlist of topics, with channel-correct push delivery via the trendradar MCP. Each spike is verified, formatted per channel, and rate-limited before being sent.
When to activate
Trigger when the user expresses any of:
- 异动告警 / 突发热点推送 / breakout alert
- 监控 XX 话题 / 订阅热点 / 盯盘 / 关注列表
- 推送到飞书 / 钉钉 / Telegram / Slack / Bark / 邮件 / ntfy / 企业微信 / webhook
- "ping me when X spikes" / "alert me if X breaks out" / "通知我 X 暴涨"
Do NOT activate for routine "show me trends" or recap requests — those belong to trend-monitor or trend-report.
Workflow
-
Resolve watchlist. Take topics from the user message. If they reference a stored list ("我的关注列表"), look in shared memory; otherwise ask once for the explicit topics. Normalize to a deduped list of strings.
-
Detect anomalies per topic. For each topic in the watchlist call:
mcp__trendradar__analyze_topic_trend( topic="<topic>", analysis_type="viral", spike_threshold=3.0, time_window=24 )Run these calls in parallel where possible.
-
Filter to real spikes. Keep only topics whose response indicates a genuine spike (e.g.
is_spike=true,viral_scoreabove threshold, or explicitspike_detected). Discard noise. If nothing spikes, tell the user "无异动" and stop — do NOT push an empty alert. -
Discover configured channels.
mcp__trendradar__get_notification_channels()Use the returned
channels[]to know whichids haveconfigured: true. If the user named a channel that is not configured, surface the missing env var keys (see Edge cases) and skip that channel. -
Per channel: fetch format rules, format, send. For each target channel
<id>:mcp__trendradar__get_channel_format_guide(channel="<id>")Use the
guide.supported/guide.unsupported/guide.promptfields to format the message body. Then:mcp__trendradar__send_notification( channel="<id>", title="【异动】<topic>", content="<formatted body>" )
What this file has done since we first saw it
Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.
- 12d ago First seen · 160 lines · 87 tokens per session scan A 381633abef19
trend-alert is a skill published in the GitHub repository asoiso/trend-radar (2 stars, last pushed 4mo ago), licensed Apache-2.0. It adds 87 tokens to every session and 2,367 once invoked, about $0.0004 per session on Opus 5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-31.
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