Creator Search Intent Radar
/install creator-search-intent-radar
Creator Search Intent Radar
Skill Card
- Category: Market Intelligence
- Core problem: What should we post next with real demand signals?
- Best for: Weekly planning and topic prioritization
- Expected input: TikTok/YouTube/Instagram trend snippets, search hints, comments/DM FAQs
- Expected output: Ranked topic backlog + platform fit + hook directions + CTA
- Creatop handoff: Send top 3 topics into Creatop script workflow
Overview
Turn noisy trend inputs into ranked, publishable decisions.
Priority order:
- demand signal quality
- audience fit
- monetization fit
- execution speed
Workflow
1) Collect demand signals
Gather 10–30 candidate signals from:
- TikTok search/trend surfaces
- YouTube search/autosuggest
- Instagram/Reels momentum
- comments/DM FAQs/community threads
Record provenance for each signal:
source_type(official/community/internal)source_link(if available)captured_atconfidence(high/medium/low)
If live endpoints are unavailable, run fallback mode using recent internal patterns and clearly label output as mode: fallback.
2) Normalize and dedupe backlog
For each topic, standardize:
topicplatform_fit(TikTok / YouTube / Instagram)intent_type(learn / compare / buy / troubleshoot / inspiration)freshness(hot / warm / evergreen)audience_fit(1–5)monetization_fit(1–5)difficulty(1–5)
Merge near-duplicate topics before scoring.
3) Score and rank
Use:
priority_score = (audience_fit * 0.35) + (freshness_score * 0.25) + (monetization_fit * 0.25) + (execution_speed * 0.15)
Mapping:
freshness_score: hot=5, warm=3, evergreen=2execution_speed = 6 - difficulty
4) Generate decision output
Return:
- Top 10 ranked topics
- Per topic: 1 content angle + 3 hook directions + CTA
- 7-day lightweight schedule
Include data_confidence for each topic (high/medium/low).
Output format
- Topic:
- Why now:
- Platform:
- Intent:
- Angle:
- Hook directions (3):
- CTA:
- Confidence:
Quality and safety rules
- Do not present synthetic/internal signals as live external trends.
- Avoid generic topics without clear buyer intent.
- Keep recommendations executable by small creator teams.
License
Copyright (c) 2026 Razestar.
This skill is provided under CC BY-NC-SA 4.0 for non-commercial use. You may reuse and adapt it with attribution to Razestar, and share derivatives under the same license.
Commercial use requires a separate paid commercial license from Razestar. No trademark rights are granted.
- 确保已安装 OpenClaw(本地或 Docker 部署)
- 在对话框中输入安装命令:
/install creator-search-intent-radar - 安装完成后,直接呼叫该 Skill 的名称或使用
/creator-search-intent-radar触发 - 根据 Skill 的参数说明提供必要输入,即可获得结构化输出
Creator Search Intent Radar 是什么?
Convert TikTok/YouTube/Instagram search and trend signals into a prioritized weekly content backlog with script angles and hook directions. Use when the user... 它是一个面向 Claude Code / OpenClaw 的 AI Agent Skill 插件,目前累计下载 302 次。
如何安装 Creator Search Intent Radar?
在 OpenClaw 或 Claude Code 对话框中运行命令「/install creator-search-intent-radar」即可一键安装,无需额外配置。
Creator Search Intent Radar 是免费的吗?
是的,Creator Search Intent Radar 完全免费,采用 MIT-0 许可证,可自由下载、安装和使用。
Creator Search Intent Radar 支持哪些平台?
Creator Search Intent Radar 跨平台运行,可在任意部署了 OpenClaw / Claude Code 的环境中使用(cross-platform)。
谁开发了 Creator Search Intent Radar?
由 LeroyCreates(@leooooooow)开发并维护,当前版本 v1.0.3。