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Demand Signals

作者 LeroyCreates · GitHub ↗ · v1.0.0 · MIT-0
cross-platform ✓ 安全检测通过
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在 OpenClaw 中安装
/install demand-signals
功能描述
Identify emerging product categories and consumer demand signals from TikTok comments, search trends, and creator activity before they peak.
使用说明 (SKILL.md)

Demand Signals

The window between "this is starting to trend" and "every seller is already stocked and competing on price" is often just four to eight weeks on TikTok. Most sellers discover trends after they have peaked — when the hashtag is saturated, the suppliers have raised prices, and the organic opportunity has collapsed. This skill helps ecommerce operators read early demand signals — from comment sentiment in viral videos, to accelerating hashtag use, to creator content shifts — and translate those signals into sourcing and listing decisions before a trend reaches saturation. The goal is to give sellers a structural advantage by turning observable platform behavior into inventory and content decisions weeks ahead of peak demand.

Use when

  • You are actively scanning TikTok for the next breakout product in your category and want a structured framework for evaluating whether a product appearing repeatedly in your For You Page represents a genuine emerging demand trend or a short-lived creator spike that will not translate into sustained commercial sales volume on TikTok Shop.
  • You have noticed a surge of creator content around a specific problem, aesthetic, lifestyle moment, or seasonal use case and want to assess whether this represents a real buyer demand signal or merely creator-to-creator content mimicry without meaningful purchase intent behind the views and comments.
  • Your sourcing team needs a structured brief to send to suppliers, and you want to translate TikTok trend observations — like a specific ingredient going viral in skincare, or a product format being requested across hundreds of comment sections — into product specifications and order timing windows before competitors act.
  • A product category you operate in has slowed down and you need to identify adjacent or emerging sub-categories that are currently building momentum on TikTok and could serve as your next logical product expansion without requiring a full pivot in supplier relationships.

What this skill does

This skill takes trend observation inputs — such as a description of viral video behavior, a hashtag cluster that has been accelerating in use, a recurring comment request pattern, or a creator content shift you have noticed — and evaluates them against a structured demand signal framework. It assesses signal strength by distinguishing between one-off curiosity spikes and sustained behavioral patterns across multiple creators and comment sections. It evaluates commercial intent by examining whether viewers are asking where to buy, sharing personal need contexts, or simply watching for entertainment. It estimates competitive saturation by gauging how many sellers appear to already be active in the space. Finally, it assesses timing viability by comparing the apparent trend lifecycle stage against typical TikTok trend trajectories so sellers can judge whether they are genuinely early or already late. The output helps sellers make a clear go, monitor, or skip decision with supporting reasoning rather than acting on gut feel alone.

Inputs required

  • Trend observation (required): A specific description of what you are seeing on TikTok, e.g., "Videos about silent walking have been appearing daily in my For You Page for three weeks, with commenters repeatedly asking which shoes and insoles the creators are using" or "The hashtag #glacierskincare has tripled in post volume over the last two weeks and appears in both creator and buyer content." The more concrete the observation, the more precise the signal assessment.
  • Your current product category (required): The category you sell in or are considering entering, e.g., "women's activewear accessories" or "home organization and storage products." This context helps calibrate whether the trend represents a natural extension of your existing catalog or a significant market pivot requiring new supplier relationships.
  • Sourcing lead time (optional): How long it takes you to source and receive new inventory from your typical suppliers, e.g., "45 days from order placement to warehouse receipt." This allows the skill to factor timing viability directly into the go or monitor recommendation.

Output format

The output is organized into five clearly structured parts. First, a Signal Summary written in two to three sentences describing the trend observation and explaining why it registers as potentially commercially significant rather than a content-only phenomenon. Second, a Signal Strength Assessment that scores the trend across four dimensions — Volume and Reach, Commercial Intent, Competitive Saturation, and Timing Window — with each dimension rated Low, Medium, or High and accompanied by a one-sentence rationale explaining the score. Third, a Go, Monitor, or Skip recommendation with clear reasoning tied directly to the dimension scores rather than a generic judgment. Fourth, if the recommendation is Go or Monitor, a Product Positioning Brief covering the target buyer profile, the primary benefit angle most resonant with the trend's emotional driver, and a suggested content hook for your first three to five videos. Fifth, a Sourcing and Timing Window note advising when to place supplier orders and when to expect the peak sales window if the trend continues on its current trajectory, adjusted for the lead time provided.

Scope

  • Designed for: TikTok Shop sellers, ecommerce operators, product sourcing teams, brand strategists, category managers
  • Platform context: TikTok Shop (primary); demand signals identified may also apply to Shopee, Instagram Shopping, and Amazon with category-specific adjustments
  • Language: English

Limitations

  • This skill cannot access live TikTok search volume data, platform analytics dashboards, or creator performance metrics; all signal evaluation is based on qualitative pattern analysis of user-provided observations and general TikTok trend lifecycle knowledge.
  • Trend timing predictions are estimates calibrated against typical TikTok trend lifecycle patterns and may be significantly inaccurate for unusual demand spikes driven by news events, celebrity endorsements, or geopolitical factors outside the platform's normal content dynamics.
  • This skill does not provide supplier contacts, manufacturing cost benchmarks, or logistics recommendations; it focuses exclusively on demand signal evaluation and go-to-market timing so that sourcing decisions can be made with clearer demand confidence before committing capital.
安全使用建议
This skill is a passive analysis framework that relies on you to paste or describe what you see; it does not fetch TikTok data or require credentials. Before installing or using it, consider: (1) do not paste any private customer data, account tokens, or supplier secrets into the inputs; (2) if you want the agent to run automated scraping or connect to TikTok in future versions, require explicit credentials and verify the install spec and data-handling details; (3) review any update that adds an install step, network calls, or requests for keys — those would materially change the security posture; and (4) if you prefer to avoid autonomous runs, change the skill invocation settings in your agent to require explicit user invocation.
功能分析
Type: OpenClaw Skill Name: demand-signals Version: 1.0.0 The skill bundle consists solely of metadata and a markdown file (SKILL.md) providing a conceptual framework for analyzing TikTok ecommerce trends. It contains no executable code, network requests, or instructions that could lead to data exfiltration or unauthorized system access.
能力评估
Purpose & Capability
The name and description promise a framework for evaluating TikTok-derived demand signals; the skill's instructions request exactly the kind of user-provided inputs (trend observation, product category, optional lead time) needed to perform that analysis. No unrelated capabilities or credentials are requested.
Instruction Scope
SKILL.md describes a bounded runtime behaviour: accept explicit user observations, evaluate them against a signal-framework, and produce a five-part structured output. It explicitly notes it cannot access live TikTok analytics and does not instruct reading local files, fetching external data, or contacting third-party endpoints.
Install Mechanism
There is no install spec and no code files — the skill is instruction-only, so nothing will be written to disk or pulled from external URLs. This is the lowest-risk install profile.
Credentials
The skill requires no environment variables, credentials, or config paths. That aligns with its stated purpose of analyzing user-supplied observations rather than querying protected APIs or performing authenticated scraping.
Persistence & Privilege
The skill is not forced-always, and uses the platform-default model invocation behavior. It does not request persistent system-level privileges or modifications to other skills. Autonomous invocation is allowed by default but is not combined with other concerning privileges here.
如何使用
  1. 确保已安装 OpenClaw(本地或 Docker 部署)
  2. 在对话框中输入安装命令:/install demand-signals
  3. 安装完成后,直接呼叫该 Skill 的名称或使用 /demand-signals 触发
  4. 根据 Skill 的参数说明提供必要输入,即可获得结构化输出
版本历史
v1.0.0
Initial release.
元数据
Slug demand-signals
版本 1.0.0
许可证 MIT-0
累计安装 0
当前安装数 0
历史版本数 1
常见问题

Demand Signals 是什么?

Identify emerging product categories and consumer demand signals from TikTok comments, search trends, and creator activity before they peak. 它是一个面向 Claude Code / OpenClaw 的 AI Agent Skill 插件,目前累计下载 135 次。

如何安装 Demand Signals?

在 OpenClaw 或 Claude Code 对话框中运行命令「/install demand-signals」即可一键安装,无需额外配置。

Demand Signals 是免费的吗?

是的,Demand Signals 完全免费,采用 MIT-0 许可证,可自由下载、安装和使用。

Demand Signals 支持哪些平台?

Demand Signals 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 Demand Signals?

由 LeroyCreates(@leooooooow)开发并维护,当前版本 v1.0.0。

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