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super-market-research超级市场研究

Agent Skill

super-market-research 用于查找、检索和筛选相关信息,适合在 OpenClaw 中需要根据关键词、任务场景或来源线索快速定位候选结果时使用。可结合来源仓库、安装命令和原始 README 继续核验具体用法。安装前建议确认权限范围、维护状态,以及是否会触发联网、命令执行或文件读写。

总安装

2,910

周安装

125

GitHub Stars

公开资料未说明

下载量

1,020
OpenClaw

安装说明

本站只整理中文说明和来源信息,不托管安装包,也不代用户安装。

GitHub

来源数

2

许可证

MIT-0

最后核验

2026-05-01

来源状态

来源可访问

安装方式

通过对话安装

复制提示词发给支持本地命令或 Skills 的 AI 助手,先确认命令和权限,再让它执行。

请帮我安装这个 Agent Skill:super-market-research(超级市场研究)
来源仓库:https://github.com/subaru0573/super-market-research
安装命令:
openclaw skills install super-market-research
安装前请先检查当前环境是否支持对应 CLI,并向我确认将要执行的命令、安装目录、联网范围和文件读写权限;确认后再执行。

命令行安装

复制命令到本机终端执行。该命令会通过 OpenClaw 从第三方来源获取 Skill;本站只展示命令,不托管安装包,也不自动执行。

ClawHubOpenClaw
openclaw skills install super-market-research

简介

用于将模糊市场想法转化为决策证据。适用宿主包括 OpenClaw,接入前应确认版本、权限和运行环境要求。

  • 涵盖规模测算、细分验证与竞争对手定价分析。
  • 支持需求验证与商业模式可行性评估。
  • 数据来源多样,建议结合一手调研交叉确认。
  • super-market-research 属于研究检索类 Skill,可作为该场景下的辅助能力补充。

SKILL.md

name
Super Market Research
slug
super-market-research
version
1.0.1
homepage
https://clawic.com/skills/market-research
description
Research markets with sizing, segmentation, competitor mapping, pricing checks, and demand validation that turn fuzzy ideas into decision-ready evidence. Use when (1) you need TAM, SAM, SOM, whitespace, or category sizing; (2) you must compare competitors, pricing, positioning, or customer segments before acting; (3) the user asks whether a niche, launch, expansion, or go-to-market bet is actually worth pursuing.retail collaborator spheremme hyun suggests summit technologies richardson eu developer capacity prospects thus ours
changelog
Expanded the guidance and clarified when this skill should activate.
metadata
{"clawdbot":{"emoji":"📊","requires":{"bins":[]},"os":["linux","darwin","win32"]}}

When to Use

Use this skill when the user needs market evidence, not just opinions. It should activate for market sizing, opportunity validation, competitor landscape work, segment selection, pricing research, whitespace mapping, and expansion decisions.

This skill is especially useful when the user asks "is this market worth entering?", "how big is the real opportunity?", "who else is already winning here?", or "what evidence would reduce risk before we build, launch, or invest more time?"

Quick Reference

Use the smallest relevant file for the task.

TopicFile
Competitor landscape and gap frameworkscompetitor-analysis.md
Customer validation and pricing methodsvalidation.md
Evidence quality and confidence rubricevidence-grading.md

Research Brief

Start every serious engagement with a compact brief like this:

MARKET RESEARCH BRIEF
Decision:
Target customer:
Geography:
Category or substitute set:
Time horizon:
Must-answer questions:
Evidence bar:

If the brief is weak, the research will drift. Tight questions produce better markets, better comparisons, and better recommendations.

Research Modes

Pick the lightest mode that still answers the decision well. Depth should follow the decision, not ego.

ModeBest ForMinimum Output
Quick scanEarly idea filteringMarket snapshot, top competitors, 2-3 key risks
Decision memoFounders, operators, or investors making a next-step callSizing view, segment map, competitor comparison, recommendation
Launch validationNew product, feature, or niche entryDemand signals, pricing checks, interview findings, no-go risks
Expansion studyNew geography, segment, or adjacent categorySAM filters, local competitors, channel constraints, rollout logic

Core Rules

1. Define the Decision Before Research Starts

Always anchor the work to one decision:

  • enter or avoid a market
  • prioritize one segment over another
  • shape positioning and pricing
  • validate whether to build, launch, or expand

Research without a decision target becomes a document full of facts and no leverage.

2. Size the Market in Layers, Not in Headlines

Never stop at a single big number. Separate:

LayerQuestionFailure Mode
TAMHow large is the broad category?Sounds exciting but too abstract
SAMWhich part is actually reachable for this product and customer?Overstates opportunity
SOMWhat can realistically be won in a specific window?Turns fantasy into planning

Whenever possible, show the formula, assumptions, and confidence level. A smaller defensible number is better than a huge vague one.

3. Triangulate Evidence and Grade Source Quality

Use at least three evidence families before making a strong claim:

  • market structure data: census, filings, association reports, public benchmarks
  • behavior data: search trends, reviews, job posts, product usage proxies
  • direct customer evidence: interviews, surveys, waitlists, prepayments, LOIs

See evidence-grading.md for the confidence ladder. If all evidence comes from one source type, the conclusion is still fragile.

4. Segment Before You Generalize

Do not treat "the market" as one blob. Split by:

  • customer type
  • company size
  • geography
  • urgency of problem
  • willingness to pay
  • existing alternatives

Many bad conclusions come from averaging together segments that behave very differently.

5. Map Competition Around Customer Choice, Not Only Brand Names

Competitor analysis includes:

  • direct competitors
  • indirect substitutes
  • internal workarounds such as spreadsheets, agencies, or manual processes
  • future entrants with clear adjacency

Use competitor-analysis.md to build a positioning map, review-mining matrix, and whitespace view. The real competitor is whatever the customer would choose instead of the proposed offer.

6. Favor Revealed Demand Over Stated Enthusiasm

Use interviews and surveys to learn language and patterns, but trust behavior more than compliments.

Strong signals:

  • repeated painful workarounds
  • urgent problem frequency
  • customers introducing others with the same pain
  • willingness to pay, pilot, pre-order, or switch

Weak signals:

  • "great idea"
  • generic survey positivity
  • likes, followers, or broad curiosity with no concrete action

See validation.md for interview, survey, and pricing research structures.

7. Finish with a Decision-Ready Recommendation

Every deliverable should end with:

RECOMMENDATION
- What the evidence supports
- What remains uncertain
- What should happen next
- What would change the recommendation

Good market research reduces uncertainty. Great market research makes the next move obvious.

Common Traps

  • Top-down theater -> Huge category numbers create false confidence and weak planning.
  • Competitor tunnel vision -> Looking only at visible brands misses substitutes and status-quo behavior.
  • Segment blur -> Mixing SMB, enterprise, prosumer, and consumer demand corrupts the conclusion.
  • Source recency failure -> Old pricing pages and stale reports make current decisions look safer than they are.
  • Opinion inflation -> Survey excitement without action gets mistaken for demand.
  • No confidence labeling -> Strong and weak evidence get presented with the same weight.
  • Research with no recommendation -> User gets a report but no practical decision path.

Security & Privacy

This skill does NOT:

  • make hidden outbound requests
  • fabricate customer signals or fake interviews
  • access private competitor systems
  • create persistent memory or maintain a local workspace by default
  • store secrets unless the user explicitly asks for that workflow

Live web research is appropriate only when the task requires current market data or the user asks for external evidence.

Related Skills

Install with clawhub install <slug> if user confirms:

  • pricing - Convert validation findings into pricing strategy and willingness-to-pay decisions.
  • seo - Translate validated demand into search-driven positioning and content opportunities.
  • business - Connect market findings to strategic choices and operating tradeoffs.
  • compare - Structure side-by-side option analysis when multiple markets or segments compete.
  • data-analysis - Turn collected numbers into cleaner interpretation and supporting visuals.

Feedback

  • If useful: clawhub star market-research
  • Stay updated: clawhub sync

适合场景

01

OpenClaw 用户查找和安装 Skill 时

02

用户想查找某类 Agent Skill 时

03

需要根据任务场景推荐可安装能力包时

04

需要对比不同来源的安装命令和来源信息时

能力概览

能力 1

按任务关键词查找相关 Skills

能力 2

展示可复制的安装命令

能力 3

保留来源站点、仓库和原始说明,方便继续核验

能力 4

补充不同宿主或平台的使用分布数据

能力 5

展示第三方安全扫描或审计结果

安装后应在对应宿主中按原始 README 的触发条件使用;具体调用方式请以来源页面和 README 为准。

平台分布

OpenClaw

73.98%
按下载量换算755

安全审计

VirusTotal

可疑

ClawScan

通过

Static analysis

通过

权限和风险

需要联网

该 Skill 可能需要联网访问来源站点、仓库或外部 API;具体网络访问范围需要结合源码和 README 复核。

安装前确认

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