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OpenClaw

Claw1 Web Researcher

Web Research Assistant

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Installation

Suivez les instructions du dépôt pour votre agent. Consultez les fichiers et dépendances avant l’installation.

SkillHub CLI

skillhub install gpunter/claw1-web-researcher

Examinez la source et la compatibilité, puis suivez les étapes d’installation.

Donnez le lien à votre agent et demandez-lui d’examiner instructions et dépendances avant d’expliquer les étapes.

Voir la source ↗Guides

Instructions

Web Research Assistant

A structured web research skill for AI agents. Conduct market research, competitor analysis, trend monitoring, and content curation with organized, actionable output.

Built by CLAW-1 — because every agent needs good intel.

Commands

/research topic <query> [depth:quick|standard|deep]

Research a topic and return structured findings. Default depth is standard.

  • quick: 3-5 sources, key facts only, ~2 min
  • standard: 8-12 sources, analysis + insights, ~5 min
  • deep: 15-20 sources, comprehensive report with citations, ~10 min

Example: /research topic "AI agent monetization strategies" depth:deep

/research competitors <product_or_niche>

Find and analyze competitors in a niche. Returns: names, pricing, features, positioning, gaps.

Example: /research competitors "OpenClaw skills marketplace"

/research trends <industry_or_topic>

Identify current trends, emerging opportunities, and market signals.

Example: /research trends "autonomous AI agents 2026"

/research prices <product_type>

Research pricing for a product category. Returns: price ranges, common tiers, positioning advice.

Example: /research prices "AI prompt packs on Gumroad"

/research summarize <url>

Fetch and summarize a single URL into key points, facts, and actionable takeaways.

Example: /research summarize "https://example.com/article"

/research monitor <topic> [frequency:daily|weekly]

Set up a research brief on a topic. Returns a structured update each time it runs.

Example: /research monitor "ClawHub skill launches" frequency:daily

Output Format

All research commands return structured output:

## Research: [Topic]
**Depth**: [quick/standard/deep] | **Sources**: [count] | **Date**: [date]

### Key Findings
1. [Finding with source]
2. [Finding with source]

### Analysis
[Synthesis of findings, patterns, implications]

### Opportunities
- [Actionable opportunity 1]
- [Actionable opportunity 2]

### So...

Informations sur la source

Source
github
Repository
openclaw/skills
Path
skills/gpunter/claw1-web-researcher
Version
—
Commit
69cdf3a0277024cc24e7eca30a9e9823c34034d6
Source de classification
rules
Statut
active
Visibilité
public

Ces informations proviennent de l’analyse indexée et peuvent être anciennes. Vérifiez les fichiers actuels.

Contenu extrait

SKILL.md
# Web Research Assistant

A structured web research skill for AI agents. Conduct market research, competitor analysis, trend monitoring, and content curation with organized, actionable output.

Built by CLAW-1 — because every agent needs good intel.

## Commands

### `/research topic <query> [depth:quick|standard|deep]`
Research a topic and return structured findings. Default depth is `standard`.

- **quick**: 3-5 sources, key facts only, ~2 min
- **standard**: 8-12 sources, analysis + insights, ~5 min  
- **deep**: 15-20 sources, comprehensive report with citations, ~10 min

Example: `/research topic "AI agent monetization strategies" depth:deep`

### `/research competitors <product_or_niche>`
Find and analyze competitors in a niche. Returns: names, pricing, features, positioning, gaps.

Example: `/research competitors "OpenClaw skills marketplace"`

### `/research trends <industry_or_topic>`
Identify current trends, emerging opportunities, and market signals.

Example: `/research trends "autonomous AI agents 2026"`

### `/research prices <product_type>`
Research pricing for a product category. Returns: price ranges, common tiers, positioning advice.

Example: `/research prices "AI prompt packs on Gumroad"`

### `/research summarize <url>`
Fetch and summarize a single URL into key points, facts, and actionable takeaways.

Example: `/research summarize "https://example.com/article"`

### `/research monitor <topic> [frequency:daily|weekly]`
Set up a research brief on a topic. Returns a structured update each time it runs.

Example: `/research monitor "ClawHub skill launches" frequency:daily`

## Output Format

All research commands return structured output:

```
## Research: [Topic]
**Depth**: [quick/standard/deep] | **Sources**: [count] | **Date**: [date]

### Key Findings
1. [Finding with source]
2. [Finding with source]

### Analysis
[Synthesis of findings, patterns, implications]

### Opportunities
- [Actionable opportunity 1]
- [Actionable opportunity 2]

### So...

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