x-collect
Collect and research materials for X (Twitter) content creation using multi-round web search strategy. Use when user wants to gather trending topics, research subjects for X posts, or mentions "collect materials", "research topic", "find content for X", "x-collect". Performs 4-round deep research mimicking human research workflow.
Best use case
x-collect is best used when you need a repeatable AI agent workflow instead of a one-off prompt.
Collect and research materials for X (Twitter) content creation using multi-round web search strategy. Use when user wants to gather trending topics, research subjects for X posts, or mentions "collect materials", "research topic", "find content for X", "x-collect". Performs 4-round deep research mimicking human research workflow.
Teams using x-collect should expect a more consistent output, faster repeated execution, less prompt rewriting.
When to use this skill
- You want a reusable workflow that can be run more than once with consistent structure.
When not to use this skill
- You only need a quick one-off answer and do not need a reusable workflow.
- You cannot install or maintain the underlying files, dependencies, or repository context.
Installation
Claude Code / Cursor / Codex
Manual Installation
- Download SKILL.md from GitHub
- Place it in
.claude/skills/x-collect/SKILL.mdinside your project - Restart your AI agent — it will auto-discover the skill
How x-collect Compares
| Feature / Agent | x-collect | Standard Approach |
|---|---|---|
| Platform Support | Not specified | Limited / Varies |
| Context Awareness | High | Baseline |
| Installation Complexity | Unknown | N/A |
Frequently Asked Questions
What does this skill do?
Collect and research materials for X (Twitter) content creation using multi-round web search strategy. Use when user wants to gather trending topics, research subjects for X posts, or mentions "collect materials", "research topic", "find content for X", "x-collect". Performs 4-round deep research mimicking human research workflow.
Where can I find the source code?
You can find the source code on GitHub using the link provided at the top of the page.
Related Guides
SKILL.md Source
# X Collect
Collect trending topics and research materials for X content creation using a systematic 4-round web search strategy.
## Prerequisites
- WebSearch tool available
- Internet connection
## Optional State (ContextStore)
If available, leverage user preference state to improve search quality:
- State dir: `~/.claude/skills/x-create/state/`
- Positive samples: `liked_topics.json` (preferred topics/entities/sources)
- Negative samples: `rejected_topics.json` (avoid low-value/repetitive topics)
If state files don't exist, proceed normally.
## Workflow
### Input
User provides:
- **Topic** (required): The subject to research (e.g., "AI Agent最新进展", "Claude 4 发布")
- **Language** (optional): Output language, defaults to Chinese (zh-CN)
### 4-Round Search Strategy
Simulate human research thinking process with progressive depth.
**Query expansion rules (lightweight):**
- Start with user `topic`
- Add 2-5 query variants based on:
- **User profile** (domains/persona if known)
- **liked_topics.json** high-frequency keywords/entities (if available)
- Keep ~20% queries as **exploration** (cross-domain / adjacent keywords) to avoid information bubble
**Dedup & clustering (at the end of each round):**
- Merge near-duplicate URLs/titles
- Group materials into topic clusters (rough tags are fine)
**Round 1: Official Sources (权威信息)**
```
Search: "{topic} 官方文档"
Search: "{topic} GitHub"
Search: "{topic} official announcement"
```
Goal: Get authoritative first-hand information
**Round 2: Technical Analysis (技术解析)**
```
Search: "{topic} 详细介绍"
Search: "{topic} 教程 tutorial"
Search: "{topic} how it works"
```
Goal: Understand technical details and mechanisms
**Round 3: Comparison & Reviews (对比评测)**
```
Search: "{topic} vs {competitor}"
Search: "{topic} 评测 review"
Search: "{topic} pros cons"
```
Goal: Get different perspectives and comparisons
**Round 4: Supplementary Verification (补充验证)**
```
# Analyze gaps from previous rounds
missing_info = analyze_gaps(previous_results)
Search: "{missing_info}"
Search: "{topic} 最新 latest 2024 2025"
```
Goal: Fill information gaps and get latest updates
### Output Format
Generate structured material document:
```markdown
# {Topic} 素材收集报告
## 收集时间
{timestamp}
## 核心信息
- **官方定义**: ...
- **关键特性**: ...
- **最新动态**: ...
## 素材列表
### 素材 1
- **标题**: ...
- **来源**: {url}
- **摘要**: 2-3句话概括
- **关键点**:
- 要点1
- 要点2
- **潜在选题角度**: ...
- **推荐推文类型**: [高价值干货/犀利观点/热点评论/故事洞察/技术解析]
- **QualityScore (0-10)**: ...
- **TopicCluster**: ...
- **HookCandidates**:
- ...
### 素材 2
...
## 热度分析
- **当前热度**: 高/中/低
- **趋势**: 上升/稳定/下降
- **讨论焦点**: ...
## 争议点
- 争议1: ...
- 争议2: ...
## 下一步建议
使用 `/x-filter` 对素材进行打分筛选
```
Additionally, append a machine-readable block for hooks/state ingestion:
```json
MATERIALS_JSON
{
"schema_version": "x_skills.materials.v1",
"topic": "{Topic}",
"timestamp": "{timestamp}",
"items": [
{
"title": "...",
"url": "...",
"summary": "...",
"key_points": ["..."],
"quality_score_0_10": 0,
"topic_cluster": "...",
"hook_candidates": ["..."]
}
]
}
```
## Execution Steps
1. **Receive topic** from user
2. **Execute Round 1** searches (official sources)
3. **Execute Round 2** searches (technical analysis)
4. **Execute Round 3** searches (comparisons)
5. **Analyze gaps** from rounds 1-3
6. **Execute Round 4** searches (fill gaps)
7. **Synthesize results** into structured format
8. **Output MATERIALS_JSON** (for hooks/state ingestion)
9. **(Optional) Append event** for feedback loop:
- `python ~/.claude/skills/x-create/scripts/x_state.py event --event collect.completed --payload-json '{"topic":"...","items_count":12,"explore_ratio":0.2}'`
10. **Report summary** to user
## Example
User: `/x-collect Claude MCP协议`
Expected behavior:
1. Search "Claude MCP协议 官方文档"
2. Search "MCP Model Context Protocol GitHub"
3. Search "MCP协议 详细介绍"
4. Search "MCP协议 教程"
5. Search "MCP vs function calling"
6. Search "MCP协议 评测"
7. Identify gaps: need more about security, adoption rate
8. Search "MCP协议 安全性"
9. Search "MCP协议 最新 2025"
10. Generate structured material report
## Integration
After collection, suggest:
```
素材收集完成!共找到 X 条相关素材。
下一步:运行 /x-filter 对素材进行打分筛选,≥7分的选题将进入创作池。
```
## Tips
- For trending topics, prioritize recency (2024-2025)
- For technical topics, prioritize official docs and GitHub
- For controversial topics, collect multiple perspectives
- Always note the source URL for credibilityRelated Skills
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