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Tweet Processor

Tweet Processor Skill

caqlayan0 installations selon la source☆ 0 Étoiles du dépôt

Installation

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

SkillHub CLI

skillhub install caqlayan/tweet-processor

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

Tweet Processor Skill

Extract and categorize insights from tweet links into structured notes.

Usage

When user sends a tweet URL, automatically:

  1. Navigate to the tweet
  2. Extract key insights (tools, tech, people, learnings)
  3. Categorize into tweet-notes/ files
  4. Append with proper formatting

Input

  • Tweet URL (any x.com or twitter.com link)

Output

Appends to:

  • tweet-notes/tools.md — Software, services, APIs discovered
  • tweet-notes/tech.md — Development techniques, workflows
  • tweet-notes/design.md — UI/UX insights
  • tweet-notes/people.md — Accounts to follow
  • tweet-notes/misc.md — Other valuable insights

Format

## [Brief Title]
**Date:** YYYY-MM-DD
**URL:** [tweet URL]
**Key takeaway:** [What matters]
**Why it matters:** [Brief context]

---

Rules

  • Be selective — only genuinely useful insights
  • Skip fluff and noise
  • One insight can go into multiple files if relevant
  • Always include the source URL
  • Use today's date

Informations sur la source

Source
github
Repository
openclaw/skills
Path
skills/caqlayan/tweet-processor
Version
—
Commit
b7789b6a14bba9ddcde6f7d2a36cc93211f61aa7
Source de classification
rules
Statut
active
Visibilité
public

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

README

Tweet Processor Skill

Automated tweet analysis and categorization for the tweet-notes system.

What It Does

When you send a tweet link to the agent with this skill active, it will:

  1. Navigate to the tweet using browser automation
  2. Extract key insights (tools, techniques, people, learnings)
  3. Categorize into appropriate files:
    • tools.md — Software, APIs, services
    • tech.md — Development techniques, workflows
    • design.md — UI/UX insights
    • people.md — Worthwhile accounts
    • misc.md — Other valuable insights
  4. Append with consistent formatting including date and URL

How to Use

Simply send a tweet URL:

https://x.com/username/status/1234567890

The agent will automatically:

  • Detect it's a tweet link
  • Navigate and extract content
  • Categorize insights
  • Update the files
  • Report what was added

Output Format

Each entry follows this structure:

## [Brief Descriptive Title]
**Date:** 2025-02-20
**URL:** https://x.com/...
**Key takeaway:** [The core insight or tool/technique]
**Why it matters:** [Context on why this is valuable]

---

Files Managed

  • /tweet-notes/tools.md — Tools and services discovered
  • /tweet-notes/tech.md — Technical insights and workflows
  • /tweet-notes/design.md — Design resources and patterns
  • /tweet-notes/people.md — Accounts to follow
  • /tweet-notes/misc.md — Everything else

Philosophy

  • Be selective — Only capture genuinely useful insights
  • Skip the fluff — Ignore hype and noise
  • Actionable > Interesting — Focus on things that can be used
  • Link everything — Always include source URLs

Contenu extrait

SKILL.md
# Tweet Processor Skill

Extract and categorize insights from tweet links into structured notes.

## Usage

When user sends a tweet URL, automatically:
1. Navigate to the tweet
2. Extract key insights (tools, tech, people, learnings)
3. Categorize into tweet-notes/ files
4. Append with proper formatting

## Input

- Tweet URL (any x.com or twitter.com link)

## Output

Appends to:
- `tweet-notes/tools.md` — Software, services, APIs discovered
- `tweet-notes/tech.md` — Development techniques, workflows
- `tweet-notes/design.md` — UI/UX insights
- `tweet-notes/people.md` — Accounts to follow
- `tweet-notes/misc.md` — Other valuable insights

## Format

```markdown
## [Brief Title]
**Date:** YYYY-MM-DD
**URL:** [tweet URL]
**Key takeaway:** [What matters]
**Why it matters:** [Brief context]

---
```

## Rules

- Be selective — only genuinely useful insights
- Skip fluff and noise
- One insight can go into multiple files if relevant
- Always include the source URL
- Use today's date
README
# Tweet Processor Skill

Automated tweet analysis and categorization for the tweet-notes system.

## What It Does

When you send a tweet link to the agent with this skill active, it will:

1. **Navigate** to the tweet using browser automation
2. **Extract** key insights (tools, techniques, people, learnings)
3. **Categorize** into appropriate files:
   - `tools.md` — Software, APIs, services
   - `tech.md` — Development techniques, workflows  
   - `design.md` — UI/UX insights
   - `people.md` — Worthwhile accounts
   - `misc.md` — Other valuable insights
4. **Append** with consistent formatting including date and URL

## How to Use

Simply send a tweet URL:
```
https://x.com/username/status/1234567890
```

The agent will automatically:
- Detect it's a tweet link
- Navigate and extract content
- Categorize insights
- Update the files
- Report what was added

## Output Format

Each entry follows this structure:

```markdown
## [Brief Descriptive Title]
**Date:** 2025-02-20
**URL:** https://x.com/...
**Key takeaway:** [The core insight or tool/technique]
**Why it matters:** [Context on why this is valuable]

---
```

## Files Managed

- `/tweet-notes/tools.md` — Tools and services discovered
- `/tweet-notes/tech.md` — Technical insights and workflows
- `/tweet-notes/design.md` — Design resources and patterns
- `/tweet-notes/people.md` — Accounts to follow
- `/tweet-notes/misc.md` — Everything else

## Philosophy

- **Be selective** — Only capture genuinely useful insights
- **Skip the fluff** — Ignore hype and noise
- **Actionable > Interesting** — Focus on things that can be used
- **Link everything** — Always include source URLs

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