fear-and-greed

Access the Alternative.me Crypto Fear & Greed Index. Use this tool to anchor your baseline market sentiment analysis, determining whether the broader retail market is in a state of Extreme Fear (capitulation risk) or Extreme Greed (euphoria/correction risk).

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byopenclaw

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Best use case

fear-and-greed is best used when you need a repeatable AI agent workflow instead of a one-off prompt.

Teams using fear-and-greed 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

$curl -o ~/.claude/skills/fear-and-greed-index/SKILL.md --create-dirs "https://raw.githubusercontent.com/openclaw/skills/main/skills/arielcaba-dev/fear-and-greed-index/SKILL.md"

Manual Installation

Download SKILL.md from GitHub
Place it in .claude/skills/fear-and-greed-index/SKILL.md inside your project
Restart your AI agent — it will auto-discover the skill

How fear-and-greed Compares

Feature / Agent	fear-and-greed	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?

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.

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SKILL.md Source

# Crypto Fear & Greed Index API

Access the global crypto market sentiment baseline using the free Alternative.me API.

## API Endpoint

Base URL: `https://api.alternative.me/fng/`

The API requires no authentication or API keys. 

### Get Current Sentiment

Fetch the latest daily Fear & Greed metric (0-100 score + classification label):

```bash
curl -s "https://api.alternative.me/fng/?limit=1"
```

Returns a JSON structure containing:
- `value`: The 0-100 numerical score.
- `value_classification`: The textual label (e.g. "Extreme Fear", "Fear", "Greed", "Extreme Greed").
- `timestamp`: Unix epoch of the data point.

## Common Use Cases

### Sentiment Baseline Anchoring
When conducting qualitative sentiment analysis on news headlines or on-chain flows, first fetch the Fear & Greed index to anchor your assumptions about retail psychology.

1. If `value` < 25 (Extreme Fear): The market is highly sensitive to bearish catalysts. Price may be artificially depressed.
2. If `value` > 75 (Extreme Greed): The market is euphoric and ignoring risk. High danger of sudden liquidations or corrections.

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