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Macd

CLAWHUB · Unverified

Calculate MACD from price data. Use when computing MACD/signal/histogram from a price series, spotting crossovers, reading momentum, or planning MACD-based e... Skill: Macd Owner: bytesagain-lab Summary: Calculate MACD from price data. Use when computing MACD/signal/histogram from a price series, spotting crossovers, reading momentum, or planning MACD-based e... Tags: latest:2.0.4 Version history: v2.0.4 | 2026-03-26T16:42:57.365Z | user Real MACD calculation from price series, declared python3 requirement v2.0.3 | 2026-03-26T16:40:11.024Z | user Clean build v2.0.2 | 2026-03

62
Rank
84
Safety
969
Downloads

About

What it does, and when to use it.

Capability contract not published. No trust telemetry is available yet. 969 downloads reported by the source. Last updated 10/12/2026.

Avoid when

  • Contract metadata is missing or unavailable for deterministic execution.

Risk flags: missing_or_unavailable_contract, trust_data_unavailable, schema_references_missing

Install and run

Setup complexity: low.

clawhub skill install s174pq5f3gzez3838vt2642fmx848f1d:macd
  1. Setup complexity is LOW. This package is likely designed for quick installation with minimal external side-effects.
  2. Final validation: Expose the agent to a mock request payload inside a sandbox and trace the network egress before allowing access to real customer data.

Contract: missing

curl -s "https://www.xpersona.co/api/v1/agents/clawhub-bytesagain-lab-macd/snapshot"

Run-check

$0.02 USD

1 measured facts are behind this paywall: success rate and latency, uptime and estimated cost, when not to use it, how to call it, benchmark scores.

Agents pay $0.02 in USDC. A card payment is $0.50, the smallest a card allows.

Documentation

CLAWHUB

12,436 characters of source documentation, loaded on request.

Extracted files

3 files captured from the source.

SKILL.md

---
name: "MACD — Moving Average Convergence Divergence"
description: "Calculate MACD from price data. Use when computing MACD/signal/histogram from a price series, spotting crossovers, reading momentum, or planning MACD-based entries."
version: "2.0.4"
author: "BytesAgain"
homepage: https://bytesagain.com
source: https://github.com/bytesagain/ai-skills
tags: ["macd", "trading", "crypto", "stocks", "technical-analysis", "finance", "momentum"]
---

# MACD — Moving Average Convergence Divergence

Calculate MACD from price data. Compute EMA, MACD line, signal line, and histogram from a CSV or inline price series.

## Requirements
- bash 4+
- python3 (standard library only)

## Commands

### calculate
Calculate MACD from a comma-separated price series.
```bash
bash scripts/script.sh calculate "170.5,171.2,172.8,171.0,173.5,174.2,175.0,174.8,176.1,175.5,177.2,178.0,176.5,177.8,179.0,178.5,180.2,179.8,181.0,180.5,182.3,181.8,183.0,182.5,184.0,183.5"
```

### calculate-file
Calculate MACD from a CSV file (one price per line or column).
```bash
bash scripts/script.sh calculate-file prices.csv
```

### interpret
Interpret MACD, signal, and histogram values with trading signals.
```bash
bash scripts/script.sh interpret 1.25 0.80
```

### crossover
Explain crossover patterns and trading rules.
```bash
bash scripts/script.sh crossover
```

### histogram
MACD histogram analysis and momentum reading guide.
```bash
bash scripts/script.sh histogram
```

### strategies
MACD trading strategies with entry/exit rules.
```bash
bash scripts/script.sh strategies
```

### help
Show all commands.
```bash
bash scripts/script.sh help
```

## Output
- Computed MACD line, signal line, and histogram from real price data
- EMA values at each step
- Crossover and divergence signals
- Trading strategy frameworks

## Feedback
https://bytesagain.com/feedback/
Powered by BytesAgain | bytesagain.com

_meta.json

{
  "ownerId": "kn76vqrf94wk924mddj8fp4p5x8497tb",
  "slug": "macd",
  "version": "2.0.4",
  "publishedAt": 1774543377365
}

skill-card.md

## Description:

Calculate MACD from price data. Use when computing MACD/signal/histogram from a price series, spotting crossovers, reading momentum, or planning MACD-based entries.

This skill is ready for commercial/non-commercial use.

## Publisher:

[bytesagain-lab](https://clawhub.ai/user/bytesagain-lab)

### License/Terms of Use:

MIT-0

## Use Case:

External users and finance-focused agents use this skill to compute MACD, signal line, histogram, and EMA values from supplied price data. It also provides educational momentum, crossover, histogram, and strategy guidance for interpreting MACD outputs.

### Deployment Geography for Use:

Global

## Known Risks and Mitigations:

Risk: CSV filename handling in calculate-file can allow local code execution when filenames or paths come from untrusted sources.

Mitigation: Review and fix filename handling before using calculate-file with external or untrusted paths; use only trusted local files until then.

Risk: The skill provides direct trading actions without a risk disclosure.

Mitigation: Use outputs as educational technical-analysis guidance only, not financial advice; require human review before acting on trading suggestions.

## Reference(s):

- [ClawHub skill page](https://clawhub.ai/bytesagain-lab/skills/macd)
- [BytesAgain homepage](https://bytesagain.com)

## Skill Output:

**Output Type(s):** [text, shell commands, guidance]

**Output Format:** [Plain text terminal output with tabular numeric values and explanatory guidance]

**Output Parameters:** [1D]

**Other Properties Related to Output:** [Requires bash 4+ and python3 standard library; calculation commands require enough price observations for the selected slow and signal periods.]

## Skill Version(s):

2.0.4 (source: server release metadata and frontmatter)

## Ethical Considerations:

Users should evaluate whether this skill is appropriate for their environment, review any generated or modified files before relying on them, and apply their organization's safety, security, and compliance requirements before deployment.

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