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Macd

v2.0.4

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

0· 180·1 current·1 all-time

Install

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Best for remote or guided setup. Copy the exact prompt, then paste it into OpenClaw for bytesagain-lab/macd.

Previewing Install & Setup.
Prompt PreviewInstall & Setup
Install the skill "Macd" (bytesagain-lab/macd) from ClawHub.
Skill page: https://clawhub.ai/bytesagain-lab/macd
Keep the work scoped to this skill only.
After install, inspect the skill metadata and help me finish setup.
Use only the metadata you can verify from ClawHub; do not invent missing requirements.
Ask before making any broader environment changes.

Command Line

CLI Commands

Use the direct CLI path if you want to install manually and keep every step visible.

OpenClaw CLI

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openclaw skills install macd

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npx clawhub@latest install macd
Security Scan
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high confidence
Purpose & Capability
Name/description match the included code and instructions. The skill only requires bash and python3 and exposes commands to calculate MACD from an inline series or a CSV file, interpret values, and display trading guidance — all consistent with a MACD calculator.
Instruction Scope
SKILL.md instructs the agent to run the provided scripts/script.sh commands. The script only reads user-supplied input (inline price list or a file path), computes values locally, and prints results. It does not reach out to external endpoints or read environment variables beyond those it sets to pass data to Python. Note: calculate-file reads whatever file path the user supplies (expected for this feature).
Install Mechanism
No install spec is provided and the skill is instruction/script-only. Nothing is downloaded or written to disk by an installer — the lowest-risk model for install behavior.
Credentials
The skill declares no required environment variables, no credentials, and no config paths. The script uses temporary environment variables to pass parameters to the embedded Python invocations only, which is proportional to its function.
Persistence & Privilege
always is false and the skill does not request persistent or elevated agent/system privileges. It does not modify other skills or alter system configuration.
Assessment
This skill appears to do only local MACD calculations using your provided price series or a CSV file. Before running: ensure you have python3 and bash available; only pass files you intend the tool to read (it will open any path you give it); if you plan to run untrusted skills, consider running them in a sandbox. Also validate numeric results (indexing/alignment logic in the script is a bit intricate) before using outputs for live trading decisions — this review addresses coherence, not financial correctness.

Like a lobster shell, security has layers — review code before you run it.

latestvk9727f0ng63mqzfcew27cqspas83mzpb
180downloads
0stars
5versions
Updated 1w ago
v2.0.4
MIT-0

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 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 scripts/script.sh calculate-file prices.csv

interpret

Interpret MACD, signal, and histogram values with trading signals.

bash scripts/script.sh interpret 1.25 0.80

crossover

Explain crossover patterns and trading rules.

bash scripts/script.sh crossover

histogram

MACD histogram analysis and momentum reading guide.

bash scripts/script.sh histogram

strategies

MACD trading strategies with entry/exit rules.

bash scripts/script.sh strategies

help

Show all commands.

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

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