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Analyze Move Risk Gauges Leadlag

Listed
fatfingererr·vlatest·marketing·MIT

Evaluates move risk based on lead/lag indicators, providing nuanced insights for strategic decision-making.

Repository

Install on your platform

Showing Claude Code. One command installs this skill into any of the agents below.

  1. 1

    Run this in your project

    terminal
    $ npx skills add fatfingererr/macro-skills --skill analyze-move-risk-gauges-leadlag -a claude-code

  2. Uses the open-source skills CLI and needs Node.js. Add -g to install it for your user instead of this project.

What we know about this skill

Publisher

fatfingererr

Taken from the source listing. We haven't verified who controls this account.

Install target

Live repository

Not pinned. Installing fetches whatever the repository holds at the time you run the command.

No human has reviewed this code. The checks below are a static scan of the files at one commit — nobody has run this skill or judged whether it works. A skill runs with whatever access you give your agent, so read the source before you install it.

Automated safety checks

scanned

This skill failed 1 of 6 checks. A failure is not proof of bad intent; it means something in the code needs a human to look at it before you run it.

  • No undeclared network calls: failed

    Contacts 4 hosts that are neither well-known infrastructure nor declared in the skill's frontmatter: en.macromicro.me, finance.yahoo.com, fred.stlouisfed.org, www.investing.com.

    Every host the skill dials — from its scripts, its config endpoints or the commands it tells the agent to run — is either well-known package and API infrastructure or declared in its own frontmatter. Links in documentation are not counted.

    Hosts contacted

    127.0.0.1localfred.stlouisfed.orgundeclaredfinance.yahoo.comundeclaredwww.investing.comundeclareden.macromicro.meundeclaredgithub.comsource host

    What it found (3 of 12)

    • skills/analyze-move-risk-gauges-leadlag/manifest.json:65contacts fred.stlouisfed.org
      "url": "https://fred.stlouisfed.org",
    • skills/analyze-move-risk-gauges-leadlag/scripts/fetch_data.py:58contacts fred.stlouisfed.org
      FRED_CSV_URL = "https://fred.stlouisfed.org/graph/fredgraph.csv"
    • skills/analyze-move-risk-gauges-leadlag/manifest.json:80contacts finance.yahoo.com
      "url": "https://finance.yahoo.com",

  • Declares what it does: passed

    SKILL.md parses and declares a name and a description.

    SKILL.md exists, its frontmatter parses, and it declares a name and a description.

  • No obfuscated payloads: passed

    No encoded or obfuscated payloads.

    No base64, hex or compressed blob is decoded and then executed, and no encoded shell commands.

  • No credential access: passed

    Reads no keys, tokens, keychains or credential files.

    Neither the code nor the SKILL.md instructions read SSH keys, cloud credentials, keychains, token stores, browser cookie databases or dotfiles that hold secrets.

  • No pipe-to-shell installers: passed

    No pipe-to-shell or download-and-run installers.

    No `curl … | sh` pattern, in the code or in the instructions, that runs code fetched at run time.

  • Pinned to a commit: passed

    Scanned fatfingererr/macro-skills at 13e5388028.

    The exact upstream commit SHA that was scanned is recorded, so the result refers to specific bytes.

Commit
13e5388028
Manifest
skills/analyze-move-risk-gauges-leadlag/SKILL.md
Scanned
14 files, 4,820 lines
This is a static scan, not a review. It reads the skill's files; it does not run them, and it cannot tell you whether the skill is any good or whether the code does what its description says. A skill runs with whatever access you give your agent.
What each check looks for →

About this skill

What it does

This skill analyzes movement data, providing risk gauges and differentiating between lead and lag conditions. It assesses the potential danger associated with movements based on available information. The analysis helps determine if a move is advantageous or potentially hazardous, factoring in timing and positioning.

When to use it

  • Gaming: Evaluate the risk of an action in a strategy game, such as predicting enemy counter-moves.
  • Robotics: Assess the safety of robot movements in dynamic environments.
  • Financial Trading: Analyze market trends and identify potential risks associated with investment strategies.
  • Logistics: Determine the safest routes for vehicles by assessing lead/lag conditions related to traffic patterns.

Key capabilities

  • Risk Gauge Calculation
  • Lead/Lag Differentiation
  • Movement Data Analysis
  • Hazard Prediction

Example prompts

  • "Analyze this movement data and provide a risk gauge."
  • "Is this action leading or lagging, and what's the associated risk?"
  • "Assess the safety of this robot's next move based on current conditions."

Tips & gotchas

The accuracy of the analysis depends heavily on the quality and completeness of the input movement data. Ensure the data includes relevant factors like speed, direction, and surrounding environment information for optimal results.