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Financial Deep Research

Listed
eng0ai·vlatest·data

Analyzes financial data for insights & trends using advanced algorithms, aiding in informed investment decisions and market understanding.

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 rebyteai-template/rebyte-skills --skill financial-deep-research -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

eng0ai

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 6 hosts that are neither well-known infrastructure nor declared in the skill's frontmatter: doi.org, ir.apple.com, seekingalpha.com, www.bloomberg.com, www.sec.gov….

    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

    www.sec.govundeclaredwww.bloomberg.comundeclaredwww.wsj.comundeclaredseekingalpha.comundeclaredir.apple.comundeclareddoi.orgundeclared

    What it found (3 of 8)

    • financial-deep-research/scripts/citation_manager.py:230contacts www.sec.gov
      url="https://www.sec.gov/cgi-bin/browse-edgar?action=getcompany&CIK=0000320193",
    • financial-deep-research/scripts/source_evaluator.py:383contacts www.sec.gov
      'url': 'https://www.sec.gov/cgi-bin/browse-edgar?action=getcompany&CIK=0000320193',
    • financial-deep-research/scripts/citation_manager.py:240contacts www.bloomberg.com
      url="https://www.bloomberg.com/quote/AAPL:US",

  • 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 eng0ai/eng0-template-skills at 0062e44684.

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

Commit
0062e44684
Manifest
financial-deep-research/SKILL.md
Scanned
12 files, 3,625 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

The financial-deep-research skill enables AI agents to perform in-depth analysis of financial data, including stock market trends, company performance metrics, and economic indicators. It leverages advanced algorithms to extract insights from large datasets, helping users make informed investment decisions.

When to use it

  • Analyzing quarterly earnings reports for a portfolio of stocks
  • Identifying potential investment opportunities based on macroeconomic trends
  • Evaluating the financial health of a company before investing

Key capabilities

  • Access and analyze real-time financial data
  • Generate detailed market trend forecasts
  • Compare company performance metrics across industries

Example prompts

  • "Analyze the stock performance of Apple Inc. over the last 12 months."
  • "Compare the revenue growth of Tesla and Ford in the automotive industry."
  • "Predict potential market trends based on recent Federal Reserve interest rate decisions."

Tips & gotchas

  • Ensure access to up-to-date financial databases for accurate results.
  • Be aware that predictions are based on historical data and may not always reflect future outcomes.