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Analysis Swarm

Checked
d-o-hub·vlatest·agents·MIT

D-O-Hub's analysis-swarm rapidly synthesizes insights from diverse data sources through collaborative AI processing.

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 d-o-hub/rust-self-learning-memory --skill analysis-swarm -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

d-o-hub

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 passed all 6 checks. We read its files at one commit and looked for the things that make a skill dangerous to run — not for whether it works.

  • 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 undeclared network calls: passed

    Makes no network calls.

    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.

  • 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 d-o-hub/rust-self-learning-memory at da7210f59b.

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

Commit
da7210f59b
Manifest
.agents/skills/analysis-swarm/SKILL.md
Scanned
6 files, 296 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 analysis-swarm skill enables an AI agent to process and synthesize information from multiple sources concurrently. It can analyze text, code, or other data formats, identifying key themes, patterns, and anomalies across them. This allows for more comprehensive understanding and decision-making compared to sequential analysis of individual inputs.

When to use it

  • Competitive Analysis: Gathering and comparing information from competitor websites and marketing materials.
  • Research Synthesis: Combining findings from multiple research papers or articles on a specific topic.
  • Code Review & Bug Detection: Analyzing code snippets from different developers to identify potential conflicts or bugs.
  • Sentiment Analysis of Customer Feedback: Aggregating and analyzing customer reviews from various platforms (social media, surveys, etc.).

Key capabilities

  • Concurrent data processing
  • Pattern identification across multiple sources
  • Anomaly detection
  • Text and code analysis

Example prompts

  • "Analyze these three articles about climate change and summarize the main arguments."
  • "Compare these five competitor product descriptions and identify their key differentiators."
  • "Review these four code snippets for potential security vulnerabilities."

Tips & gotchas

The skill performs best with structured data or clearly defined input formats. Large inputs may require increased processing time.