Skip to content
TrustedSkillsbeta
Back to all skills

Rust Call Graph

Checked
zhanghandong·vlatest·backend

Generates Rust code call graphs from source files to visualize function dependencies and understand program flow.

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 actionbook/rust-skills --skill rust-call-graph -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

zhanghandong

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 zhanghandong/rust-skills at 5c40d3ad78.

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

Commit
5c40d3ad78
Manifest
skills/rust-call-graph/SKILL.md
Scanned
1 file, 187 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 rust-call-graph skill enables AI agents to analyze and visualize function call relationships in Rust codebases. It can parse source files, identify dependencies between functions, and generate a structured representation of how functions interact within the project.

When to use it

  • To understand complex code structures during debugging or refactoring
  • For generating documentation that maps out function interactions
  • When optimizing performance by identifying frequently called functions
  • During code reviews to trace execution paths across modules

Key capabilities

  • Parses Rust source files for function definitions and calls
  • Builds a call graph representing dependencies between functions
  • Supports visualization of the graph in various formats (e.g., DOT, JSON)
  • Identifies cyclic dependencies or unused functions

Example prompts

  • "Generate a call graph for the src/lib.rs file."
  • "Show me all functions called by main() in this project."
  • "Visualize the function dependencies as a DOT file."

Tips & gotchas

  • Ensure that the Rust code is well-formed and compiled to avoid parsing errors.
  • Large projects may require additional memory or processing time for accurate graph generation.