rust-call-graph
Visualize Rust function call graphs with configurable depth and direction using LSP.
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What it does
Supports three query directions: incoming calls (who calls this), outgoing calls (what this calls), and bidirectional analysis
Configurable traversal depth (default 3 levels) to control graph scope and complexity
Generates ASCII tree visualizations with entry points, leaf functions, and hot path analysis
Includes complexity insights and potential issues flagging (high fan-out, multiple callers)
Installation Guide
How to use rust-call-graph on Cursor
AI-first code editor with Composer
Prerequisites
Before installing skills in Cursor, ensure your development environment meets these requirements:
- ›Cursor installed and configured on your machine
- ›Node.js 16+ with npm — verify with
node --version - ›Active project directory where you want to add
rust-call-graph
Run the install command
Execute the skills CLI command in your project's root directory to begin installation:
Fetches rust-call-graph from zhanghandong/rust-skills and configures it for Cursor.
Select Cursor when prompted
The CLI shows a list of agents. Use arrow keys and space to select Cursor:
Verify installation
Confirm successful installation by checking the skill directory location:
Restart Cursor to activate rust-call-graph. Access via /rust-call-graph in your agent's command palette.
Security Notice
We perform automated surface-level scans (Gen AI Scanner, Socket, Snyk) during installation. These checks detect common vulnerabilities but do not guarantee complete security. Always review skill source code and verify the publisher's reputation before production use.
Skills execute code in your environment. Always review source, verify the publisher, and test in isolation before production.
Documentation
Rust Call Graph
Visualize function call relationships using LSP call hierarchy.
Usage
/rust-call-graph <function_name> [--depth N] [--direction in|out|both]
Options:
--depth N: How many levels to traverse (default: 3)--direction:in(callers),out(callees),both
Examples:
/rust-call-graph process_request- Show both callers and callees/rust-call-graph handle_error --direction in- Show only callers/rust-call-graph main --direction out --depth 5- Deep callee analysis
LSP Operations
1. Prepare Call Hierarchy
Get the call hierarchy item for a function.
LSP(
operation: "prepareCallHierarchy",
filePath: "src/handler.rs",
line: 45,
character: 8
)
2. Incoming Calls (Who calls this?)
LSP(
operation: "incomingCalls",
filePath: "src/handler.rs",
line: 45,
character: 8
)
3. Outgoing Calls (What does this call?)
LSP(
operation: "outgoingCalls",
filePath: "src/handler.rs",
line: 45,
character: 8
)
Workflow
User: "Show call graph for process_request"
│
▼
[1] Find function location
LSP(workspaceSymbol) or Grep
│
▼
[2] Prepare call hierarchy
LSP(prepareCallHierarchy)
│
▼
[3] Get incoming calls (callers)
LSP(incomingCalls)
│
▼
[4] Get outgoing calls (callees)
LSP(outgoingCalls)
│
▼
[5] Recursively expand to depth N
│
▼
[6] Generate ASCII visualization
Output Format
Incoming Calls (Who calls this?)
## Callers of `process_request`
main
└── run_server
└── handle_connection
└── process_request ◄── YOU ARE HERE
Outgoing Calls (What does this call?)
## Callees of `process_request`
process_request ◄── YOU ARE HERE
├── parse_headers
│ └── validate_header
├── authenticate
│ ├── check_token
│ └── load_user
├── execute_handler
│ └── [dynamic dispatch]
└── send_response
└── serialize_body
Bidirectional (Both)
## Call Graph for `process_request`
┌─────────────────┐
│ main │
└────────┬────────┘
│
┌────────▼────────┐
│ run_server │
└────────┬────────┘
│
┌────────▼────────┐
│handle_connection│
└────────┬────────┘
│
┌────────────────────┼────────────────────┐
│ │ │
┌───────▼───────┐ ┌───────▼───────┐ ┌───────▼───────┐
│ parse_headers │ │ authenticate │ │send_response │
└───────────────┘ └───────┬───────┘ └───────────────┘
│
┌───────┴───────┐
│ │
┌──────▼──────┐ ┌──────▼──────┐
│ check_token │ │ load_user │
└─────────────┘ └─────────────┘
Analysis Insights
After generating the call graph, provide insights:
## Analysis
**Entry Points:** main, test_process_request
**Leaf Functions:** validate_header, serialize_body
**Hot Path:** main → run_server → handle_connection → process_request
**Complexity:** 12 functions, 3 levels deep
**Potential Issues:**
- `authenticate` has high fan-out (4 callees)
- `process_request` is called from 3 places (consider if this is intentional)
Common Patterns
| User Says | Direction | Use Case |
|---|---|---|
| "Who calls X?" | incoming | Impact analysis |
| "What does X call?" | outgoing | Understanding implementation |
| "Show call graph" | both | Full picture |
| "Trace from main to X" | outgoing | Execution path |
Visualization Options
| Style | Best For |
|---|---|
| Tree (default) | Simple hierarchies |
| Box diagram | Complex relationships |
| Flat list | Many connections |
| Mermaid | Export to docs |
Mermaid Export
graph TD
main --> run_server
run_server --> handle_connection
handle_connection --> process_request
process_request --> parse_headers
process_request --> authenticate
process_request --> send_response
Related Skills
| When | See |
|---|---|
| Find definition | rust-code-navigator |
| Project structure | rust-symbol-analyzer |
| Trait implementations | rust-trait-explorer |
| Safe refactoring | rust-refactor-helper |
List & Monetize Your Skill
Submit your Claude Code skill and start earning
Use Cases
Task Automation & Efficiency
Automate repetitive workflows and reduce manual effort
Example
Generate reports, summarize documents, draft communications
Save 3-5 hours per week on routine tasks
Knowledge Enhancement
Learn new skills, understand complex topics, get expert guidance
Example
Explain concepts, provide examples, suggest learning resources
Accelerate learning and skill development by 2x
Quality Improvement
Enhance output quality through reviews, suggestions, and refinements
Example
Review drafts, suggest improvements, catch errors
Improve work quality by 30-40% with less effort
Implementation Guide
Prerequisites
- ›Claude Desktop or compatible AI client with skill support
- ›Clear understanding of task or problem to solve
- ›Willingness to iterate and refine outputs
Time Estimate
15-45 minutes depending on use case complexity
Steps
- 1Install skill using provided installation command
- 2Test with simple use case relevant to your work
- 3Evaluate output quality and relevance
- 4Iterate on prompts to improve results
- 5Integrate into regular workflow if valuable
Common Pitfalls
- ⚠Expecting perfect results without iteration
- ⚠Not providing enough context in prompts
- ⚠Using skill for tasks outside its intended scope
- ⚠Accepting outputs without review and validation
Best Practices
✓ Do
- +Start with clear, specific prompts
- +Provide relevant context and constraints
- +Review and refine all outputs before using
- +Iterate to improve output quality
- +Document successful prompt patterns
✗ Don't
- −Don't use without understanding skill limitations
- −Don't skip validation of outputs
- −Don't share sensitive information in prompts
- −Don't expect skill to replace human judgment
💡 Pro Tips
- ★Be specific about desired format and style
- ★Ask for multiple options to choose from
- ★Request explanations to understand reasoning
- ★Combine AI efficiency with human expertise
When to Use This
✓ Use when
Use when skill capabilities match your task, clear ROI on time saved, and you can validate outputs. Best for repetitive tasks, learning, and quality improvement.
✗ Avoid when
Avoid when task requires deep expertise you can't validate, involves sensitive decisions, or when learning process is more valuable than speed of completion.
Learning Path
- 1Familiarize yourself with skill capabilities and limitations
- 2Start with low-risk, non-critical tasks
- 3Progress to more complex and valuable use cases
- 4Build expertise through regular use and experimentation
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Reviews
- CChen Gupta★★★★★Dec 28, 2024
Useful defaults in rust-call-graph — fewer surprises than typical one-off scripts, and it plays nicely with `npx skills` flows.
- AAlexander Menon★★★★★Dec 24, 2024
We added rust-call-graph from the explainx registry; install was straightforward and the SKILL.md answered most questions upfront.
- GGanesh Mohane★★★★★Dec 4, 2024
rust-call-graph has been reliable in day-to-day use. Documentation quality is above average for community skills.
- RRahul Santra★★★★★Nov 23, 2024
Keeps context tight: rust-call-graph is the kind of skill you can hand to a new teammate without a long onboarding doc.
- JJames Huang★★★★★Nov 19, 2024
I recommend rust-call-graph for anyone iterating fast on agent tooling; clear intent and a small, reviewable surface area.
- IIshan Srinivasan★★★★★Nov 15, 2024
rust-call-graph fits our agent workflows well — practical, well scoped, and easy to wire into existing repos.
- PPratham Ware★★★★★Oct 14, 2024
We added rust-call-graph from the explainx registry; install was straightforward and the SKILL.md answered most questions upfront.
- JJames Khan★★★★★Oct 10, 2024
Solid pick for teams standardizing on skills: rust-call-graph is focused, and the summary matches what you get after install.
- JJames Singh★★★★★Oct 6, 2024
rust-call-graph has been reliable in day-to-day use. Documentation quality is above average for community skills.
- YYusuf Huang★★★★★Sep 17, 2024
rust-call-graph reduced setup friction for our internal harness; good balance of opinion and flexibility.
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