rust-learner

Fetch Rust versions, crate information, and API documentation from authoritative sources.

zhanghandong/rust-skillsUpdated Apr 8, 2026

Works with

Claude CodeCursorClineWindsurfCodexGooseGitHub CopilotZed

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Install Skill

Run in your terminal

$npx skills add https://github.com/zhanghandong/rust-skills --skill rust-learner

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this week

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What it does

  • Supports queries about Rust release features, crate versions, and standard library documentation via dedicated agent routing

  • Operates in two modes: agent-based (when agent files available) for background task execution, or inline mode using actionbook selectors and browser automation

  • Covers crate info from lib.rs and crates.io, Rust changelogs from releases.rs, std library docs from doc.rust-lan

Category

Backend

Last updated

Apr 8, 2026

Installation Guide

How to use rust-learner on Cursor

AI-first code editor with Composer

1

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-learner
2

Run the install command

Execute the skills CLI command in your project's root directory to begin installation:

$npx skills add https://github.com/zhanghandong/rust-skills --skill rust-learner

Fetches rust-learner from zhanghandong/rust-skills and configures it for Cursor.

3

Select Cursor when prompted

The CLI shows a list of agents. Use arrow keys and space to select Cursor:

◆ Which agents do you want to install to?
│ ── Universal (.agents/skills) ────────────────
│ · Cline · Codex · Goose · Windsurf
│ ●Cursor(selected)
│ · Cursor · Aider · Continue
4

Verify installation

Confirm successful installation by checking the skill directory location:

.cursor/skills/rust-learner

Restart Cursor to activate rust-learner. Access via /rust-learner 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 Learner

Version: 2.1.0 | Last Updated: 2025-01-27

You are an expert at fetching Rust and crate information. Help users by:

  • Version queries: Get latest Rust/crate versions
  • API documentation: Fetch docs from docs.rs
  • Changelog: Get Rust version features from releases.rs

Primary skill for fetching Rust/crate information.

Execution Mode Detection

CRITICAL: Check agent file availability first to determine execution mode.

Try to read the agent file for your query type. The execution mode depends on whether the file exists:

Query Type Agent File Path
Crate info/version ../../agents/crate-researcher.md
Rust version features ../../agents/rust-changelog.md
Std library docs ../../agents/std-docs-researcher.md
Third-party crate docs ../../agents/docs-researcher.md
Clippy lints ../../agents/clippy-researcher.md

Agent Mode (Plugin Install)

When agent files exist at ../../agents/:

Workflow

  1. Read the appropriate agent file (relative to this skill)
  2. Launch Task with run_in_background: true
  3. Continue with other work or wait for completion
  4. Summarize results to user
Task(
  subagent_type: "general-purpose",
  run_in_background: true,
  prompt: <read from ../../agents/*.md file>
)

Agent Routing Table

Query Type Agent File Source
Rust version features ../../agents/rust-changelog.md releases.rs
Crate info/version ../../agents/crate-researcher.md lib.rs, crates.io
Std library docs (Send, Sync, Arc, etc.) ../../agents/std-docs-researcher.md doc.rust-lang.org
Third-party crate docs (tokio, serde, etc.) ../../agents/docs-researcher.md docs.rs
Clippy lints ../../agents/clippy-researcher.md rust-clippy docs

Agent Mode Examples

Crate Version Query:

User: "tokio latest version"

Claude:
1. Read ../../agents/crate-researcher.md
2. Task(subagent_type: "general-purpose", run_in_background: true, prompt: <agent content>)
3. Wait for agent
4. Summarize results

Rust Changelog Query:

User: "What's new in Rust 1.85?"

Claude:
1. Read ../../agents/rust-changelog.md
2. Task(subagent_type: "general-purpose", run_in_background: true, prompt: <agent content>)
3. Wait for agent
4. Summarize features

Inline Mode (Skills-only Install)

When agent files are NOT available, execute directly using these steps:

Crate Info Query

1. actionbook: mcp__actionbook__search_actions("lib.rs crate info")
2. Get action details: mcp__actionbook__get_action_by_id(<action_id>)
3. agent-browser CLI (or WebFetch fallback):
   - open "https://lib.rs/crates/{crate_name}"
   - get text using selector from actionbook
   - close
4. Parse and format output

Output Format:

## {Crate Name}

**Version:** {latest}
**Description:** {description}

**Features:**
- `feature1`: description

**Links:**
- [docs.rs](https://docs.rs/{crate}) | [crates.io](https://crates.io/crates/{crate}) | [repo]({repo_url})

Rust Version Query

1. actionbook: mcp__actionbook__search_actions("releases.rs rust changelog")
2. Get action details for selectors
3. agent-browser CLI (or WebFetch fallback):
   - open "https://releases.rs/docs/1.{version}.0/"
   - get text using selector from actionbook
   - close
4. Parse and format output

Output Format:

## Rust 1.{version}

**Release Date:** {date}

### Language Features
- Feature 1: description
- Feature 2: description

### Library Changes
- std::module: new API

### Stabilized APIs
- `api_name`: description

Std Library Docs (std::*, Send, Sync, Arc, etc.)

1. Construct URL: "https://doc.rust-lang.org/std/{path}/"
   - Traits: std/{module}/trait.{Name}.html
   - Structs: std/{module}/struct.{Name}.html
   - Modules: std/{module}/index.html
2. agent-browser CLI (or WebFetch fallback):
   - open <url>
   - get text "main .docblock"
   - close
3. Parse and format output

Common Std Library Paths:

Item Path
Send, Sync, Copy, Clone std/marker/trait.{Name}.html
Arc, Mutex, RwLock std/sync/struct.{Name}.html
Rc, Weak std/rc/struct.{Name}.html
RefCell, Cell std/cell/struct.{Name}.html
Box std/boxed/struct.Box.html
Vec std/vec/struct.Vec.html
String std/string/struct.String.html

Output Format:

## std::{path}::{Name}

**Signature:**
```rust
{signature}

Description: {description}

Examples:

{example_code}

### Third-Party Crate Docs (tokio, serde, etc.)

  1. Construct URL: "https://docs.rs/{crate}/latest/{crate}/{path}"
  2. agent-browser CLI (or WebFetch fallback):
    • open
    • get text ".docblock"
    • close
  3. Parse and format output

**Output Format:**
```markdown
## {crate}::{path}

**Signature:**
```rust
{signature}

Description: {description}

Examples:

{example_code}

### Clippy Lints

  1. agent-browser CLI (or WebFetch fallback):
  2. Parse and format output

**Output Format:**
```markdown
## Clippy Lint: {lint_name}

**Level:** {warn|deny|allow}
**Category:** {category}

**Description:**
{what_it_checks}

**Example (Bad):**
```rust
{bad_code}

Example (Good):

{good_code}

---

## Tool Chain Priority

Both modes use the same tool chain order:

1. **actionbook MCP** - Get pre-computed selectors first
   - `mcp__actionbook__search_actions("site_name")` → get action ID
   - `mcp__actionbook__get_action_by_id(id)` → get URL + selectors

2. **agent-browser CLI** - Primary execution tool
   ```bash
   agent-browser open <url>
   agent-browser get text <selector_from_actionbook>
   agent-browser close
  1. WebFetch - Last resort only if agent-browser unavailable

Fallback Principle (CRITICAL)

actionbook → agent-browser → WebFetch (only if agent-browser unavailable)

DO NOT:

  • Skip agent-browser because it's slower
  • Use WebFetch as primary when agent-browser is available
  • Block on WebFetch without trying agent-browser first

Deprecated Patterns

Deprecated Use Instead Reason
WebSearch for crate info Task + agent or inline mode Structured data
Direct WebFetch actionbook + agent-browser Pre-computed selectors
Guessing version numbers Always fetch from source Prevents misinformation

Error Handling

Error Cause Solution
Agent file not found Skills-only install Use inline mode
actionbook unavailable MCP not configured Fall back to WebFetch
agent-browser not found CLI not installed Fall back to WebFetch
Agent timeout Site slow/down Retry or inform user
Empty results Selector mismatch Report and use WebFetch fallback

Proactive Triggering

This skill triggers AUTOMATICALLY when:

  • Any Rust crate name mentioned (tokio, serde, axum, sqlx, etc.)
  • Questions about "latest", "new", "version", "changelog"
  • API documentation requests
  • Dependency/feature questions

DO NOT use WebSearch for Rust crate info. Use agents or inline mode instead.

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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

  1. 1Install skill using provided installation command
  2. 2Test with simple use case relevant to your work
  3. 3Evaluate output quality and relevance
  4. 4Iterate on prompts to improve results
  5. 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

  1. 1Familiarize yourself with skill capabilities and limitations
  2. 2Start with low-risk, non-critical tasks
  3. 3Progress to more complex and valuable use cases
  4. 4Build expertise through regular use and experimentation

Related Skills

Reviews

4.643 reviews
  • D
    Dhruvi JainDec 16, 2024

    Keeps context tight: rust-learner is the kind of skill you can hand to a new teammate without a long onboarding doc.

  • A
    Aisha MalhotraDec 12, 2024

    rust-learner is among the better-maintained entries we tried; worth keeping pinned for repeat workflows.

  • A
    Aisha BhatiaDec 12, 2024

    rust-learner has been reliable in day-to-day use. Documentation quality is above average for community skills.

  • O
    OshnikdeepNov 7, 2024

    rust-learner has been reliable in day-to-day use. Documentation quality is above average for community skills.

  • A
    Aisha ChawlaNov 3, 2024

    Solid pick for teams standardizing on skills: rust-learner is focused, and the summary matches what you get after install.

  • J
    James ShahNov 3, 2024

    Keeps context tight: rust-learner is the kind of skill you can hand to a new teammate without a long onboarding doc.

  • G
    Ganesh MohaneOct 26, 2024

    Solid pick for teams standardizing on skills: rust-learner is focused, and the summary matches what you get after install.

  • Z
    Zaid WhiteOct 22, 2024

    rust-learner has been reliable in day-to-day use. Documentation quality is above average for community skills.

  • L
    Lucas MenonOct 22, 2024

    rust-learner is among the better-maintained entries we tried; worth keeping pinned for repeat workflows.

  • S
    Sakshi PatilSep 17, 2024

    We added rust-learner from the explainx registry; install was straightforward and the SKILL.md answered most questions upfront.

showing 1-10 of 43

1 / 5

Discussion

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