Fetch Rust versions, crate information, and API documentation from authoritative sources.
Works with
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
AI-first code editor with Composer
Before installing skills in Cursor, ensure your development environment meets these requirements:
node --versionrust-learnerExecute the skills CLI command in your project's root directory to begin installation:
Fetches rust-learner from zhanghandong/rust-skills and configures it for Cursor.
The CLI shows a list of agents. Use arrow keys and space to select Cursor:
Confirm successful installation by checking the skill directory location:
Restart Cursor to activate rust-learner. Access via /rust-learner in your agent's command palette.
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.
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Automate repetitive workflows and reduce manual effort
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Generate reports, summarize documents, draft communications
Save 3-5 hours per week on routine tasks
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Explain concepts, provide examples, suggest learning resources
Accelerate learning and skill development by 2x
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Review drafts, suggest improvements, catch errors
Improve work quality by 30-40% with less effort
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Version: 2.1.0 | Last Updated: 2025-01-27
You are an expert at fetching Rust and crate information. Help users by:
Primary skill for fetching Rust/crate information.
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 |
When agent files exist at ../../agents/:
run_in_background: trueTask(
subagent_type: "general-purpose",
run_in_background: true,
prompt: <read from ../../agents/*.md file>
)
| 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 |
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
When agent files are NOT available, execute directly using these steps:
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})
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
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.)
**Output Format:**
```markdown
## {crate}::{path}
**Signature:**
```rust
{signature}
Description: {description}
Examples:
{example_code}
### Clippy Lints
**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
actionbook → agent-browser → WebFetch (only if agent-browser unavailable)
DO NOT:
| 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 | 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 |
This skill triggers AUTOMATICALLY when:
DO NOT use WebSearch for Rust crate info. Use agents or inline mode instead.
Prerequisites
Time Estimate
15-45 minutes depending on use case complexity
Steps
Common Pitfalls
✓ Do
✗ Don't
💡 Pro Tips
✓ 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.
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Keeps context tight: rust-learner is the kind of skill you can hand to a new teammate without a long onboarding doc.
rust-learner is among the better-maintained entries we tried; worth keeping pinned for repeat workflows.
rust-learner has been reliable in day-to-day use. Documentation quality is above average for community skills.
rust-learner has been reliable in day-to-day use. Documentation quality is above average for community skills.
Solid pick for teams standardizing on skills: rust-learner is focused, and the summary matches what you get after install.
Keeps context tight: rust-learner is the kind of skill you can hand to a new teammate without a long onboarding doc.
Solid pick for teams standardizing on skills: rust-learner is focused, and the summary matches what you get after install.
rust-learner has been reliable in day-to-day use. Documentation quality is above average for community skills.
rust-learner is among the better-maintained entries we tried; worth keeping pinned for repeat workflows.
We added rust-learner from the explainx registry; install was straightforward and the SKILL.md answered most questions upfront.
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