Rust Lifetime Complex
CheckedAnalyzes complex Rust code to identify potential lifetime issues and suggest safe borrowing strategies.
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rust-lifetime-complex. SKILL.md frontmatter is not valid YAML, so the skills CLI skips it.We check each listing against its upstream repository with the rules the skills CLI uses, last on 2026-09-28. We don't show a command we know will fail.
What we know about this skill
Publisher
huiali
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Install target
Live repository
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Automated safety checks
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
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No credential access: passed
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No `curl … | sh` pattern, in the code or in the instructions, that runs code fetched at run time.
Pinned to a commit: passed
Scanned huiali/rust-skills at 947bf77509.
The exact upstream commit SHA that was scanned is recorded, so the result refers to specific bytes.
- Commit
- 947bf77509
- Scanned
- 8 files, 1,058 lines
- Copies in repo
- 2 — all of them scanned
About this skill
What it does
This skill enables AI agents to reason about and generate correct Rust code involving complex lifetimes. It allows for understanding of lifetime annotations, borrowing rules, and how they relate to memory safety in Rust programs. The agent can assist with tasks such as identifying potential lifetime issues and suggesting appropriate fixes within existing codebases.
When to use it
- Code review: Analyze Rust code snippets to identify potential lifetime errors or areas where lifetimes could be improved for clarity and efficiency.
- Code generation: Generate new Rust functions or modules that require careful management of memory ownership and borrowing, ensuring correctness by default.
- Refactoring: Assist in refactoring existing Rust code to improve its safety and performance by correctly applying lifetime annotations.
- Learning & Explanation: Explain complex lifetime scenarios within a Rust program to developers learning the language.
Key capabilities
- Understanding of Rust's borrowing rules.
- Generation of correct lifetime annotations (
'a,'static, etc.). - Identification of potential dangling pointers and other lifetime-related errors.
- Reasoning about ownership and memory safety in Rust code.
Example prompts
- "Explain the lifetimes involved in this Rust function: [code snippet]"
- "Generate a Rust struct with two fields, ensuring that both are valid borrows."
- "I'm getting a 'borrowed value does not live long enough' error here: [code snippet]. Can you suggest a fix?"
Tips & gotchas
- The agent’s effectiveness is dependent on the complexity of the Rust code provided. Very large or intricate projects may require more context for accurate analysis.
- Ensure that the AI agent has access to relevant dependencies and compiler information when generating or analyzing code.