Async & Concurrency Reviewer
v1.0.0Reviews async and concurrency code for deadlocks, race conditions, missing cancellation, and misuse across multiple languages, returning detailed fix reports.
⭐ 0· 84·0 current·0 all-time
MIT-0
Download zip
LicenseMIT-0 · Free to use, modify, and redistribute. No attribution required.
Security Scan
OpenClaw
Benign
high confidencePurpose & Capability
Name, description, and the SKILL.md checklist all consistently describe a code review assistant for async/concurrency issues across languages. There are no unrelated environment variables, binaries, or installs requested that would be inconsistent with that purpose.
Instruction Scope
The instructions are narrowly scoped to receiving pasted code and returning structured findings. They do not instruct reading system files, environment variables, or sending data to external endpoints. However, the "self-improvement" section asks the skill to track counts and surface aggregated patterns after 20 reviews, which implies stateful tracking of past reviews (or their metadata). That could lead to persistent storage of user-submitted code or findings if not implemented carefully.
Install Mechanism
No install spec or code files are included (instruction-only), so nothing is written to disk or fetched at install time. This is the lowest-risk install profile.
Credentials
The skill does not request any environment variables, credentials, or config paths. That is proportionate for a stateless, instruction-only code reviewer.
Persistence & Privilege
The skill does not request always:true or elevated privileges. Nevertheless, the SKILL.md's self-improvement requirement (aggregating results after 20 reviews) implies persistent storage or memory. Users should verify whether the platform will store review content or summaries in long-term memory and whether that storage is appropriate for sensitive code.
Assessment
This skill appears coherent and low-risk: it asks you to paste code and returns a structured review. Before installing or using it on proprietary/sensitive code, confirm how the platform handles long-term memory and whether the skill will persist review data (the SKILL.md asks it to aggregate findings after 20 reviews). Never paste secrets, credentials, or entire production configs into the review prompt. If you need guarantees, ask the skill author (or platform) to disable persistent learning or to only store anonymized metadata, and test with non-sensitive examples first.Like a lobster shell, security has layers — review code before you run it.
latestvk9775fpfb3rqykqyh8rad2gnp183cc1s
License
MIT-0
Free to use, modify, and redistribute. No attribution required.