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rust-code-review

Rust Code review checklist and decision framework for Rust PRs, derived from rust-best-practices.

DeepseekModel 官方收录技能 质量 优秀 · 78 v1.0.0

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name rust-code-review description Rust Code review checklist and decision framework for Rust PRs, derived from rust-best-practices. globs ["**/*.rs"] alwaysApply true Rust Code Review Use this for Rust review work where consistency, safety, and maintainability matter. Follow ths standards in https://github.com/apollographql/rust-best-practices Mandatory pre-merge checks Ownership and data flow are intentional. Error handling is explicit and aligns with crate/binary boundaries. Clippy and format quality are clean in touched files. Performance changes are measured before acceptance. Public APIs are documented; docs match runtime behavior. Tests cover intended behavior and error paths. Unsafe or raw-pointer usage is justified and constrained. Severity matrix P0: unsafe memory bug, panic in recoverable production path, silent data corruption. P1: correctness bug, missing error propagation, invalid API contract. P2: likely performance regression, missing public API docs, flaky tests. P3: style/readability issues, avoidable clone/allocation, unnecessary complexity. Review skills Ownership-first coding Prefer borrowing ( &T , &mut T ) over cloning. Use Clone only when ownership is required or snapshots are explicitly needed. Treat unnecessary clones (especially in loops) as likely regressions. Reject clone on Copy types. Value vs reference Pass Copy /small POD types by value. Pass large heap-backed or non-trivial objects by reference. Surface ownership intent in function signatures. Use Cow<'_, T> when input may be borrowed or owned. Fallible control flow Use let PATTERN = EXPR else { ... } for expected early exits. Use if let ... else when divergence needs additional logic. Prefer ? for bubbling errors. Avoid unwrap / expect in production except when impossible-by-design cases are documented. Allocation and allocation timing Prefer _else APIs to avoid eager allocation ( ok_or_else , map_or_else , etc.). Keep iterator chains lazy; allocate only when required by terminal ops. Do not collect and allocate only to throw away data. Iterator vs loop Use iterator chains for data transformation and composition. Use for for early exits and side-effect-heavy or control-heavy loops. Require readable formatting; avoid long unreadable chains. Lints and static checks Run and fix warnings from: cargo clippy --all-targets --all-feature --locked -- -D warnings Do not globally silence useful lints. Prefer #[expect(clippy::...)] with rationale instead of #[allow(...)] unless fully justified. Error discipline Libraries: prefer typed errors ( thiserror and #[from] conversions). Binaries: anyhow acceptable, but keep context rich and actionable. Test both success and error behavior. Tests as behavior docs One behavior per test. One core assertion per test where possible. Names should be descriptive sentence-like statements. Prefer unit tests for internals, integration tests for public behavior. Use snapshot tests only for complex, stable structured outputs. Documentation and comments Use /// / //! for API behavior and constraints. Use // for why , safety rationale, platform constraints, and assumptions. Remove stale comments; prefer smaller functions over narrative comments. Link TODOs to issues instead of leaving bare TODO: . Pointers and concurrency Prefer & / &mut before any heap pointer. Use Arc for cross-thread shared ownership; Rc for single-threaded. Use Box for recursive/heap allocation needs. Review raw pointer usage as unsafe boundaries with explicit invariants. Quick rejection triggers Unnecessary clones in hot paths. Unjustified allow(clippy::...) . Silent recovery from Err that discards root cause. Copying large types by value without a proof of intent. Comments that simply restate what code already expresses. TODOs without ownership/context.
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下载的 .skill 包内含以下字段。
字段 说明
format格式标识(skill/v1)
skill_id技能唯一 ID
name技能名称
version版本号
description技能描述
category所属分类(数组)
trigger_words触发词列表
tags标签列表
source来源标识
source_url来源链接(本页地址)
exported_at导出时间(每次下载生成)
system_prompt系统提示词正文
model_config模型参数:provider / model / temperature / max_tokens / top_p
examples示例
install_guide各平台导入说明(Coze / Dify / Claude / 自定义框架)
同一份技能可按不同平台格式导出。
.skill 标准格式,含 system_prompt 与 model_config,导入任意 Agent 框架即可使用 下载
.skillpro 增强格式,额外含脚本 / 工具 / 依赖 / 钩子占位 下载
.json 纯 JSON 导出,只含 system_prompt 与模型参数 下载
Coze 带 frontmatter 的 Markdown,Coze 平台导入用 下载
Dify Dify DSL,创建应用后直接导入 下载

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