Results for “correctness”

Patterns for managing MSBuild item groups: Include/Remove/Update semantics, item metadata, batching with %(Metadata), transforms, per-item filtering, and cross-product batching pitfalls. Only activate in MSBuild/.NET build context. USE FOR: diagnosing and fixing item group anti-patterns in .csproj files, reviewing item management for correctness, fixing CS2002 duplicate file warnings from SDK globbing, fixing targets that run more times than expected due to cross-product batching, fixing Include vs Update misuse on SDK-globbed items, fixing FileWrites registration for generated file clean support, moving generated files to IntermediateOutputPath. DO NOT USE FOR: target chain architecture (use target-authoring), property patterns (use property-patterns), incrementality (use incremental-build), general anti-patterns (use msbuild-antipatterns), non-MSBuild build systems.

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Validates custom dotnet new templates for correctness before publishing. Catches missing fields, parameter bugs, shortName conflicts, constraint issues, and common authoring mistakes that cause templates to fail silently. USE FOR: checking template.json files for errors before publishing or testing, diagnosing why a template doesn't appear after installation, reviewing template parameter definitions for type mismatches and missing defaults, finding shortName conflicts with dotnet CLI commands, validating post-action and constraint configuration. DO NOT USE FOR: finding or using existing templates (use template-discovery), creating projects from templates (use template-instantiation), creating templates from existing projects (use template-authoring).

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宣言した処理（計測 / 通知 / 保存 / 検証 / 例外通知）が起点から末端まで途切れず配線されているかを確認し、「実装したつもり」で経路が途中で止まっている欠落を検出する

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Review changes to the Agent Skills import/export bridge for path safety, round-trip fidelity, and validation correctness.

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差分で新規に導入された import・メソッド呼び出し・ライブラリ API 参照が実在するかを code_search で検証し、AI 生成コード特有の幻覚的参照（存在しない関数・メソッド・モジュール・引数シグネチャ）を検出する

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Review a repository change for correctness, security, and maintainability.

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Review FriendlyBet quality, regression risk, test plans, release readiness, version bump discipline, scoring/locking correctness, provider fallback behavior, and dirty-worktree safety. Use before shipping app code, scoring changes, migrations, sports integrations, copy updates, PWA cache changes, or any risky user-facing flow.

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Senior Kotlin specialist code review — framework-agnostic. Use whenever the user asks to review, audit, critique, or get feedback on Kotlin code, a file, a class, a function, a module, a diff, a branch, a commit, or a pull request. Judges Kotlin language idioms, logic correctness, architecture and layering, concurrency (coroutines, Flow, structured concurrency, cancellation, race conditions), null safety, exception safety, testability, performance, and security. Detects force-unwraps, unchecked casts, GlobalScope, leaked mutability, broken structured concurrency, hidden side effects, weak abstractions, untestable seams, allocation hot spots, weak crypto, input-validation gaps, and PII logging. Outputs prioritized findings with file:line anchors and minimal-diff fixes. No assumptions about DI framework, UI framework, or build system.

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Validate documentation before merging - check completeness, broken links, code example accuracy, and factual correctness. Use when reviewing docs for quality gates or running pre-merge doc validation.

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Review working changes - code quality, security, library correctness, and standards auto-fix

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Design, validate, and optimize schema.org structured data for eligibility, correctness, and measurable SEO impact.

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Reviews Swift code for concurrency correctness, modern API usage, and common async/await pitfalls. Use when reading, writing, or reviewing Swift concurrency code.

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Implement, review, or improve SwiftUI features using the iOS 26+ Liquid Glass API. Use when asked to adopt Liquid Glass in new SwiftUI UI, refactor an existing feature to Liquid Glass, or review Liquid Glass usage for correctness, performance, and design alignment.

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Fan six specialist reviewers (general correctness, silent failures, type design, test gaps, comment accuracy, simplification) out over the current diff, a branch, or a PR in parallel, then merge their findings into one deduplicated, ranked report. Use for a thorough review before merging. Not for editing code or approving on someone's behalf.

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Diff-scoped correctness review that reads the codebase around the change — callers, contracts, and invariants — and returns line-anchored findings ranked by severity with confidence, then a merge-risk verdict. Use for reviewing a PR, diff, or named change set. Not for style review, approvals-as-rubber-stamp, or editing the code.

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Improve clarity and reduce needless complexity after behavior is understood; preserve behavior and keep cleanup separate from correctness fixes.

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Run convex-doctor static analysis, interpret findings, and fix issues across security, performance, correctness, schema, and architecture categories. Use when running convex-doctor, fixing convex-doctor warnings or errors, improving the convex-doctor score, or when asked about Convex code quality, static analysis, or linting Convex functions.

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Implement, review, or improve SwiftUI features using the iOS 26+ Liquid Glass API. Use when asked to adopt Liquid Glass in new SwiftUI UI, refactor an existing feature to Liquid Glass, or review Liquid Glass usage for correctness, performance, and design alignment.

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Implement and review iOS 26+ SwiftUI Liquid Glass UI. Use when adopting Liquid Glass or checking its correctness, performance, and design fit.

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An uncompromising Academic Research Engineer. Operates with absolute scientific rigor, objective criticism, and zero flair. Focuses on theoretical correctness, formal verification, and optimal implementation across any required technology.

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Automatic quality control, linting, and static analysis procedures. Use after every code modification to ensure syntax correctness and project standards. Triggers onKeywords: lint, format, check, validate, types, static analysis.

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Deep, excruciating code review. Use anytime to analyze code for correctness, edge cases, security, performance, and design issues. Not tied to baseline—this is pure code analysis.

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Delegate writing predictable code to the `code-write` command, which has a cheaper writer model write the target file directly so the generated code never enters your context. Use for tests, scaffolding, fixtures, boilerplate, or a new file that copies an existing pattern, and when the user says "code write", "生成を委譲", or "雛形を書かせて". Do NOT use for design decisions, changes to public contracts or shared modules, edits inside an existing file that needs judgment, or logic with subtle correctness requirements.

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Delegate reading large or multiple files to the `bulk-read` command, which sends the files to a cheaper reader model and returns only its answer. Use when a question needs the content of a file over about 350 lines or of several files at once, when a PreToolUse guard denied an unbounded read, or when the user says "bulk read", "一括読み込み", or "まとめて読んで". Do NOT use for files you are about to edit, for subtle correctness reasoning such as concurrency bugs, or for short files that fit a bounded read.

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