「correctness」の検索結果

大量データの取り込みや過去分の補充、変換、同期の遅さを工程別に調べ、処理方法を比較して高速化し、行数・ファイル数・時刻の整合性まで確認するスキル。

• 大量データの取り込み・書き出しの高速化
• 過去データの補充時間を短縮したいとき
• バッチサイズや並列処理数を比較したいとき

Subjects every non-trivial decision to a fresh-context adversarial review before it stands. Use when you want every assumption cross-examined before proceeding, when stress-testing a plan for hidden failure modes, when correctness matters more than speed, when working in unfamiliar code, when stakes are high (production auth, security-sensitive logic, a high-stakes migration, irreversible operations), or any time a confident output would be cheaper to verify now than to debug later.

日本語の概要は準備中です。原文の説明を表示しています。

Grounds every implementation decision in official documentation. Use when you want to verify an approach against the official docs before implementing it, or when you want authoritative, source-cited code free from outdated patterns. Use when building with any framework or library where correctness matters.

日本語の概要は準備中です。原文の説明を表示しています。

Review the current diff, or a PR number/branch/path target, for correctness bugs (plus reuse/simplification/efficiency cleanups where the model's review recipe covers them) at the given effort level (low|medium|high|xhigh|max: from few high-confidence findings up to many, some of them uncertain; ultra: deep multi-agent review in the cloud); with no level given, it reuses the level you typed last. Pass --comment to post findings as inline PR comments, or --fix to apply the findings to the working tree after the review. Pass --max-findings <n> to report up to n findings, or --max-findings all for every finding. The choice stays until you pass --max-findings default. For ultra on a GitHub.com PR target, --post asks to post the finished review’s findings to the PR as a single comment from the user’s GitHub account (not a review; the launch dialog still confirms in interactive sessions, while non-interactive mode posts on the flag alone) and --no-post hides that option.

日本語の概要は準備中です。原文の説明を表示しています。

Evaluate an Agent Skill bundle for structural integrity, trigger quality, artifact improvement, script correctness, safety, installed-tree integrity, and target-host portability before release.

日本語の概要は準備中です。原文の説明を表示しています。

Render-correctness doctrine for scene-to-scene seams in HyperFrames launch videos — the prerequisites that make transitions composite correctly on the master timeline. Load when assembling the master timeline / index.html, when a white flash appears at a cut or crossfade seam (especially on dark films), when reasoning about why a transition opacity dip shows through, or when verifying the render-side mechanics of how overlapping scene wrappers blend. Covers the opaque stage-ground (#root background) white-flash guard and how the injector overlaps wrappers, holds final frames, ping-pongs tracks, and stamps lint-clean template code onto the master timeline. Does NOT contain the per-transition catalog — see the transition registry for individual transition entries.

日本語の概要は準備中です。原文の説明を表示しています。

Handles LLM-as-judge evaluation workflows on Arize including creating/updating evaluators, running evaluations on spans or experiments, managing tasks, trigger-run operations, column mapping, and continuous monitoring. Use when the user mentions create evaluator, LLM judge, hallucination, faithfulness, correctness, relevance, run eval, score spans, score experiment, trigger-run, column mapping, continuous monitoring, or improve evaluator prompt.

日本語の概要は準備中です。原文の説明を表示しています。

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.

日本語の概要は準備中です。原文の説明を表示しています。

Assess a GitHub issue or PR for demonstrated need, supported alternatives, correctness, and maintainer action. Desk review only.

日本語の概要は準備中です。原文の説明を表示しています。

Review code changes for security, performance, and correctness. Trigger with a PR URL or diff, "review this before I merge", "is this code safe?", or when checking a change for N+1 queries, injection risks, missing edge cases, or error handling gaps.

日本語の概要は準備中です。原文の説明を表示しています。

Edit any video by conversation. Transcribe, cut, color grade, generate overlay animations, burn subtitles — for talking heads, montages, tutorials, travel, interviews. No presets, no menus. Ask questions, confirm the plan, execute, iterate, persist. Production-correctness rules are hard; everything else is artistic freedom.

日本語の概要は準備中です。原文の説明を表示しています。

Review code for actionable defects. Correctness is the core; performance and security are optional sub-cases of the same engine. Anchors on agreements between participants across a boundary, forces a violating execution, and refutes every candidate before reporting. Use when asked to review changes, find bugs, audit a codebase, or check whether a fix is safe.

日本語の概要は準備中です。原文の説明を表示しています。

Validate skill files for structural compliance and behavioral correctness. Four modes: static linter, spec, category rubric, audit.

日本語の概要は準備中です。原文の説明を表示しています。

Verify the OpenSEO MCP server end-to-end on a local dev server — protocol-level correctness against real DataForSEO, then a headless-agent consumer probe that tests tool ergonomics (descriptions, schemas, output size, errors, async flows) without the maintainer manually driving an MCP client. Use after adding or changing MCP tools, or when asked to check that the MCP "works" or "is ergonomic".

日本語の概要は準備中です。原文の説明を表示しています。

Review Apache ShardingSphere or user-authorized downstream pull requests and PR discussions from public or authorized repository evidence. Use for code-correctness or mergeability decisions, CI-focused review, root-cause and regression analysis, complete consolidated findings, copy-ready committer feedback, challenged findings, multi-round review, and formal review of local implementation candidates in the repository completion loop.

日本語の概要は準備中です。原文の説明を表示しています。

Code review focused exclusively on over-engineering. Finds what to delete: reinvented standard library, unneeded dependencies, speculative abstractions, dead flexibility. One line per finding: location, what to cut, what replaces it. Use when the user says "review for over-engineering", "what can we delete", "is this over-engineered", "simplify review", or invokes /ponytail-review. Complements correctness-focused review, this one only hunts complexity.

日本語の概要は準備中です。原文の説明を表示しています。

Review code changes for correctness, clarity, and potential issues. Use when the user asks for a review, code review, PR review, or wants feedback on a diff or file.

日本語の概要は準備中です。原文の説明を表示しています。

Writes, debugs, and refactors JavaScript code using modern ES2023+ features, async/await patterns, ESM module systems, and Node.js APIs. Use when building vanilla JavaScript applications, implementing Promise-based async flows, optimising browser or Node.js performance, working with Web Workers or Fetch API, or reviewing .js/.mjs/.cjs files for correctness and best practices.

日本語の概要は準備中です。原文の説明を表示しています。

Analyzes code diffs and files to identify bugs, security vulnerabilities (SQL injection, XSS, insecure deserialization), code smells, N+1 queries, naming issues, and architectural concerns, then produces a structured review report with prioritized, actionable feedback. Use when reviewing pull requests, conducting code quality audits, identifying refactoring opportunities, or checking for security issues. Invoke for PR reviews, code quality checks, refactoring suggestions, review code, code quality. Complements specialized skills (security-reviewer, test-master) by providing broad-scope review across correctness, performance, maintainability, and test coverage in a single pass.

日本語の概要は準備中です。原文の説明を表示しています。

Use only when the user explicitly asks to fix and verify a validated or plausible security vulnerability. Do not use for ordinary bug fixes, correctness or design review findings, general validation, or full PR, commit, branch, patch, or repository scans.

日本語の概要は準備中です。原文の説明を表示しています。

Deep file-focused code review for correctness bugs. Unlike shallow-review which runs 6 specialists in parallel across the entire patch, deep-review focuses on user-specified files with full pattern catalogs (500+ patterns), codebase investigation, and source-level context gathering. Use when: the user specifies particular files for focused review, a shallow review flagged areas that need deeper investigation, reviewing critical-path code changes, examining complex serialization/lifecycle/state-machine changes. The user instructs which files to focus on (typically a subset of files in the patch).

日本語の概要は準備中です。原文の説明を表示しています。

Audit a datafusion-spark function implementation for correctness against Apache Spark 4.2.0. Studies the Spark source across versions, reviews the Rust implementation and its signature, verifies expected values against a real PySpark, fixes divergences, and captures the rest as issues and disabled tests.

日本語の概要は準備中です。原文の説明を表示しています。

Use only when the user explicitly asks to fix and verify a validated or plausible security vulnerability. Do not use for ordinary bug fixes, correctness or design review findings, general validation, or full PR, commit, branch, patch, or repository scans.

日本語の概要は準備中です。原文の説明を表示しています。

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

日本語の概要は準備中です。原文の説明を表示しています。