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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.

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Review a verdaccio diff, branch, or pull request against the repository review guide (security first, then npm-client compatibility, performance, product fit, maintainability), verify each finding against the code, and report actionable issues. Use for code reviews and for reviewing your own changes before or during a PR workflow.

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 an existing verdaccio/verdaccio pull request end to end — description, diff, review threads, CI, labels, changeset, release-line coverage — verify the findings, and report them; optionally fix them on the PR branch when asked. Use when given a PR number or URL to review, re-review, or "review and fix".

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。

飞书云空间（云盘/云存储）：管理 Drive 文件和文件夹，包含上传/下载、创建文件夹、复制/移动/删除、查看元数据、查询权限设置、评论/权限/订阅、标题、版本、飞书文档密级标签（secure labels）和本地文件导入。用户需要整理云盘目录、处理云空间资源 URL/token、判断链接类型/真实 token/标题，或导入 Word/Markdown/Excel/CSV/PPTX/.base 为 docx/sheet/bitable/slides 时使用；doubao.com 云空间 URL/token 也按资源路径和 token 路由，不回退 WebFetch。不负责：文档内容编辑（走 lark-doc）、表格/Base 表内数据操作（走 lark-sheets/lark-base）、知识空间节点/成员管理（走 lark-wiki）、原生 Markdown 文件读写/patch/diff（走 lark-markdown）。

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。

Turn a refined research proposal or method idea into a detailed, claim-driven experiment roadmap. Use after `research-refine`, or when the user asks for a detailed experiment plan, ablation matrix, evaluation protocol, run order, compute budget, or paper-ready validation that supports the core problem, novelty, simplicity, and any LLM / VLM / Diffusion / RL-based contribution.

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。

Automated PR review and CI auto-fix for GitHub and GitLab using the Composio CLI. Pulls diffs, fetches failing job logs, posts review comments, and loops fix commits until checks go green.

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。

Perform a read-only, defect-first review of a specified code change and return every actionable finding. Use when another agent delegates review of uncommitted changes, a base-branch diff, a commit, or custom review instructions.

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。

Build multiple genuinely different versions of a UI piece you describe, rendered behind a visual picker so you can flip through them live and promote the one that feels right. Only runs when explicitly invoked; it does not trigger on its own.

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。

Survey a codebase's animation and motion code as a senior motion advisor, then produce a prioritized audit and self-contained implementation plans for other agents (or cheaper models) to execute. Read-only on source code — it plans improvements, it does not apply them. Use when the user asks to "improve the animations", "audit the motion", "make this app feel better", or wants a roadmap of animation fixes rather than a review of a single diff.

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。

Replays a CARLA .log recorded by the recorder — the whole run or a time window, at any speed, following a chosen actor, optionally regenerating sensors and restoring weather. Use when the user asks to "replay the recording", "play back the run", "watch it again in slow motion / at 2x", "follow vehicle N during replay", or "replay onto a different map".

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 an autonomous agent for the CARLA Leaderboard — an AutonomousAgent subclass with setup/sensors/run_step/destroy, a sensor suite inside the track's budget, and the right constructor signature for the leaderboard version (1.0 and 2.x differ). Generates a working skeleton, validates the sensor configuration against the real per-track limits offline, and covers the ROS1/ROS2 agent base classes. Use when the user asks to "write a leaderboard agent", "make my agent work with the leaderboard", "add sensors to my agent", "port my agent to 2.1", or hits SensorConfigurationInvalid.

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。

Reads a CARLA Leaderboard results.json — per-route driving score, route completion, infraction penalty and the infraction lists — explains how the score was computed for that leaderboard version, and rescores an existing result under the other version's rules (2.0 multiplicative vs 2.1 additive) without re-running anything. Also diffs two runs and merges sharded result files. Use when the user asks "what did I score", "why is my score low", "did my agent pass", "why don't my scores match the leaderboard", or hands over a results.json.

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。

Fine-tunes and evaluates OpenVLA-OFT and OpenVLA-OFT+ policies for robot action generation with continuous action heads, LoRA adaptation, and FiLM conditioning on LIBERO simulation and ALOHA real-world setups. Use when reproducing OpenVLA-OFT paper results, training custom VLA action heads (L1 or diffusion), deploying server-client inference for ALOHA, or debugging normalization, LoRA merge, and cross-GPU issues.

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。

Independent verification agent for loop-produced changes. Finds reasons to reject. Runs tests. Confirms diff scope. Use after minimal-fix or any implementer sub-agent — never in the same role as the implementer.

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 an immutable patch artifact's program impact, regression risk, and auto-merge eligibility. Use for generated patch files, provider pull-request diffs, or commit ranges when reviewers need evidence about affected runtime paths, contracts, tests, and recoverability. This skill is read-only and does not generate, edit, apply, push, or merge 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。

Review an existing fix PR using the audited repro and full diff, preserving branch and approval rules.

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 Omnigent CLI's setup/onboarding flow, terminal UI/UX, and critical user journeys in a completely isolated, reproducible loop. Drives the real `omnigent` binary through a PTY (pexpect) inside a throwaway OMNIGENT_CONFIG_HOME / OMNIGENT_DATA_DIR sandbox that never touches the user's real ~/.omnigent, captures ANSI-stripped frames for UX inspection, and proves a change is verifiable via a before→fix→after baseline diff. Load when developing or reviewing a CLI setup/onboarding/REPL/picker change (omnigent/cli.py, omnigent/onboarding/*, omnigent/repl/*, scripts/install_oss.sh), reproducing a cold-start/first-run UX bug, or confirming a fix actually lands. Several agents can run it concurrently on separate worktrees.

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。

Check the full candidate diff, affected consumers, focused tests, evidence identities, and verification 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。

Generate self-contained HTML visual explanations for systems, code changes, plans, data, and technical concepts. Use for diagrams, architecture overviews, diff or plan reviews, project recaps, comparison tables, slide decks, animated explainers, narrated MP4 videos, and other visual explanations.

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 code analysis with ASCII visualizations showing structure, flow, and state transitions. Use when analyzing patches/diffs, explaining classes or subsystems, understanding code architecture, reviewing changes for inconsistencies, or when asked to visualize how code works. Provides before/after diagrams, data/control flow, concurrency analysis, assumptions, and failure modes. Triggers on explain this patch/code/class, how does X work, show me the flow, visualize this change, code review requests, or proactive analysis during PR reviews.

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。

Multi-pass deep code review for large patches (1000+ LOC) that maximizes real bug detection. Orchestrates targeted-review, shallow-review, and deep-review in parallel across all HIGH and MEDIUM risk files and commits: understands the feature holistically, splits by file and commit, runs deep review on every HIGH/MEDIUM file, targeted review across the same scope, and per-commit shallow review, followed by cross-cut consistency checks. Use when: reviewing a large patch (feature branch, multi-commit, or single large diff, 1000+ LOC), doing a thorough pre-merge review, or when shallower reviews miss bugs due to patch size. Triggers on: "review this branch", "review these commits", "review this feature", "mega review", "thorough review", "full review of X commits", or when the user specifies a commit range or feature for review.

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。

Comprehensive guide for writing Apache Cassandra in-JVM distributed tests (dtests). Use when creating tests that simulate multi-node Cassandra clusters within a single JVM for faster integration testing. Covers cluster creation (single-node, multi-node, multi-datacenter), configuration (all cassandra.yaml parameters, features, network topology), instance lifecycle (startup/shutdown/restart), query execution, message filtering for failure scenarios, running code on instances, ClusterUtils utilities, and debugging classloader-related issues (serialization failures, same-class-different-classloader problems).

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。

Write or review Apache SeaTunnel E2E (Testcontainers) and unit tests so they are stable, leak-free, and deterministic. Use when creating a new *IT/*Test class, reviewing a test diff, or refactoring a flaky or leaking test.

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。