A scoring scale for evaluating how well a CLI is designed for AI agents, based on the "Rewrite Your CLI for AI Agents" principles.
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。
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概要と使いどころ
A scoring scale for evaluating how well a CLI is designed for AI agents, based on the "Rewrite Your CLI for AI Agents" principles.
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。
Adopt better-result in an existing TypeScript codebase. Use when replacing try/catch, Promise rejection handling, null sentinels, or thrown domain exceptions with typed Result workflows.
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。
Knip dead code detection best practices for JavaScript and TypeScript projects. Use when configuring Knip, analyzing unused code, setting up CI integration, or cleaning up codebases. Triggers on knip.json, dead code, unused exports, unused dependencies, bundle optimization.
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。
Resolve Drizzle migration merge/rebase conflicts in OneQuery by rewinding local-only migration history and regenerating migration metadata. Use when conflicts involve packages/db/src/migrations/meta/_journal.json, migration SQL files in packages/db/src/migrations/*.sql, or migration snapshots in packages/db/src/migrations/meta/*_snapshot.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。
Score a repository's agentic legibility from repo-visible evidence only. Use when Codex needs to audit how easy a codebase is for coding agents to discover, bootstrap, validate, and navigate, especially for harness-engineering reviews, developer-experience audits, repo cleanup, or before/after comparisons after improving docs, tooling, or architectural constraints.
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。
Guide for writing idiomatic Rust code based on Apollo GraphQL's best practices handbook. Use this skill when: (1) writing new Rust code or functions, (2) reviewing or refactoring existing Rust code, (3) deciding between borrowing vs cloning or ownership patterns, (4) implementing error handling with Result types, (5) optimizing Rust code for performance, (6) writing tests or documentation for Rust projects.
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。
以固定的九节结构生成美国司法意见书的详细法学院案件简报:记忆钩子、事实、程序历史、 法官投票、判决要旨、逐意见分析、五个未来适用假设情形、评论和已核实的关键引文。 还构建投票表、跨案件一致性表、基于视角的评论,以及 article、Beamer 和案例教科书章节格式的 LaTeX。 当有人要求简报案件、分析或解释意见、为学生总结决定、从判决要旨生成假设情形、 评论判决、制表法官投票方式,或将案件分析转换为 LaTeX 时使用。触发词包括 "brief this case"、"case brief"、"explain the holding"、"what did the court hold"、 "hypotheticals based on"、"critique this opinion"、"vote table"、"Beamer presentation"、 "chapter brief",以及在教学情境中对司法意见或最高法院决定的任何引用。 需要网络搜索来核实引文、投票和判决要旨。
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。
Drafts an Appellee's Response Brief defending the trial court's judgment and arguing for affirmance. Covers standard of review analysis, record-based rebuttal, authority distinction, and procedural compliance. Trigger when drafting appellee briefs, response briefs, answering briefs, or defending trial court judgments on appeal.
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。
Manages intent — features, enhancements, bugs and the reasoning behind them — recorded as prose in the knowledge base with a lifecycle. Use when capturing new work, moving work through backlog, refinement or implementation, releasing or cancelling work, or asking what is pending, in flight, or no longer valid.
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。
Compare two local documents and convert differences into LLM-ready Markdown in one synchronous call. Supports PDF, Word, PPT, and image documents accepted by Calliper, and returns a structured markdown diff table suitable for change review, clause comparison, downstream extraction, and rule-based validation.
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 when building data pipelines, ETL jobs, event processors, message-broker producers/consumers, application caching layers, database migrations, BigQuery queries, or event-sourcing handlers in TypeScript. Triggers on edits to indexer/ETL/migration code, Prisma or Drizzle schemas, BigQuery integration code, RabbitMQ/Kafka/SQS/BullMQ producer or consumer code, Redis cache wrappers, or mentions of "data engineering", "ETL", "pipeline", "indexer", "event sourcing", "data warehouse", "data migration", "message queue", "RabbitMQ", "Kafka", "SQS", "BullMQ", "Redis cache", or "caching".
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 when building games or interactive software in Godot 4 with C# — designing scenes and nodes, writing gameplay code, handling input, physics, animation, UI, rendering, save systems, performance work, WebSocket-based multiplayer, or exporting to platforms. Triggers on "Godot", "GDScript", "C# Godot", "scene tree", Godot node types (Node2D, Node3D, Control, CharacterBody), "_Process", "_PhysicsProcess", "signal", "autoload", "RPC", "WebSocketMultiplayerPeer", "shader", "export preset", or any Godot 4 project files. For game design see game-systems-designer; for balance see game-balancer; for game-specific intake see game-design-shaper.
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 when writing, reviewing, or deploying Solidity smart contracts — token contracts, signature-gated claim systems, merkle-gated staking vaults, allocation modules, role-based proxies, or factory patterns. Triggers on edits to `*.sol` files, `hardhat.config.*`, `foundry.toml`, deploy scripts, or mentions of "smart contract", "Solidity", "Web3", "EVM", "Hardhat", "Foundry", "ERC20/721/1155", "merkle", "staking", or "on-chain". For security audits and adversarial review see security-engineering.
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。
Appwrite Rust SDK skill. Use when building server-side Rust applications with Appwrite. Covers async client setup with API keys, user management, TablesDB database/table/row operations, file storage, function executions, permissions, queries, and error handling. Uses the crates.io `appwrite` package and Tokio.
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。
Appwrite Ruby SDK skill. Use when building server-side Ruby applications with Appwrite, including Rails and Sinatra integrations. Covers user management, database/table CRUD, file storage, and functions via API keys.
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。
Appwrite CLI skill. Use when managing Appwrite projects from the command line. Covers installation, login, project initialization, multi-file project configuration, deploying functions/sites/tables/buckets/teams/webhooks/topics, flag-based list queries, non-interactive CI/CD mode, and generating type-safe SDKs.
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。
Appwrite .NET SDK skill. Use when building server-side C# or .NET applications with Appwrite, including ASP.NET and Blazor integrations. Covers user management, database/table CRUD, file storage, and functions via API keys.
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。
Appwrite Go SDK skill. Use when building server-side Go applications with Appwrite. Covers user management, database/table CRUD, file storage, and functions via API keys. Uses per-service packages and functional options pattern.
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。
Appwrite PHP SDK skill. Use when building server-side PHP applications with Appwrite, including Laravel and Symfony integrations. Covers user management, database/table CRUD, file storage, and functions via API keys.
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。
Appwrite Python SDK skill. Use when building server-side Python applications with Appwrite, including Django, Flask, and FastAPI integrations. Covers user management, database/table CRUD, file storage, and functions via API keys.
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 auditor that grades software projects and the agents/developers who built them. Produces structured JSON + Markdown reports with a standardized rubric. Evaluates architecture, correctness, testing, authorship cohesiveness, ghost code, and more. Optionally ingests tmux session logs for process evidence and interrogates agents about specific problems found. Use when asked to "audit", "grade", "evaluate", "review code quality", "rate this project", "score the agents", or "assess the codebase". Especially useful after Marcus multi-agent experiments to grade agent output and track quality over time.
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。
Launch Marcus multi-agent experiments with independent CLI agents in tmux panes. Use when the user says "build X with Marcus", "run a Marcus experiment", "spawn N agents with Marcus", "/marcus", or references the Marcus multi-agent framework. This skill handles experiment setup, config generation, and spawning independent agent CLI processes that coordinate via the Marcus MCP server. Each agent runs in its own tmux pane with full autonomy. NOT for ClawTeam — this is specifically for the Marcus MCP-based multi-agent system. NOTE: "Marcus" is also the name of the MCP server that agents use for coordination. The /marcus skill launches experiments that USE the Marcus MCP server — they are complementary, not competing. The MCP server must be running before invoking this skill. The Marcus MCP server is agent-agnostic; this skill supports Anthropic's claude CLI, OpenAI's codex CLI, and Google's gemini CLI as agent harnesses (selected via --harness).
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。
Dr. Kaia Chen - AI Architect, mentor, and strategic advisor for Marcus. Use when the user says "Kaia", "Dr. Chen", "ask Kaia", "/kaia", or wants architectural advice, trade-off analysis, production readiness guidance, mentorship, a voice of reason, or a second opinion on design decisions. Kaia grounds her advice in the actual codebase (via Chen MCP tools) and research literature, and logs important decisions and insights via Simon.
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。
Launch Marcus multi-agent experiments with independent CLI agents in tmux panes. Use when the user says "build X with Marcus", "run a Marcus experiment", "spawn N agents with Marcus", "/marcus", or references the Marcus multi-agent framework. This skill handles experiment setup, config generation, and spawning independent agent CLI processes that coordinate via the Marcus MCP server. Each agent runs in its own tmux pane with full autonomy. NOT for ClawTeam — this is specifically for the Marcus MCP-based multi-agent system. NOTE: "Marcus" is also the name of the MCP server that agents use for coordination. The /marcus skill launches experiments that USE the Marcus MCP server — they are complementary, not competing. The MCP server must be running before invoking this skill. The Marcus MCP server is agent-agnostic; this skill supports both Anthropic's claude CLI and OpenAI's codex CLI as agent harnesses (selected via --harness).
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。