106 件 ・ 関連度順
概要と使いどころ
Build autonomous AI agents with Claude Agent SDK. Structured outputs guarantee JSON schema validation, with plugins system and hooks for event-driven workflows. Prevents 14 documented errors. Use when: building coding agents, SRE systems, security auditors, or troubleshooting CLI not found, structured output validation, session forking errors, MCP config issues, subagent cleanup.
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。
MySQLとMariaDBのテーブル設計や遅いSQLを見直し、インデックス、更新処理、接続管理、複製の遅延を点検して、修正案と検証手順をまとめるスキル。
文章やMermaidから、システム構成や業務の流れを操作できるHTML図に変換します。検索や関係の追跡、画像・動画への書き出しに対応し、9項目の検証結果も添えます。
Tools are how AI agents interact with the world. A well-designed tool is the difference between an agent that works and one that hallucinates, fails silently, or costs 10x more tokens than necessary. This skill covers tool design from schema to error handling. JSON Schema best practices, description writing that actually helps the LLM, validation, and the emerging MCP standard that's becoming the lingua franca for AI tools. Key insight: Tool descriptions are more important than tool implementa
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。
Translate one, multiple, or all explicitly requested FastGPT i18next namespace JSON files from the completed Simplified Chinese source into every supported target locale, with product-language research and structural validation. Use only when the user explicitly invokes `$i18n-translate` and identifies namespace names, files under `packages/web/i18n/zh-CN/`, or all namespaces; never trigger implicitly for ordinary i18n, copywriting, or documentation work.
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。
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).
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 JSON Schema definitions for MCP tool input parameters. Creates well-documented, AI-consumable schemas with proper types, descriptions, and validation 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。
Security considerations for Jackson JSON deserialization in Java applications. Covers timing of validation, raw input interception, and common deserialization attack patterns.
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。
Detect insecure JWT (JSON Web Token) implementations in a codebase using a two-phase approach: first map all JWT issuance and verification sites to understand the token lifecycle and signing configuration, then check each verification site for exploitable weaknesses such as algorithm confusion, missing signature verification, weak secrets, header injection, and missing claim validation. Requires sast/architecture.md (run sast-analysis first). Outputs findings to sast/jwt-results.md. If no JWT usage is found in Phase 1, Phase 2 is skipped. Use when asked to find JWT, token forgery, or authentication bypass bugs.
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。
Retrieve machine-readable context with tanstack libraries, tanstack doc, tanstack search-docs, tanstack create --list-add-ons --json, and --addon-details for agent-safe discovery and preflight 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。
Extract structured data matching a JSON schema from websites. Handles complex nested schemas, arrays, pagination, and validation. Always outputs via formatOutput.
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。
Workflow for publishing skills and agents to the dotnet-skills Claude Code marketplace. Covers adding new content, updating plugin.json, validation, and release tagging.
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。
MongoDB schema design patterns and anti-patterns. Use when designing data models, reviewing schemas, migrating from SQL, or troubleshooting performance issues caused by schema problems. Triggers on "design schema", "embed vs reference", "MongoDB data model", "schema review", "unbounded arrays", "one-to-many", "tree structure", "16MB limit", "schema validation", "JSON Schema", "time series", "schema migration", "polymorphic", "TTL", "data lifecycle", "archive", "index explosion", "unnecessary indexes", "approximation pattern", "document versioning".
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 with Aurora DSQL — manage schemas, execute queries, handle migrations, diagnose query plans, diagnose cluster performance, load data, and develop applications with a serverless, distributed SQL database. Covers IAM auth, multi-tenant patterns, MySQL-to-DSQL and PostgreSQL-to-DSQL schema conversion, foreign key constraints, OCC retry patterns, ORM migration (Django/EF Core/Hibernate/Rails/SQLAlchemy), DDL operations, query plan explainability, system diagnostics via CloudWatch AAS, SQL compatibility validation, and bulk data loading. Load before answering DSQL limit or error-code questions; it has limits docs omit. Triggers on phrases like: DSQL, Aurora DSQL, distributed SQL database, serverless PostgreSQL-compatible database, migrate to DSQL, DSQL query plan, DSQL EXPLAIN ANALYZE, DSQL ENUM, DSQL foreign key, DSQL OCC retry, DSQL multi-region, DSQL JSONB, DSQL GIN index, load into DSQL, load CSV into DSQL, bulk load DSQL, aurora-dsql-loader, DSQL slow, DSQL performance, DSQL wait events, DSQL AAS.
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。
Configuration module patterns for LlamaFarm. Covers Pydantic v2 models, JSONSchema generation, YAML processing, and 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。
Customise the prd-taskmaster plugin workflow via curated brainstorm questions. The AI asks, the user answers in plain English, and the skill writes their preferences to .atlas-ai/config/atlas.json. Future runs of prd-taskmaster read that file and apply user preferences to phase gates, validation strictness, default provider, preferred execution mode, and template choice. For deeper tweaks beyond the curated questions, users can hand-edit files in .atlas-ai/customizations/. Use when the user says "customise workflow", "customize workflow", "adjust my PRD settings", "tune the skill", or wants to change how prd-taskmaster behaves.
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 `pvanalyze` to inspect existing .NET `.nettrace` files from the command line, including GC, JIT, CPU stacks, allocation, DATAS, events, exceptions, timeline, and call-tree analysis with JSON or SpeedScope. USE FOR: the user mentions pvanalyze, PerfView-style CLI trace analysis, or cross-platform .nettrace inspection; the task starts from an existing .nettrace file and needs. DO NOT USE FOR: unrelated stacks; generic tasks that do not need this specific guidance. INVOKES: inspect the repository context, edit targeted files, and run relevant build, test, lint, or validation commands when changes are made.
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。
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).
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 the open-source free `StyleCop.Analyzers` package for naming, layout, documentation, and style rules in .NET projects. Use when a repo wants stricter style conventions than the SDK analyzers alone provide. USE FOR: the repo wants StyleCop.Analyzers; naming, layout, or documentation style needs stronger enforcement; the team needs stylecop.json guidance. DO NOT USE FOR: repos that intentionally rely only on SDK analyzers; repos where StyleCop overlaps too heavily with an existing style package and no. INVOKES: inspect the repository context, edit targeted files, and run relevant build, test, lint, or validation commands when changes are made.
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 `graphify-dotnet` to generate codebase knowledge graphs, architecture snapshots, and exportable repository maps from .NET or polyglot source trees, with optional AI-enriched semantic relationships. USE FOR: graphify commands; graph JSON, HTML, SVG, Cypher, Markdown, and Obsidian exports; repository map and architecture snapshot generation. DO NOT USE FOR: unrelated stacks; generic tasks that do not need this specific guidance. INVOKES: inspect the repository context, edit targeted files, and run relevant build, test, lint, or validation commands when changes are made.
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 you need framework-agnostic MongoDB and non-relational database query guidance — document schema design, collection modeling, JSON Schema validation, indexes, aggregation pipelines, query performance, consistency trade-offs, transactions, and operational safety — without choosing Spring Boot, Quarkus, or Micronaut. This should trigger for requests such as Design MongoDB document schemas; Review MongoDB queries and indexes; Improve aggregation pipeline performance; Model non-relational data access patterns; Review NoSQL consistency and transaction trade-offs. Part of Plinth Toolkit
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。
Thesis report synthesis — turn a thesis's markdown artifacts into its letter-size thesis-report.html, then OPTIMIZE it against real page renders. Four-step loop — pack (deterministic Python bundle of all sources + report/metrics.json), author (the LLM writes report/content.html — narrative, KPI tiles, badges, timeline, tables and citations are LLM judgment), assemble (deterministic validation, template injection, Q50 pins, Q47 overflow gate), render + optimize (Chrome headless per-page PNGs — the LLM reads them and iterates until every page is visually clean). Spec 046 Q46–Q50.
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 adding or changing tuning values, items, enemies, abilities or levels - put them in the engine's data assets (ScriptableObject, Resource, DataAsset/DataTable, JSON/RON) with validation and stable IDs, keep runtime state out of shared data, inject services instead of singletons, and test data invariants.
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 skill for building, migrating, and maintaining Astro v7 projects. Covers best practices from the official AGENTS.md, the v6→v7 migration path, validation of breaking/deprecated patterns, AI-enhanced dev server usage (background mode, JSON logging), advanced routing with src/fetch.ts, route caching, Sätteri Markdown, and the Rust compiler. Use when the user mentions 'Astro', '.astro files', 'astro dev', 'astro build', 'islands architecture', 'content collections', 'SSG', 'SSR adapter', 'upgrade to Astro 7', 'migrate Astro', 'Astro v7', 'Astro v6', 'Sätteri', 'route caching', 'Astro.cache', 'astro dev --background', 'src/fetch.ts', 'advanced routing', 'Hono + Astro', 'Rolldown', 'Vite 8', 'queued rendering', 'CDN cache provider', 'Astro AI', 'related content', 'related posts', 'vector embeddings Astro', 'astro-related-content', or asks about static site generation with Astro.
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。