'json validation' 검색 결과

Configuration module patterns for LlamaFarm. Covers Pydantic v2 models, JSONSchema generation, YAML processing, and validation.

한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.

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.

한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.

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.

한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.

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.

한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.

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).

한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.

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.

한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.

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

한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.

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.

한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.

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.

한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.

Create, compose, migrate, and review TypeScript runtime type guards with is-kit. Use when adding reusable guards; replacing typeof, null checks, or handwritten type predicates; narrowing unknown values; validating JSON or API responses; building collection or object schemas with struct or typedStruct; or reviewing existing is-kit usage. Do not use for one-off environment checks or validation that requires data transformation or rich error reporting.

한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.

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.

한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.

Use when preparing a PlainTab release or bumping the PlainTab version, triggered by phrases like "更新版本", "bump version", "upgrade to vX.Y.Z", "发布新版本". Updates manifest.json, runtime UI/version constants, localized changelogs, store listings, release notes, validation notes, and current project docs.

한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.

Remix v2 data loading and mutations. Use when writing loaders, actions, deferred data, revalidation logic, or pending state. Triggers on loader, action, useLoaderData, useActionData, json(), defer(), <Await>, shouldRevalidate, useRevalidator, useNavigation, useTransition (v1 holdover).

한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.

Deterministic Software Graph analysis via Ontoly CLI and MCP. Use when: (1) Codebase architecture, dependency, route, service, module, configuration, or impact questions need graph evidence, (2) A repository should be analyzed before source search, (3) You need a persistent SoftwareGraph.json for validation, MCP, or agent workflows. Triggers: "build software graph", "trace route", "impact analysis", "architecture summary", "dependency graph", "what uses this", "Ontoly".

한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.

Workflow for publishing skills and agents to the dotnet-skills Claude Code marketplace. Covers adding new content, updating plugin.json, validation, and release tagging.

한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.

AI content generation with OpenAI and Claude, callAIWithPrompt usage, prompt storage in app_settings, structured outputs, response format validation, multi-criteria scoring, rate limiting, JSON schema, and AI API best practices. Use when generating content, creating prompts, scoring articles, or working with OpenAI/Claude APIs.

한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.

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

한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.

Guide for adding new LLM models to Letta Code. Use when the user wants to add support for a new model, needs to know valid model handles, or wants to update the model configuration. Covers models.json configuration, CI test matrix, and handle validation.

한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.

CRISP session manager — detects project state and routes to the right entry point. Use /crisp to start or resume any CRISP engagement. Handles new projects (discovery), existing codebases (archaeology), active sprints (execute), and validation (prove). Reads docs/crisp-state.json to know where you are.

한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.

Design a generative recipe DSL so agents emit small validated JSON documents and ONE audited interpreter renders them all — data, not code. Covers the N-artifacts threshold for choosing a DSL over bespoke code, designing roles as style slots so a single recipe renders unchanged in every output style, the validator gate (compile + bounds + real render in all styles, plus a --fast mode for corpus-wide sweeps), hand-authored seed recipes, and the emergent conventions that keep a corpus of hundreds consistent without per-item steering. Use when many similar artifacts (icons, status badges, diagram nodes, test fixtures) must be generated by agents, when per-item bespoke code is multiplying unreviewable code paths, or when a whole corpus must be re-rendered cheaply into new styles.

한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.

Research-backed hook refresh workflow for updating existing hooks with TDD checkpoints and settings.json registration validation.

한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.

Build with Aurora DSQL — manage schemas, execute queries, handle migrations, diagnose query plans, 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, FK replacement code generation, OCC retry patterns, ORM migration (Django/Hibernate/Rails), DDL operations, query plan explainability, SQL compatibility validation, and bulk data loading. 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.

한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.

Use when needing 100% type-safe, schema-valid data extraction from LLMs. Keywords: structured output, JSON schema, Pydantic, Zod, type-safe, constrained decoding, validation, tool use.

한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.

Fastify routes, JSON Schema validation, plugin system, TypeScript type providers

한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.