“json schema”的搜索结果

Query UniProt's REST API (post-2022 endpoint at rest.uniprot.org) for protein sequences, annotations, GO terms, cross-references, ID mappings, and proteomes. Use when fetching UniProtKB entries, navigating the JSON schema, choosing between UniProtKB/UniRef/UniParc/Proteomes resources, deciding stream vs search endpoint for batch retrieval, running ID-mapping jobs with the async pattern, handling isoform suffixes, or filtering reviewed Swiss-Prot vs auto-annotated TrEMBL. Encodes the legacy URL migration (2022), the new JSON schema layout, and bulk-pull patterns.

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Query UniProt's REST API (post-2022 endpoint at rest.uniprot.org) for protein sequences, annotations, GO terms, cross-references, ID mappings, and proteomes. Use when fetching UniProtKB entries, navigating the JSON schema, choosing between UniProtKB/UniRef/UniParc/Proteomes resources, deciding stream vs search endpoint for batch retrieval, running ID-mapping jobs with the async pattern, handling isoform suffixes, or filtering reviewed Swiss-Prot vs auto-annotated TrEMBL. Encodes the legacy URL migration (2022), the new JSON schema layout, and bulk-pull patterns.

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Data structures and serialization formats for agent-to-agent communication. Covers message envelopes, structured output schemas, capability declarations, task handoff payloads, error/retry signaling, and context windows as data structures. Compares the version-pinned A2A, MCP, and JSON-RPC role boundaries covered by this bundle; OpenAI and LangChain-specific APIs require their own current sources. Teaches when to use rigid schemas versus free-form content with validation, typed versus untyped boundaries, and streaming versus batch. Activate on: "agent message format", "agent communication schema", "agent-to-agent protocol", "A2A protocol", "MCP message format", "structured output for agents", "agent interop", "interchange format", "agent serialization", "task handoff format", "capability declaration". NOT for: what agents say to each other (use agent-conversation-protocols), orchestration topology (use multi-agent-coordination), building agent infrastructure (use agentic-infrastructure-2026).

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docs/PLAN/{YYMMDD}_{slug}/ の schema v3 仕様書を Codex で Gate 単位に実行する。 tasks.json を正とし、Gate 契約 (Goal/Constraints/AC) に基づいて実装・検証・レビューを行う。 Trigger: spec-codex-run, spec-run

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Designs robust function/tool calling schemas for LLMs with JSON schemas, validation strategies, typed interfaces, and example calls. Use when implementing "function calling", "tool use", "LLM tools", or "agent actions".

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Generate validated JSON-LD structured data markup for any page type

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检查MySQL和MariaDB的表设计与慢SQL，审视索引、更新事务、连接管理和复制延迟，整理具体修改建议与验证步骤，并考虑权限和通信保护。

• 设计数据库表与索引
• 调查慢SQL和死锁
• 审查大型生产表的变更

提供使用Kotlin和JetBrains Exposed实现数据库查询与增删改的模式，涵盖连接复用、结构变更管理、事务、数据访问分离及测试。

• 实现数据库查询与更新
• 配置数据库连接复用
• 管理数据库结构变更

Review author information in structured data, a machine-readable description of page content. Check names, profile links, and connections to articles or pages, then identify corrections using the rendered HTML and HTTP response.

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• Check author data on article pages
• Connect authors to external profiles
• Review author markup in page templates

Design tools that AI agents can choose and use correctly. Define clear descriptions, inputs, and outputs, manage large search results, and plan approval checks, isolated execution environments, and interfaces for collaboration between agents.

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• Reviewing the scope of tools for an MCP server
• Improving tool descriptions and input examples
• Designing pagination and truncation for search results

Build and debug Apify Actors, cloud programs for web scraping, automation, and data processing. Get guidance on language templates, input and output schemas, runtime code, local testing, and deployment, with practices for handling credentials and external data.

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• Creating an Actor for web scraping
• Defining Actor inputs and structured outputs
• Debugging an Actor with local test data

Guide Prisma 8 development by selecting task-specific references for data definitions, queries, migrations that change database structure, runtime setup, debugging, and upgrades. Check package versions and generated contract files before proceeding with implementation.

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• Set up Prisma 8 or connect it to an existing database
• Edit data definitions and plan database migrations
• Write queries and configure database connections

Run diffusers generation pipelines from a terminal and save their outputs. Inspect accepted inputs without downloading model weights, apply LoRA adapters during generation, run remotely through HF Jobs, and inspect software and GPU environment details.

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• Running one-off generation or batch jobs from a terminal
• Checking a new model's basic operation
• Inspecting accepted inputs before running a pipeline

Work with Gmail through an agent to send, read, reply to, and forward emails. Review unread messages, monitor incoming mail, and access commands for managing drafts, labels, threads, and mailbox settings.

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• Reviewing unread senders, subjects, and dates
• Replying to everyone in an email thread
• Forwarding a message to new recipients

Review database structures and relationships, identify design issues, and generate relationship diagrams. The skill recommends indexes, which help queries find data efficiently, and prepares migration steps with validation and rollback planning.

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• Reviewing table structures and relationships
• Improving indexes for frequent queries
• Planning database changes without downtime

Scope a Claude Managed Agent through six questions about its job, trigger, inputs, actions, success criteria, and recurrence. Produce a validated build sheet with configuration components, deferred features, and an evaluation plan, without requiring an API key.

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• Turn an agent idea into a concrete build plan
• Define success criteria before implementation
• Separate the initial scope from later integrations

Guides development and releases for Kortix Capture, a standalone recording app. Covers installers for Windows, macOS, and Linux, app behavior, sync troubleshooting, and coordinated changes to the recording storage format and its tests.

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• Prepare or troubleshoot a Capture release
• Update installers for supported operating systems
• Investigate sync failures on a self-hosted instance

Delegate coding, analysis, refactoring, or reviews from Claude Code to Codex CLI. The skill explains unattended execution, permission settings, output capture, parallel tasks, and independent checks of changed files and test results.

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• Delegate implementation while retaining planning responsibility
• Get a second opinion on code changes
• Split independent tasks across separate git worktrees

Evaluate AI agent outputs with code checks and model-based grading. Run repeated trials to measure reliability, compare prompts or models, and check whether changes reduce quality, with saved transcripts for reviewing the results.

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• Comparing two prompts on the same test cases
• Checking quality after agent configuration changes
• Turning real failures into repeatable evaluation cases

Create search-focused product comparison and alternatives pages with balanced feature analysis and pricing tables. Get a page outline, keyword strategy, structured data that describes the content to search engines, and suggestions for placing calls to action.

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• Create a side-by-side product comparison page
• Plan a page introducing alternatives to a service
• Build a feature and pricing comparison table

Turn an OpenAPI or Swagger specification into an MCP server, a bridge that lets AI assistants call an API. Covers tool generation, authentication, local testing, and deployment to mcp-use cloud.

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• Make an internal API callable from Claude
• Generate MCP tools from a Swagger specification
• Test API calls locally before cloud deployment

Design and maintain applications where OpenRig agents help run the system. Organize instructions, shared state, and artifact checks, then trace unexpected behavior to the code, skill, or schema that needs repair.

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• Designing an application operated by OpenRig agents
• Organizing instructions and shared application state
• Tracing unexpected behavior to its source

Create and edit EAS workflow YAML files to automate builds and deployments for Expo projects. Check required settings, job dependencies, and dynamic values against the latest schema, which defines the accepted configuration.

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• Create an automated build workflow for an Expo project
• Edit EAS deployment automation
• Check workflow settings and job dependencies

Create, audit, and improve pages for AI search engines by checking crawl access, metadata, clear answers, sources, and structured data that describes page content. It produces prioritized fixes and citation-friendly pages without guaranteeing inclusion in AI answers.

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• Audit a blog for AI search visibility
• Create an article page with clear answers and supporting sources
• Fix metadata and structured data on existing pages