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概要と使いどころ
The official AWS Labs MCP server collection provides AI agents with structured access to AWS documentation, service APIs, billing data, and infrastructure metadata through the Model Context Protocol, built and maintained by AWS for secure cloud automation workflows.
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mcp-atlassian is a Model Context Protocol server that connects AI assistants to Atlassian Jira and Confluence. It enables searching and managing Jira issues, reading and editing Confluence pages, and performing project management tasks through natural language via any MCP-compatible client.
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Extracts and transforms Avro, Protobuf, and JSON Schema definitions from Confluent Schema Registry. Generates typed data models and validates schema compatibility using the Schema Registry REST API.
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Generates Airbyte source and destination connector configurations using the Airbyte API /v1/sources/create and /v1/destinations/create endpoints. Validates connection specs against the Airbyte Protocol.
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。
Agno is a high-performance Python framework for building, running, and managing agentic software at scale. It provides a three-layer architecture — framework, runtime, and control plane — enabling developers to go from agent prototype to production API in roughly 20 lines of code.
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Expert product discovery guidance for user research and problem validation. Use when conducting user interviews, validating problems, applying jobs-to-be-done framework, sizing opportunities, customer segmentation, competitive analysis, prototype testing, usability testing, designing surveys, or synthesizing research insights. Covers discovery sprints, continuous discovery, and research operations.
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Babel internal issue protocol — close a handoff after downstream agent picked it up or user signed off. Moves designs/<name>/.handoff/<label>.md to .handoff/closed/ (using mv per CLAUDE.md), appends to handoff_log.jsonl.
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Babel internal issue protocol — create a labeled handoff between pipeline agents. Writes designs/<name>/.handoff/<label>.md and appends to handoff_log.jsonl; best-effort gh issue create if gh available. Triggered by every guru/architect agent at handoff 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。
读取指定 CBB / protocol wiki 文件，解析其 ## Interface / ## Ports section，返回结构化端口表 + 参数表。bba-architect 用于填入 MAS 模块接口。触发场景：(1) bb-search-cbb 命中后取详细接口；(2) 显式 /bb-get-interface-template。
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。
Babel internal issue protocol — list open handoffs by label. Scans designs/*/.handoff/*.md (filtered by label) and best-effort merge with gh issue list. Used by all guru/architect agents at startup to pick up work.
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Use when uncommitted changes need to be split into atomic, conventional commits ordered for review. Triggers on "commit this", "make commits", "clean up commits", "commit the changes". In Hedgehog, each Loop step is already meant to be its own commit — this skill matters most when a Correction Protocol fast-forward touches several steps at once and those fixes need splitting back into per-step commits.
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 .NET AI agents and multi-agent workflows with Microsoft Agent Framework using the right agent type, threads, tools, workflows, hosting protocols, and enterprise guardrails.
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Structures IAC/LPAC design with composition, authority scope, conflict review protocols, and valuation oversight. Use when designing advisory committees, defining LPAC authority, or structuring conflict resolution processes.
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。
How agents discover and use skills. Use to understand skill invocation protocol.
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 that implementation code faithfully implements its specification — checks function contracts, API contracts, and protocol compliance against source specifications
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。
Agent task delegation patterns — spawn protocols, handoff metadata, drain gate, parallel limits, and model selection for multi-agent orchestration
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Workflow recovery protocol for resuming workflows after context loss, session interruption, or errors. Handles state reconstruction, artifact recovery, and seamless workflow continuation.
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。
Entity and relation tracking skill using MCP memory server patterns and local knowledge graph storage. Build persistent knowledge graphs of entities, relationships, and observations across agent sessions. Covers the MCP memory server (@modelcontextprotocol/server-memory), local JSON-based graphs, and entity-relation querying patterns for long-running agents.
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Autonomous fixed-budget ML experiment loop — setup, iterative hypothesis testing, git-based keep/discard tracking, and indefinite autonomous execution. Implements the karpathy/autoresearch protocol.
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Byzantine consensus voting for multi-agent decision making. Implements voting protocols, conflict resolution, and agreement algorithms for reaching consensus among multiple agents.
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。
Discover, parse, and call external HTTP APIs at runtime using OpenAPI specs, tool templates, and iterative chaining. Adapted from UTCP (Universal Tool Calling Protocol) patterns for Node.js and Claude Code agents.
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Hunt Server-Side Request Forgery (SSRF) — internal network access, cloud metadata exploitation, gopher/file/dict protocol abuse, and 11 IP-filter bypass techniques. Use when an endpoint accepts a URL, hostname, or file path as input.
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Technical SEO audit across 9 categories: crawlability, indexability, security, URL structure, mobile, Core Web Vitals, structured data, JavaScript rendering, and IndexNow protocol. Use when user says "technical SEO", "crawl issues", "robots.txt", "Core Web Vitals", "site speed", or "security headers".
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。
Configure and manage MCP (Model Context Protocol) servers in Claude Code CLI. Use this skill when adding, removing, listing, or troubleshooting MCP servers, or when questions arise about MCP configuration, transport types, scopes, or authentication. Essential for connecting Claude Code to external tools, databases, and APIs.
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。