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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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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。

Implement a JSON-RPC 2.0 A2A server with full task lifecycle management (submitted/working/completed/failed/canceled/input-required), SSE streaming, and push notifications. Use when implementing an agent that participates in multi-agent A2A workflows, building a backend for an Agent Card, adding A2A protocol support to an existing agent or service, or deploying an agent that must interoperate with other A2A-compliant 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。

State management decision tree for Vue 3 SPAs: ref/reactive locally, composables for shared logic, Pinia for app-wide state, provide/inject for DI, TanStack Query Vue for server state. Vuex pointer for Vue 2 legacy. Use this skill to: - Pick the right state tool for the data shape (local / shared / server / form). - Implement a Pinia store (Setup syntax preferred). - Use provide/inject correctly with InjectionKey<T>. - Set up TanStack Query Vue for server state. - Migrate from Vuex (with caution; only if BA asks). Do NOT use this skill for: - General SFC conventions (see vue-conventions). - Form state (see vue-forms — vee-validate handles that). - Routing state (see vue-routing — use vue-router useRoute). - Testing stores (see vue-testing).

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。

TanStack Start full-stack React framework best practices for server functions, middleware, SSR/streaming, SEO, authentication, and deployment. Use when building full-stack React apps with TanStack Start, implementing server functions, configuring SSR/streaming, managing SEO and head tags, setting up authentication patterns, or deploying to Vercel/Cloudflare/Node.

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。

Work with the @upstash/workflow TypeScript/JavaScript SDK for durable, long-running workflows in serverless functions, multi-step processes that survive timeouts, retries, and restarts (built on QStash). Use when defining a workflow endpoint with serve(), running steps with context.run, sleeping for minutes to days without holding a function open, calling external APIs with context.call, waiting for an external event or webhook, invoking other workflows, configuring retries, failure callbacks, and a DLQ, controlling concurrency, rate, and parallelism, triggering, cancelling, or inspecting runs with the Workflow client, building AI agents and orchestrators, human-in-the-loop approvals, realtime updates, local development with the QStash dev server, adding middleware, or migrating workflows safely. Also use when the user asks for durable execution, step functions, saga or orchestration patterns, background jobs with checkpoints, or long-running tasks on Vercel, Next.js, Cloudflare Workers, or other serverless platforms.

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。

Work with the @upstash/qstash TypeScript/JavaScript SDK, an HTTP-based message queue, task scheduler, and background job system for serverless and edge runtimes (Next.js, Vercel, Cloudflare Workers, Deno, Node.js). Use when publishing messages to HTTP endpoints or URL groups, running background jobs without a long-running worker process, scheduling with cron expressions, delaying messages, building FIFO queues with parallelism and flow control, configuring retries and callbacks, handling a dead letter queue (DLQ), deduplicating messages, fanning out to multiple endpoints, verifying QStash webhook signatures (Next.js App Router, Pages Router, and Edge Runtime), running a local QStash dev server, or migrating regions. Also use when the user asks for a serverless cron job, async task queue, job scheduler, delayed delivery, webhook delivery with retries, or event-driven messaging between services.

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。

Work with the @upstash/redis TypeScript/JavaScript SDK, a serverless HTTP-based Redis client for Next.js, Vercel, Cloudflare Workers, edge runtimes, and Node.js. Use when adding a cache (cache-aside, write-through, TTL and expiration strategies), session storage and user sessions, a key-value store, leaderboards and rankings with sorted sets, counters, distributed locks, queues with lists, streams and consumer groups, sparse index-addressed arrays and ring buffers (ARSET, ARINSERT, ARRING, ARGREP, AROP), embeddings and nearest-neighbour vector search stored inside Redis (VECTOR commands via redis.vector, separate from @upstash/vector), JSON documents, pipelines and MULTI/EXEC transactions, Lua scripting, read replicas, or full-text search, typo-tolerant search, facets, aggregations, and search over Redis stream entries with Upstash Redis Search (different from regular FT.SEARCH; also available for TCP clients via @upstash/search-redis and @upstash/search-ioredis). Also use when migrating from ioredis or node-redis, when a Redis connection is needed from a serverless function without connection pooling, when integrating @upstash/ratelimit, or when the user says Redis cache, KV store, session store, serverless Redis, or Upstash Redis. Also use when building AI agents on Redis with Upstash AgentKit (agent memory, chat history, RAG tools, tool caching, chat persistence, resumable streams, distributed locks) for the Vercel AI SDK, TanStack AI, or Vercel Eve. Supports automatic serialization/deserialization of JavaScript types.

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。

Work with any Upstash product, SDK, or tool, including serverless Redis (caching, sessions, leaderboards, key-value storage), Ratelimit (rate limiting and throttling), QStash (message queue, cron schedules, background jobs), Workflow (durable long-running functions), Vector (vector database for embeddings, semantic search, and RAG), Search (full-text and semantic search), Box (sandboxed cloud containers for AI agents, TypeScript/JavaScript and Python), Blob (serverless S3-compatible file storage with direct browser uploads), the Upstash CLI, and no-signup scratch Redis for agents. Use when the user mentions Upstash or needs any of these capabilities in a serverless, edge, or Node.js app.

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 scanner for AI Agent skills, plugins, and MCP servers. Use when: user asks to scan a skill, check if a plugin is safe, vet an MCP server, review skill security, detect malicious code, supply chain safety, or says 'is this safe to install', 'scan this skill', 'check this MCP server', 'security scan', 'vetting', 'skill safety', 'prism scan', '安全扫描', '这个插件安全吗', '扫描一下', '检查安全性', '安装前检查', '技能审查'.

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。

Manage Model Context Protocol (MCP) servers - discover, analyze, and execute tools/prompts/resources from configured MCP servers. Use when working with MCP integrations, need to discover available MCP capabilities, filter MCP tools for specific tasks, execute MCP tools programmatically, access MCP prompts/resources, or implement MCP client functionality. Supports intelligent tool selection, multi-server management, and context-efficient capability discovery.

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。

Test Model Context Protocol (MCP) servers and tool-calling systems for security vulnerabilities including tool injection, parameter manipulation, privilege escalation, and data exfiltration through AI agent tool interfaces. Use this skill when assessing MCP server implementations, AI agent tool integrations, or any system that exposes tools to language models. Covers tool confusion attacks, cross-tool exploitation, and MCP server hardening assessment.

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 H1 Brain MCP Server to pull HackerOne program policies, scope definitions, and disclosed vulnerability reports directly into Claude's context. Based on Critical Thinking Bug Bounty Podcast Episode 166.

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。

Deep API security assessment beyond surface scanning. Covers the full OWASP API Security Top 10 (2023): Broken Object Level Authorization (BOLA / IDOR), Broken Authentication, Broken Object Property Level Authorization (mass assignment + excessive data exposure), Unrestricted Resource Consumption, Broken Function Level Authorization (BFLA / vertical privilege escalation), Unrestricted Access to Sensitive Business Flows, Server-Side Request Forgery via API parameters, Security Misconfiguration, Improper Inventory Management (shadow/zombie/deprecated endpoints, v1/v2 drift), and Unsafe Consumption of third-party APIs. Works across REST, GraphQL, gRPC, SOAP, and MCP servers. Discovers APIs from OpenAPI/Swagger specs, GraphQL introspection, gRPC reflection, .well-known endpoints, JS bundles, and traffic capture. Uses kiterunner, ffuf, schemathesis, restler-fuzzer, openapi-fuzzer, graphql-cop, clairvoyance, batchql, inql, jwt_tool, postman, mitmproxy, and manual http(action="request", ...) payloads. Every technique includes actual payloads, commands, and verification logic. Chains from /pentester or /codebase when API endpoints are discovered, chains into /web-exploit when classic injection points are found in API parameters, chains into /post-exploit when RCE is achieved, and chains into /ai-redteam when an LLM/AI endpoint is discovered (chat APIs, completion endpoints, RAG search, agentic tool-use, MCP servers).

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。

GraphQL API server with Apollo Server — schema, resolvers, context, error handling, data sources, plugins

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。

Write effective MCP server instructions for tool compaction support. Use when creating or updating the `instructions` parameter in MaaSProtectedFastMCP server initialization. Helps LLMs understand when to search for tools, workflow patterns, and cross-feature relationships.

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。

Presentation/Core/Engine split control plane — the canonical entry point for any work decomposing the Yuzu server into three binaries (presentation · core · engine) per ADR-0031-presentation-core-engine-decomposition / ADR-0032 (the admission interlock) / ADR-0033 (access-control spine). Use when the user says "/split", "/pce-split", "/decomposition", asks to plan or implement a split workstream (WS-A*, WS-B*, WS-X*), asks "what's our gap to the presentation/core split" or "is it safe to extract presentation/the engine yet", asks to audit split readiness, or starts work touching the seam (handlers calling stores directly, the INV-31-4 contract test, the Drogon port, `server/presentation` or `server/engine`, the `uce` DB grants, component service identity, or the ADR-0032 admission/grant/audit substrate — `use_case_run_id`, the release log, the capability-declaration registry).

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。

Diagnoses Workload Identity Federation for GKE authentication failures for Pods (403 "iam.serviceAccounts.getAccessToken" / permission denied, "could not find default credentials", or GKE metadata server unreachable) by verifying cluster and node-pool Workload Identity configuration, the Kubernetes ServiceAccount (KSA) to IAM binding (direct principal binding and legacy Google ServiceAccount impersonation), target-resource IAM roles, and gke-metadata-server health. Use when a Pod cannot authenticate to Google Cloud APIs even though Workload Identity is expected to be in effect. Don't use for in-cluster Kubernetes RBAC errors (API-server authorization), general workload crashes (use gke-workload-troubleshooting), or Workload Identity setup and hardening (use gke-workload-security).

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。

Assists in designing and implementing secure n-tier serverless web applications and microservices on Google Cloud. Use when users need architecture designs, security checklists, Terraform code, or deployment guidance for multi-tier serverless apps, regional data residency / European sovereignty compliance, zero-trust private VPC networking, or Private Service Connect. Don't use for VM, GKE, or non-Google Cloud architectures.

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。

Record a finding about the configured engine MCP server into .unikit/MCP-RECHECK-NOTES.md — the project's log of what has to be re-checked here. Use right after a call reported success while changing nothing, ate an argument, or validated a broken state, e.g. "write this down", "record this MCP finding", "the server lied — note it", "add a recheck note", "trap this". Takes three forms of input: the finding in one line, a path to a plan file (harvests the "## MCP Findings" table of that plan and nothing else), or nothing at all — then it takes findings already in the session first, and offers to scan the tables of plans touched since the last audit. The table only, never the plan body. Writes in the one allowed genre — a check to perform; never a lifted gate, never a named workaround, never a claim about what the server can or cannot do. Makes zero MCP calls and needs no editor. To replay, retire, or upstream existing notes use /unikit-mcp-audit instead.

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。

Curate .unikit/MCP-RECHECK-NOTES.md — the project's log of findings about the configured engine MCP server. Four jobs: re-stamp (the server moved, so every entry is suspect), replay (reproduce a `replay: safe` finding inside a disposable sandbox to see whether it still holds), retire (offer to drop what was fixed or went upstream), and upstream (print a ready diff for the packaged INDEX.md). Use for "audit the MCP notes", "are these findings still true", "recheck the MCP traps", "clean up MCP-RECHECK-NOTES", "the server was updated — revisit the notes". Replaying mutates a live editor, so it starts by telling you how to prepare it — save your scene, open an empty one — and asks once before touching anything. Everything it creates lives under a single UNIKIT_AUDIT_<runid> prefix, is deleted in one action, and the scene is never saved. To record a NEW finding use /unikit-mcp-trap instead.

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。

Design, audit, harden, review, or upgrade MCP servers and MCP Apps with revision-aware protocol profiles, explicit HTTP/deployment boundaries, capability-centered validation, bilingual reporting, and reproducible evidence. Use for MCP server architecture, JSON-RPC or Streamable HTTP bugs, security hardening, protocol-version migration, MCP Apps widget boundaries, review reconciliation, test planning, and public engineering evidence.

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 Xero MCP server — troubleshoot its self-refreshing OAuth2 token file, maintain the local best-of-breed server build, and pick up other operational notes for working with Xero MCP tools. Use when Xero MCP tools fail with authentication errors, before starting any Xero workflow, when adding or updating upstream xero-mcp-server PRs, or for general guidance on Xero MCP usage.

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。

Serve any markdown file or directory as a calm, book-like reader via a local HTTP server (127.0.0.1 only). Best for long-form documents — RFCs, runbooks, design docs, plan files — where comfortable in-browser reading matters. Supports Mermaid diagrams, dark/light mode, plan navigation sidebar, and keyboard shortcuts. Requires explicit start and stop lifecycle.

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。