563 件 ・ 関連度順
概要と使いどころ
Reviews Rust FFI code for type safety, memory layout compatibility, string handling, callback patterns, and unsafe boundary correctness. Use when reviewing extern blocks, #[repr(C)] types, bindgen output, or code calling C/C++ libraries.
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。
Register and implement PydanticAI tools with proper context handling, type annotations, and docstrings. Use when adding tool capabilities to agents, implementing function calling, or creating agent actions.
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 this skill when building Solana-enabled games or apps in Godot 4 with the Godot Solana SDK. Triggers include: Solana transactions in GDScript, SPL tokens or NFTs in a Godot project, connecting browser or mobile wallets (Phantom, Solflare, Backpack) in a Godot game, calling Anchor smart contracts from GDScript, working with Candy Machine in Godot, or any mention of SolanaClient, Transaction, Pubkey, Keypair, WalletAdapter, or AnchorProgram in a Godot context. Do NOT use for non-Godot Solana SDKs (solana-py, solana-go, solana-web3.js).
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。
Expert guide for Vercel AI SDK (Core, UI, RSC), streaming structured data, multi-provider model switching, tool calling loops, and React 19/Next.js 15 AI engineering / Panduan ahli Vercel AI SDK, streaming data terstruktur, dan integrasi AI pada React 19/Next.js 15.
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 whenever you need the Datagrok browser to actually execute JavaScript — adding viewers, filtering, modifying the view, or returning a result widget to the chat. Open this skill before calling the datagrok_exec tool.
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。
When calling LLM APIs from Python code. When connecting to llamafile or local LLM servers. When switching between OpenAI/Anthropic/local providers. When implementing retry/fallback logic for LLM calls. When code imports litellm or uses completion() 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。
Create, schedule, duplicate, inspect, cancel, archive, and troubleshoot Vapi outbound Campaigns. Use for persistent multi-contact calling, CSV or API contact personalization, campaign concurrency, campaign webhooks, pre-dial eligibility, contact outcomes, or rerunning an audience. Do not use for a single call or a simple one-off /call batch.
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。
Apple FoundationModels framework for on-device LLM — text generation, guided generation with @Generable, tool calling, and snapshot streaming in iOS 26+.
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。
Runs a multi-model orchestration workflow led by the session's Fable or Claude Opus model. Sends menial tool-calling work to Haiku subagents, judgment work to Opus subagents at an effort matched to each task, and high-stakes or fresh-perspective questions to a GPT-6 Astra Codex peer. Detects the lead from session context; `--lead fable` or `--lead opus` overrides. Use to orchestrate, delegate, fan out, get a decorrelated Codex opinion, run a blind Opus-Codex cross-check, or act as tech lead.
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。
Consults Fable as an independent, read-only reviewer at an effort the caller matches to the question. The calling session (usually Opus, or Haiku) holds the task and escalates one decision point. Use before committing to an interpretation or a substantial piece of writing or analysis, when stuck or not converging, when changing approach, or as a final check on a finished task. Fallback for when the native advisor tool is unavailable. Not for a session already running Fable.
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。
Expert in designing and building autonomous AI agents. Masters tool use, memory systems, planning strategies, and multi-agent orchestration. Use when: build agent, AI agent, autonomous agent, tool use, function calling.
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。
Add a new tool to the backend OpenAI function calling system. Use when user mentions "new tool", "add tool", "backend function", "agent capability", or wants to extend what the AI agent can do.
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 conversational AI agents using Vercel AI SDK + OpenRouter. Use when creating Next.js frontends with streaming UI, tool calling, and multi-provider support.
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 the user wants to run a diffusers pipeline from a terminal (one-off generation, batch jobs, smoke-testing a new model), run on HF Sandbox hardware via `--remote`, introspect a pipeline's input schema before calling it, or attach a LoRA at inference time. Prefer this over writing ad-hoc Python scripts for generation tasks.
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。
Reading assistant for saving, organizing, and recalling web content. Use when the user says "save this article", "read this link", "summarize this", "check my feeds", "add to my library", or asks about previously saved content. Handles articles, tweets, YouTube videos, GitHub repos, PDFs, and RSS feeds. Articles are stored with their metadata and indexed for fast search.
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 Arcade MCP to create custom MCP servers and tools with OAuth-aware authorization, evals, and deployment paths for agent tool-calling workflows.
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。
Permanently deletes a Stitch project and all its screens. Destructive — requires explicit user confirmation before calling.
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 working on or testing imp-server and its HTTP APIs - OpenAI/Anthropic endpoints, /v1/chat/completions, /v1/messages, /v1/responses, SSE streaming, tool calling, json_schema/regex/GBNF constrained decoding, thinking/reasoning_content, cache_control/prefix cache, model loading and swapping, request priority, X-Request-Id, OTLP tracing / traceparent / Jaeger, /metrics, container env (IMP_SET), "server returns 404/garbage", API compliance. Do NOT use for CLI-only inference (imp-cli), kernel work (sm120-cuda-expert), or pure output-quality checks (check-degeneration).
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.
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 the user needs to find, prioritize, or engage B2B prospects — defining an ICP, tiering accounts, building or enriching lists, reading buying signals, designing multi-channel cadences, cold calling, LinkedIn outreach, routing inbound leads, or diagnosing weak pipeline generation. Also for live prospecting coaching. Not for closing (use sales-skill), copy (use copywriter-skill), or CAC analysis (use channel-expert).
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Implement circuit breaker logic for agentic tool calls — tracking tool health, transitioning between closed/open/half-open states, reducing task scope when tools fail, routing to alternatives via capability maps, and enforcing failure budgets to prevent error accumulation. Separates orchestration (deciding what to attempt) from execution (calling tools), following the expeditor pattern. Use when building agents that depend on multiple tools with varying reliability, designing fault-tolerant agentic workflows, recovering gracefully from tool outages mid-task, or hardening existing agents against cascading tool failures.
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 building or evaluating a Hare program: hare build, run, or test, tagged-union error handling, or calling C through bodyless fn declarations and -l. Not for Zig or C: use zig-cinterop or gcc.
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Use when reading or writing AArch64 or AArch32 Thumb assembly, inline asm in C, AAPCS64 register roles, or NEON and SVE vector code. Not for ABI detail across ISAs: use abi-and-calling-conventions.
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 explaining System V AMD64, ARM AAPCS, RISC-V psABI, stack frames, variadic calls, or FFI register rules. Not for the Rust FFI binding layer: use rust-ffi.
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。