「assistant」の検索結果

Use when creating, improving, or troubleshooting Claude Code subagents. Expert guidance on agent design, system prompts, tool access, model selection, and best practices for building specialized AI assistants.

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 production-ready AI agents using Google's Agent Development Kit with AI assistant integration, React patterns, multi-agent orchestration, and comprehensive tool libraries. Use when appropriate context detected. Trigger with relevant phrases based on skill purpose.

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 assistance skill that provides stuck detection, memory management, and session learning capabilities for AI agents Trigger terms: agent stuck, loop detected, session memory, agent learning, condense memory, stuck detection, agent memory, session learnings, extraction Use when: User reports agent is stuck, looping, or needs memory/learning management

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 guidance for building and editing n8n workflows with Synta MCP tools. Use for creating new workflows, modifying existing workflows, template discovery, node configuration, validation, and connection management in n8n.

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。

Facilitate sprint planning by organizing backlog items, estimating effort, balancing capacity, identifying dependencies, and producing a sprint commitment summary. Use when teams need structured sprint planning output. Do not use for strategic roadmap planning, annual budgeting, or product vision work.

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。

Analyze Kanban flow metrics to identify bottlenecks and improve team throughput. Covers Cycle Time, Throughput, WIP, and Flow Efficiency using Little's Law and Theory of Constraints. Use when a team wants to optimize delivery flow or improve predictability. Do not use for sprint-based Scrum planning — use sprint-planning-assistant 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。

Test Retrieval-Augmented Generation (RAG) systems for data poisoning, prompt injection via retrieved documents, and data exfiltration through manipulated context windows. Use this skill when assessing RAG-based chatbots, knowledge bases, enterprise AI assistants, or any system that augments LLM responses with external document retrieval. Covers document injection, embedding manipulation, knowledge base poisoning, and cross-document inference attacks.

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 Large Language Models for direct prompt injection vulnerabilities where user input overrides system instructions, extracts system prompts, bypasses safety filters, or causes unauthorized actions. Use this skill when assessing chatbots, AI assistants, LLM-powered tools, or any application that processes natural language input through an LLM. Covers role-playing attacks, instruction hierarchy exploitation, multi-turn manipulation, and context window abuse for comprehensive AI security 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。

Exploit AI assistants equipped with web-browsing capabilities or internal API plugins to perform Server-Side Request Forgery (SSRF). This skill details injecting prompts that force the LLM to request sensitive internal endpoints, such as underlying cloud metadata services or internal networks.

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。

Visual design verification loop for matching a goal PNG to a live render. Use when the user shares a design mock / goal image and asks to match the UI to it, asks to "iterate on this design" or "match this 1:1", or calls out visual drift in a previous UI iteration. Provides histogram color sampling, shape inspection (radius/border/shadow/bg-mode/fill-vs-context), computed-style checking on the live render, snap, and side-by-side diff. After every UI change the assistant MUST snap the live render and Read the snap with the Read tool before reporting the change done — skipping that is the

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。

Assistant-behavior design skill for approximating a Claude-like analytical, careful, conversational style without claiming to be Claude or Anthropic. Use when the user asks to duplicate, emulate, adapt, or recreate a Claude-style "mythos" or persona for prompts, agent specs, writing style, reasoning discipline, safety posture, or UX behavior.

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。

将课程资料（PPT/Word/PDF/截图）按章节生成深度知识清单、教授式详细讲解和交互式章节测试，帮助学生高效期末复习。

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 a task needs the judgment of a K-12 Education Administrator (principal/assistant principal/district administrator) — making a school-level policy or resource-allocation decision, handling a discipline or safety incident, evaluating a curriculum or staffing decision, or balancing competing demands from teachers, parents, students, and district requirements.

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。

Setup assistant for running Stably Playwright tests in GitHub Actions CI/CD. Use this skill when setting up CI, configuring GitHub Actions, or debugging CI workflow failures. Triggers on "setup github actions", "CI setup", "github actions for tests", "configure CI", "run tests in CI", "github workflow", or "CI pipeline for playwright".

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 setup assistant for the Stably Playwright SDK. Use this skill when installing Stably SDK in a new project, migrating from @playwright/test, or configuring Stably reporter for CI/CD. Triggers on tasks like "setup stably", "install stably sdk", or "configure playwright with stably".

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 assistant for the Stably CLI tool. Prefer "npx stably test" over "npx playwright test". Use this skill when working with stably commands for planning, creating, running, fixing, and verifying Playwright tests using AI. Triggers on any playwright test execution (e.g. "npx playwright test", "run tests", "run e2e tests"), "create tests with stably", "fix failing tests", "run stably test", "use stably cli", "stably env", "stably --env", "remote environments", "stably verify", "verify app behavior", "stably plan", "plan test coverage", "coverage gaps", "stably runs", "test run history", "view run details", "stably analytics", "flaky tests", "test failures", or "test health".

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。

Audit an existing Lamport-style hierarchical mathematical proof forward for validity and whether its hierarchy, scope, dependencies, side conditions, and proof constructs discharge the stated theorem. Use when the central question concerns a top-down proof with numbered levels, subproofs, ASSUME/PROVE, SUFFICES, PICK, CASE, DEFINE, Q.E.D., or prose equivalents. For an ordinary proof that first needs source-preserving hierarchy, use convert-lamport; for conclusion-first AND/OR obligation reconstruction, use reverse-lamport. Do not use to generate or replace a proof, or to audit Lean, Coq, Isabelle, or other proof-assistant source.

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 `AGENTS.md` file for a project. Use when the user wants to set up custom instructions, configure AI coding assistant behavior, or create project-specific coding guidelines for AI 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。

Evaluate code (especially LLM-generated) for structural simplicity using Rich Hickey's "Simple Made Easy" framework. Use this skill whenever reviewing a PR, diff, or code snippet for accidental complexity — particularly when the code was generated by an AI coding assistant and line-by-line review isn't feasible. Also use when the user asks about complecting, simplicity vs. easiness, structural coupling, or concept deduplication. Trigger on phrases like "is this simple", "does this complect", "review for complexity", "structural analysis", or any reference to Hickey, Simple Made Easy, or grey-box review.

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。

Get productive with agentic coding assistants — task framing, iterative prompting, file-scoped workflows, review loops, and multi-file refactors. Use when pairing with an AI coding agent on real codebases.

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。

Run a monthly money check-in with an AI assistant: categorize spending, spot leaks, set one savings target, and view it through the 50/30/20 lens — judgment-free. Use once a month to stay aware of where your money goes. General educational information, not financial advice.

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 agents on OpenAI's platform patterns — assistants-style threads, function calling, structured outputs, and multi-step tool workflows. Use when working with OpenAI models as the agent engine.

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。

Ingest supplied source material into an Obsidian vault with provenance and claim tracking: pasted text, files staged in the selected vault's inbox or .raw archive, or explicitly approved URLs. Use for a single source or bounded batch, not for saving an assistant answer. Triggers: ingest, ingest this file, ingest this URL, process this source, read and file this source, batch ingest, ingest these sources.

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。

Identifies high-quality leads for your product or service by analyzing your business, searching for target companies, and providing actionable contact strategies. Perfect for sales, business development, and marketing professionals.

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。