「ai-engineer」の検索結果

Review a skill-requested filesystem, command, network, secret, or destructive action against an explicit sandbox policy without executing it.

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。

AI-native tutor and onboarding workflow for the MCPA (Model Context Protocol Associate) certification in AI Engineering from Scratch. Use when a learner wants to prepare for the MCPA, resume their certification path, learn the next lesson interactively, run and verify practical labs, take the diagnostic or a full mock, or remediate weak exam domains from GitHub with Claude Code, Codex, ChatGPT, Cursor, or another agent.

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。

Focused interactive tutor for the Agent Skills Engineering path in AI Engineering from Scratch. Start or resume this route when a learner wants to create, discover, invoke, secure, evaluate, package, or port Agent Skills. Teaches one lesson per invocation and records evidence in AGENT-SKILLS-LEARNING.md.

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 and test explicit human, implicit model or agent, programmatic application, bounded skill-composition, and harness activation policies for an Agent Skill catalog.

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。

Phase quiz for AI Engineering from Scratch. Trigger with "quiz me", "test phase", "check my understanding", "do I know phase 3", or `/check-understanding <phase>`.

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。

AI-native tutor and onboarding workflow for the four independent Claude certification tracks in AI Engineering from Scratch. Use when a learner wants to choose a Claude certification, prepare for CCAO-F, CCDV-F, CCAR-F, or CCAR-P, resume a certification path, learn the next lesson interactively, run and verify practical labs, build scored artifacts, take a diagnostic or mock exam, or remediate weak exam domains from GitHub with Claude Code, Codex, ChatGPT, Cursor, or another agent.

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 a bounded Agent Skill catalog across explicit discovery scopes and report collisions before loading instruction bodies.

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。

Validate an Agent Skill package and choose the right instruction, capability, or lifecycle primitive before implementation.

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。

Review database migration files when a change adds or modifies paths under migrations/. Use it before merge to collect forward, rollback, locking, and data-safety 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。

Review a release proposal

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。

Check deployment evidence and recovery conditions.

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 LLM applications, advanced RAG systems, and intelligent agents. Implements vector search, multimodal AI, agent orchestration, and enterprise AI integrations.

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 LLM applications, advanced RAG systems, and intelligent agents. Implements vector search, multimodal AI, agent orchestration, and enterprise AI integrations. Use PROACTIVELY for LLM features, chatbots, AI agents, or AI-powered applications.

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 LLM applications, advanced RAG systems, and intelligent agents. Implements vector search, multimodal AI, agent orchestration, and enterprise AI integrations.

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。

Interview the user relentlessly about a plan or design until reaching shared understanding, resolving each branch of the decision tree. Use when user wants to stress-test a plan, get grilled on their design, or mentions "grill me".

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。

Break a PRD into independently-workable issues and write each as a local markdown file in issues/. Use when the user wants to turn a PRD into a list of concrete 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。

Test-driven development with red-green-refactor loop. Use when user wants to build features or fix bugs using TDD, mentions "red-green-refactor", wants integration tests, or asks for test-first development.

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。

Explore a codebase to find opportunities for architectural improvement, focusing on making the codebase more testable by deepening shallow modules. Use when user wants to improve architecture, find refactoring opportunities, consolidate tightly-coupled modules, or make a codebase more AI-navigable.

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。

Generate a PRD from the client brief and write it as a local markdown file in issues/. Use when the user wants to turn a client request into a structured PRD.

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 seeing errors about better-sqlite3 native module, NODE_MODULE_VERSION mismatch, "was compiled against a different Node.js version", or similar native binding errors.

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。

Think and work like an expert Edge / Embedded AI Engineer. Use when a task calls for Edge / Embedded AI Engineer judgment. Reasons from tensor-arena budgets, full-int8 PTQ with representative calibration, and TFLM/CMSIS-NN or Vela/Ethos-U compile paths through ONNX Runtime QNN HTP and mobile delegates—treating train–serve preprocessing skew, float thresholds on quantized outputs, and NPU operator fallback as first-class failure modes.

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 LLM applications, RAG systems, and intelligent agents. Use when implementing AI features, chatbots, vector search, or agent orchestration.

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 LLM applications, advanced RAG systems, and intelligent agents. Implements vector search, multimodal AI, agent orchestration, and enterprise AI integrations.

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。

Integrate LLM API RAG fine-tuning prompt engineering พร้อมคุม token cost และกัน prompt injection

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。