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概要と使いどころ
Company expense receipt workflow. OCR, rename, sort, summarize, and prepare receipt images/PDFs/videos for D365 expense mapping and attachment. Use when sorting company expense receipts, organizing travel expense files, OCR renaming, receipt sorting, expense sorting, レシート仕分け, 出張経費バッチ, D365経費仕分け, D365経費カテゴリマッピング, or D365経費精算. Not for personal or sole-proprietor tax receipts (確定申告).
Prompt engineering and task-specification skill for improving prompts, agent instructions, system messages, evaluation prompts, coding-agent tasks, multi-step workflows, and LLM output reliability. Use when rewriting vague prompts, adding constraints, reducing ambiguity, improving safety, creating reusable prompt templates, or converting goals into actionable agent instructions.
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。
Multi-agent management workflow — task delegation, progress monitoring, quality verification with regression testing, feedback delivery, and cross-review orchestration. Use this skill when coordinating multiple agents on a shared task, monitoring delegated work, ensuring quality across agent outputs, or implementing a multi-phase plan (3+ phases or 10+ file changes).
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。
Manages cloud infrastructure through natural language conversations with Pulumi Neo, an AI agent for platform engineers. Enables infrastructure analysis, resource provisioning, stack deployment, and configuration management via conversational AI. Use when creating Neo tasks, requesting infrastructure analysis, automating cloud deployments, managing infrastructure as code (IaC), provisioning AWS/Azure/GCP resources, managing infrastructure through natural language prompts, reviewing PRs with Neo, handling Neo approval workflows, or checking Neo task status and events. Also use when the user mentions "Pulumi Neo", "Neo task", "Neo agent", or wants AI-assisted infrastructure 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。
**WORKFLOW SKILL** — Register and generalize agent errors into reusable lessons. USE FOR: when the user corrects the agent, capturing what went wrong, analyzing root cause, generalizing the error into a lesson that prevents recurrence. Use to register errors, analyze mistakes, create lessons, generalize corrections. DO NOT USE FOR: general debugging, writing tests, code 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。
Run a Meta-Harness-style optimization loop NATIVELY — automatically search over the scaffolding around a FIXED base model (memory, retrieval, context construction, prompt templates, summarization, tool-selection logic) by proposing candidate variants, scoring each on a cheap deterministic eval, and keeping a Pareto frontier of quality vs cost — using native Agent / Workflow / loop tools instead of a standalone Python harness. Use this whenever the user wants to optimize, evolve, tune, distill, or search over a harness, scaffold, prompt system, memory or retrieval policy, context-assembly code, or summarizer while keeping the model fixed; whenever they mention Meta-Harness, harness optimization, scaffold evolution, automatic prompt/memory optimization, an evolutionary or Pareto search over candidate implementations, or "make the harness/agent better without retraining"; and whenever the gain must come from the code AROUND the model rather than the model weights. Reproduces the Meta-Harness paper's method natively, with no claude_wrapper.py and no metered solver API.
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。
Comprehensive Mastra framework guide. Teaches how to find current documentation, verify API signatures, and build agents and workflows. Covers documentation lookup strategies (embedded docs, remote docs), core concepts (agents vs workflows, tools, memory, RAG), TypeScript requirements, and common patterns. Use this skill for all Mastra development to ensure you're using current APIs from the installed version or latest documentation.
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。
Iterative development workflow that coordinates implementation, refactoring, QA, and documentation agents to complete features systematically. Use when the user wants a full development workflow with quality checks.
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 for agent workflow collab recipes when optimizing a Coworld player.
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 for agent workflow collab recipes in scripted Coworld policy optimization.
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 for Crewrift-specific agent workflow collab recipes when optimizing a player.
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。
Safety guardrails for destructive operations. Wraps workflows and agent actions in configurable safety modes: CAREFUL (warns before destructive commands), FREEZE (restricts file edits to one directory), GUARD (both modes combined). Use when working in production, running destructive scripts, or debugging in sensitive areas. Voice triggers: "be careful", "safety on", "guard mode", "freeze scope". Also used automatically by the workflow engine when a workflow preset has safety: "guard" enabled.
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 with DecisionsAI when a ticket or workflow needs internet research — social posts, articles, video subtitles, GitHub, RSS, or competitor scans. Routes through Agent Reach upstream tools; run agent-reach doctor first.
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。
Auto-activate for Google ADK, LlmAgent, Runner, SQLSpecSessionService, google-genai, AgentRuntime, SpecTree, DynamicWorkflow, FunctionTool, or SSE agent chats. Not for offline ML training.
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 bonded agent systems, escrow workflows, slashing rules, oracle trust, Sybil cost, and front-running risk in protocols where agents post bonds or stake reputation. Use for collateral sizing, griefing analysis, dispute design, and bonded-agent security reviews. NOT for smart contract auditing, DeFi tokenomics, blockchain consensus design, or trading strategy.
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。
Detects the right agent and complexity tier at Phase 0 orient; runs first in every workflow. NOT for runtime agent routing inside a single skill.
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。
Audits GitHub Actions workflows for security vulnerabilities in AI agent integrations including Claude Code Action, Gemini CLI, OpenAI Codex, and GitHub AI Inference. Detects attack vectors where attacker-controlled input reaches. AI agents running in CI/CD pipelines.
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。
Padrões de design para construir agentes de codificação autônomos. Cobre integração de tools, sistemas de permissão, automação de browser e workflows com intervenção humana. Use ao construir agentes IA, projetar APIs de tools, implementar sistemas de permissão ou criar assistentes de codificação autônomos.
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。
Convex is the backend agents get right on the first try: an all-TypeScript reactive platform where the database, server functions, scheduling, file storage, auth, and realtime sync are one type-safe system, every function is a transaction, and `tsc` catches most mistakes before deploy. Ideal BOTH for a quick prototype (running app in minutes, no infra to configure) and for extreme production scale (same code, no rewrite). Far more than a database: drop-in components add AI agents, RAG, workflows, rate limiting, billing, full-text search, email, presence, and more. Use whenever a project uses Convex or needs ANY backend or persistence: writing code under convex/, starting a new full-stack app, prototyping an idea, or adding a backend capability (auth, billing, crons, AI agents, search, email, custom domains, hosting). Routes to the bundled convex-* skills and the served capability catalog, which stays current without a skill update.
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。
Reconstruct workflow behind a past coding-agent artifact using local ax sessions/commits/skills/tool traces. Use when asked how X was built.
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。
Audits GitHub Actions workflows for security vulnerabilities in AI agent integrations including Claude Code Action, Gemini CLI, OpenAI Codex, and GitHub AI Inference. Detects attack vectors where attacker-controlled input reaches. AI agents running in CI/CD pipelines.
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 Workflow Designer
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。
Route agent work through AccInt's MCP memory loop: retrieve prior outcomes, resolve frames, and close commitments with 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。