2,185 件 ・ 関連度順
概要と使いどころ
App Builder - Application Building Orchestrator workflow skill. Use this skill when the user needs Main application building orchestrator. Creates full-stack applications from natural language requests. Determines project type, selects tech stack, coordinates agents and the operator should preserve the upstream workflow, copied support files, and provenance before merging or handing off.
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。
App Builder - Application Building Orchestrator workflow skill. Use this skill when the user needs Main application building orchestrator. Creates full-stack applications from natural language requests. Determines project type, selects tech stack, coordinates agents and the operator should preserve the upstream workflow, copied support files, and provenance before merging or handing off.
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。
Diagnose an AWF (Agentic Workflow Firewall) failure from an error, workflow run URL, or symptom. Covers auth (api-proxy, enterprise/BYOK Copilot, OIDC, mcpg), ARC/DinD and self-hosted runners, alternative runtimes (gVisor/Kata/chroot), Squid/DNS/egress denials, CI and gh-aw safe-output failures, and suspected security regressions. Routes to the canonical diagnosis registry in docs/diagnostics.
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 AWF (Agentic Workflow Firewall) to run commands with network isolation and domain whitelisting. Provides L7 HTTP/HTTPS egress control 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。
Cloud-based AI swarm deployment and event-driven workflow automation with Flow Nexus platform
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。
Guidelines and workflows for the agent to maintain persistent memory using native file tools (read_file, write_file, edit_file) and standard OS commands for searching.
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 only after explicit Codex `$superloopy:superloopy-backend` or Claude Code `/superloopy:superloopy-backend` invocation, a backend task beginning with leading `loopy` or `루피`, or an active Superloopy loop routes backend work here. Relevant work includes backend application boundaries, APIs, persistence, migrations, transactions, background jobs, caches, events, reliability, security, and runtime database-agent tools. Plain API, server, database, SQL, or agent vocabulary does not activate this workflow.
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。
Drive a local ComfyUI install for image, video, and audio generation via its HTTP API. Use WHENEVER generating, rendering, or editing images/video/audio/hero assets with ComfyUI, Z-Image, Ideogram, FLUX, LTX, Wan, or when building, parameterizing, or running ComfyUI workflows. Covers the API client, workflow JSON format, model patterns, dual/multi-GPU placement, the MCP driver, in-graph Claude nodes, and VRAM coordination.
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。
Proves protocols and agent workflows with TLA+, P, Alloy, Z3, Dafny, or Lean. Use when proving protocols correct, writing TLA+ specs, or verifying LLM proofs.
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。
Context-driven AI development with AGENTS.md, repo knowledge bases, Claude Code, Codex, and Copilot. Use when adopting repo-native AI workflows or multi-repo setups.
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。
Automates Metabase cards, dashboards, Remote Sync, embedding, tenants, and the Agent API/MCP server for AI workflows. Use when scripting, promoting, or embedding Metabase content.
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。
Triage Monte Carlo alerts interactively or build an automated workflow. Fetch, score, and troubleshoot alerts using MCP tools now, or design a reusable workflow that runs on a schedule.
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 adaptive learning with ReasoningBank for pattern recognition, strategy optimization, and continuous improvement. Use when building self-learning agents, optimizing workflows, or implementing meta-cognitive systems.
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。
Designing GitHub Actions workflows in depth: trigger strategy, security hardening, performance optimization, PR automation, and Reusable Workflow design.
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。
Designing a repository's project-local operating layer and generating its skills, recipes, workflows, and routing map. Not for global ecosystem agents (Architect) or runtime execution (Nexus).
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。
Managing dependencies, CI/CD, advanced GitHub Actions workflows, containers, secrets, and operational config. Use for build, workflow, or environment 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。
Orchestrate compassionate systems tools from issue or aspiration to wise action. Use when a class needs a complete inquiry workflow.
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。
Structures git workflow practices. Use when making any code change. Use when committing, branching, resolving conflicts, splitting uncommitted work in a messy working tree into clean atomic commits, opening or reviewing a pull request (PR), pushing to a remote, or when you need to organize work across multiple parallel streams. Use when cutting a release, choosing a semantic version bump, tagging, or writing a changelog.
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。
Authors and updates customization overrides for installed BMad skills. Use when the user says 'customize bmad', 'override a skill', 'change agent behavior', or 'customize a workflow'
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。
Validates agent claims against evidence trail. Use when verifying an agent has actually done what it claims — auto-fires at workflow end. Catches 'done' without proof, 'tests pass' without output, 'fixed' without verification. Called by cook and team.
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。
Direct substantial repository work across Claude Code, Codex CLI, or Grok Build with a concise brief, parallel agents, evidence-based completion, and optional cross-CLI continuation. Use for project onboarding, multi-step implementation, agent coordination, verification planning, low-interruption setup, or deciding how another CLI should take over. Do not use it as a permission gate or mandatory workflow.
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。
Convert markdown plans into beads with dependencies using br CLI. Use when creating task graphs, polishing beads before implementation, or bridging planning to agent swarm execution.
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。
Universal dispatcher: run a named taffy workflow (.claude/taffy/<name>.yaml), a skill (/skill-name), or a sub-agent (@agent-name). Falls back to skills.sh registry when a skill is not found locally. Tracks all runs in .claude/state/maple.json so the maple TUI shows live progress.
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。