「multi-step」の検索結果

Create a workflow command that orchestrates multi-step execution through sub-agents with file-based task prompts

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 saga patterns for distributed transactions and cross-aggregate workflows. Use when coordinating multi-step business processes, handling compensating transactions, or managing long-running 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。

Extract reusable knowledge from the current session into a persistent skill. Use when you discover something non-obvious, create a workaround, or develop a multi-step workflow that future sessions would benefit from.

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 types /hep-storm, mentions @Hephaestus storm, or asks to force-robustly drive a loop-worthy goal (apps, sites, agents, automations, debugging, multi-step research, data/report generation) to a verified finish. Stormbreaker routes the goal to real Agentlas specialists, materializes a dependency-ordered pipeline fabric, and runs a verifier-first loop that does not stall, run away, or claim false success. Trivial questions are answered directly, not stormed.

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 types /hep-storm or /agentlas-storm, says @Hephaestus storm <goal>, or asks to drive a goal to verified completion through a force-robust Stormbreaker loop. Stormbreaker routes the goal to real Agentlas specialists, materializes a dependency-ordered pipeline fabric, and runs each work packet as a verifier-first hardened loop that does not stall, run away, or claim false success. Use it for loop-worthy work — apps, sites, agents, automations, debugging, multi-step research, data/report generation. Trivial questions are answered directly, not stormed.

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。

Creates explicit validation checkpoints (verification gates) between project phases to catch errors early and ensure quality before proceeding. Use when the user asks about quality gates, milestone checks, phase transitions, approval steps, go/no-go decision points, or preventing cascading errors across a multi-step workflow. Produces acceptance criteria checklists, automated CI gate configurations, manual sign-off requirements, and conditional review rules for scenarios such as security changes, API changes, or database migrations.

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 an LLM agent design and find where it will be unreliable, expensive, or unsafe. Use when asked to review an agent architecture, critique a multi-step/tool-using agent, debug an agent that loops or goes off-task, or harden an agent before launch. Produces a structured review — task fit, control flow, tools, memory/context, failure handling, cost, and safety — with prioritised findings and fixes.

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 is multi-step, may span context resets or sessions, uses subagents, or risks losing state before completion.

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 you have an approved spec or written requirements for a multi-step task that needs a durable plan document before touching code. Small, single-owner, or fast-path tasks do not need this 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。

Break large features into independently verifiable, human-reviewable slices under a feature directory in specs/. Use for risky or multi-step feature work that needs upfront questioning, API seams, browser-playable checkpoints, HTML visualizations, screenshot gates, staged implementation plans, recursive fog-of-war reslicing, or proactive research into reference implementations/best practices before slicing. Pairs with your project's verification harness and screenshot gates (the browser checkpoints), [refactor-clean](../refactor-clean/SKILL.md) (review the materialized spec so the plan describes one-owner architecture, not the feature bolted on), [screenshot-critique](../../visual/screenshot-critique/SKILL.md) and [compare-screenshots](../../visual/compare-screenshots/SKILL.md) (the visual gates), and a code-review pass (audit each slice before it lands).

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 asks "what's on my plate today", "catch me up", "morning brief", or wants a summary of their day across calendar, reminders and email. The single most common multi-step automation. Powered by LMCP on macOS and Windows.

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。

Coordinate multi-step work across services the user has authorized through Aident Loadout, using live action schemas, connection checks, cost preflight, and explicit approval for side effects.

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。

Send cold email and run outbound email campaigns from an agent with Sendsets. Connect or check sending mailboxes, turn a lead list (CSV or inline) into a multi-step email sequence with follow-ups, validate merge fields, send a test, launch, and read and answer replies. Use when the user asks to send cold emails, email a list of prospects or leads, run an outreach or outbound sequence, or follow up with contacts by email.

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。

Anti-slop skill for PRODUCT UI - dashboards, data tables, forms, multi-step flows, settings, list/detail, app shells. The agent reads the surface, budgets the frame first, and ships dense interfaces that are correct at every edge case (overflow, long labels, empty/error/loading states, i18n expansion, keyboard/a11y). House-system-first; maps to Carbon/Polaris/Atlaskit/Fluent/Primer/Material3/Radix-shadcn/Ant. The counterpart to taste-skill, which owns landing/portfolio/marketing.

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Performs retrosynthetic planning using AiZynthFinder (template-based MCTS), maintained or version-pinned template-free models, ASKCOS, and emerging RetroSynFormer with explicit handling of route scoring, configurable MCTS rewards, building-block availability, and forward-prediction checks. Use when assessing synthetic feasibility of generated or selected molecules, planning multi-step syntheses, building synthesis-aware design pipelines, or screening libraries for retro-route feasibility.

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, diagnose, or review SwiftUI motion using explicit and scoped implicit animations, springs, transitions, PhaseAnimator, KeyframeAnimator, matched geometry or navigation zoom, SF Symbol effects, and custom Animation types. Use when views should animate on state changes, insertion, removal, navigation, or multi-step choreography, or when motion must respect Reduce Motion and Swift concurrency.

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。

Apply step-by-step analysis for complex problems with revision capability. Use for multi-step reasoning, hypothesis verification, adaptive planning, problem decomposition, course correction.

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。

Define, validate, run, resume, and audit repo-local multi-step automations with current `asc workflow` and `.asc/workflow.json`, including step outputs and safe release/TestFlight 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。

Transforms workflow to use Manus-style persistent markdown files for planning, progress tracking, and knowledge storage. Use when starting complex tasks, multi-step projects, research tasks, or when the user mentions planning, organizing work, tracking progress, or wants structured output.

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。

Versatile JavaScript animation engine for DOM, CSS, SVG, and JavaScript objects. Use when creating timeline-based animations, stagger effects, SVG morphing, keyframe sequences, or complex choreographed animations. Triggers on tasks involving Anime.js, timeline animations, staggered sequences, SVG path animations, morphing, or multi-step animation choreography. Alternative to GSAP for SVG-heavy animations and React-independent projects.

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 involves running a Scenario workflow through MCP, including anything the user calls a Scenario app, a saved pipeline, or a multi-step generation graph. Triggers include listing workflows, building workflow_run's inputs object, pricing a run with a dry run, approving or rejecting a stuck approval node, a run rejected for input length, or a workflows_list reply flooding the context. Creating or editing graphs is scenario-workflow-authoring. Keywords: workflow, app, approval gate.

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。

Capture a hard-won "golden path" from the current session as a reusable Agent Skill, so future sessions start already knowing it. Use it (1) right after non-trivial debugging, after working out a multi-step operational workflow, or after rediscovering project facts you didn't know up front — e.g. how to reach the dev/prod database, where credentials and env vars live, how to deploy, run migrations, or verify a change live; and (2) whenever the user says "remember this", "save this as a skill", "make a skill for this", "don't make me re-explain this next time", or otherwise wants a workflow preserved across sessions. Proactively recognize the moment even when unprompted: if a task took several attempts before it worked, used non-obvious tooling, or is likely to recur, harvest it without asking first. Delegates to a subagent when your tool supports one, or works inline, to extract the proven procedure into a new project-local or global 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。

Build resilient, long-running, multi-step applications with AWS Lambda durable functions with automatic state persistence, retry logic, and orchestration for long-running executions. Covers the critical replay model, step operations, wait/callback patterns, error handling with saga pattern, testing with LocalDurableTestRunner. Triggers on phrases like: lambda durable functions, workflow orchestration, state machines, retry/checkpoint patterns, long-running stateful Lambda functions, saga pattern, human-in-the-loop callbacks, and reliable serverless 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。

Form optimization for lead capture, contact, demo request, application, and checkout forms. Covers field-cost analysis, multi-step form design, validation UX, mobile optimization, and A/B testing frameworks.

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。