84건 · 관련도순
Creates durable, resumable workflows using Vercel's Workflow DevKit. Use when building workflows that need to survive restarts, pause for external events, retry on failure, or coordinate multi-step operations over time. Triggers on mentions of "workflow", "durable functions", "resumable", "workflow devkit", or step-based orchestration.
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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.
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Builds form components and data collection interfaces including contact forms, registration flows, checkout processes, surveys, and settings pages. Includes 50+ input types, validation strategies, accessibility patterns (WCAG 2.1), multi-step wizards, and UX best practices. Provides decision trees from data type to component selection, validation timing guidance, and error handling patterns. Use when creating forms, collecting user input, building surveys, implementing validation, designing multi-step workflows, or ensuring form accessibility.
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Expert in creating custom slash commands for Claude Code. Slash commands encode repeatable workflows as markdown files, turning complex multi-step processes into simple one-line invocations. Essential for team standardization, onboarding, and reducing cognitive load during development. Use when "custom command, slash command, workflow template, /command, claude command, project commands, team workflows, claude-code, commands, slash-commands, workflow, automation, templates, productivity" mentioned.
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Multi-model agent orchestration using specialized agents for planning, coding, research, math/science, visual analysis, and adversarial review. Use when tasks are complex enough to benefit from different models' strengths, when you want adversarial review to catch blind spots, or when coordinating multi-step workflows across agent roles. Triggers on complex projects, multi-step tasks, architecture decisions, or when explicitly requested.
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AI agent workflow patterns including ReAct agents, multi-agent systems, loop control, tool orchestration, and autonomous agent architectures. Use when building AI agents, implementing workflows, creating autonomous systems, or when user mentions agents, workflows, ReAct, multi-step reasoning, loop control, agent orchestration, or autonomous AI.
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Use to run a dynamic, goal-driven workflow — orchestrate a multi-step goal by composing skills, tools, and MCPs, with a quality gate and verification at each step. Trigger on "/workflow", "run the <name> workflow", "orchestrate X", or a multi-step recurring goal ("draft the investor update", "give me my morning brief"). Follows references/sops/dynamic-workflows.md and the wf-*.md cards. Respects the autonomy/cadence gate (auto on reversible/internal, draft-then-approve on external/regulated).
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Rowan is a cloud-native molecular modeling and medicinal-chemistry workflow platform with a Python API. Use for pKa and macropKa prediction, conformer and tautomer ensembles, docking and analogue docking, protein-ligand cofolding, MSA generation, molecular dynamics, permeability, descriptor workflows, and related small-molecule or protein modeling tasks. Ideal for programmatic batch screening, multi-step chemistry pipelines, and workflows that would otherwise require maintaining local HPC/GPU infrastructure.
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Orchestrate end-to-end machine learning pipelines using Prefect or Airflow with DAG construction, task dependencies, retry logic, scheduling, monitoring, and integration with MLflow, DVC, and feature stores for production ML workflows. Use when automating multi-step ML workflows from data ingestion to deployment, scheduling periodic model retraining, coordinating distributed training tasks, or managing retry logic and failure recovery across pipeline stages.
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Application-level business logic security testing for any domain. Takes an understanding-first approach: map the intended workflows before probing them. Covers: value/quantity logic abuse (negative, zero, overflow, rounding on any numeric field), workflow and state machine bypass (skipping required steps, forcing illegal state transitions, reusing one-time tokens), trust boundary violations (BOLA horizontal/vertical, BFLA, cross-tenant access, negative ownership attacks), idempotency and replay attacks (duplicate submissions, double-spend, same-reference reuse), multi-step flow integrity (checkout, registration, approval, verification), quota and rate limit bypass, time/date manipulation, and authorization code / reference number predictability. Domain-agnostic — applies to SaaS, e-commerce, banking, gaming, social platforms, APIs, or any multi-user application with stateful workflows. Chains from /pentester; chains into /param-fuzz when boundary violations or mass assignment are confirmed.
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Base skill for Refly ecosystem: creates, discovers, and runs domain-specific skills bound to workflows. Routes user intent to matching domain skills via symlinks, delegates execution to Refly backend. Use when user asks to: create skills, run workflows, automate multi-step tasks, or manage pipelines. Triggers: refly, skill, workflow, run skill, create skill, automation, pipeline. Requires: @refly/cli installed and authenticated.
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Automate Anthropic Admin tasks involving API keys, usage, workspaces, and organization management through Rube MCP, a connection to external tools. The skill guides tool discovery, connection checks, multi-step workflows, and bulk operations.
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Automate Anthropic Admin tasks involving API keys, usage, workspaces, and organization management through Rube MCP, a connection to external tools. The skill guides tool discovery, connection checks, multi-step workflows, and bulk operations.
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Build and update Convex backend code, including schemas, queries, authentication, storage, and scheduled jobs. Apply input and output validation, indexed data access, and deployment checks to verify the implementation.
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Design specialized assistants that work with their own separate context. Define responsibilities, delegation conditions, working steps, and report formats for reusable subagents handling verification, debugging, security audits, or code reviews.
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Model ongoing requests and multi-step agent work to estimate capacity, latency, and cost per completed task. Break execution into stages, account for queues and retries, and produce workload tables with average and peak resource budgets.
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AI-powered browser automation — navigate sites, fill forms, extract structured data, log in with stored credentials, and build reusable multi-step workflows using natural language. Install: pip install skyvern && skyvern setup
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Run automated release testing (UI or API) via the AWS DevOps Agent using a pre-configured test profile. Use when the user wants to validate multi-step workflows, verify features, check for regressions, or test API endpoints. Trigger words include run tests, UAT, test my app, test profile, UI test, API test, automated testing, regression test, QA, end-to-end test, run the QA agent.
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Authors and edits AWS Step Functions state machines: writes Amazon States Language (ASL) in JSONata, and chooses and structures state types (Task, Choice, Map, Parallel, Pass, Wait, Succeed, Fail). Covers ASL syntax, JSONata data transformation and variables, Retry/Catch error handling, service integrations (.sync, waitForTaskToken callbacks), Distributed Map for large-scale S3/CSV processing, saga/compensation patterns, Standard vs Express workflow choice, TestState API unit testing, and migrating state machines from JSONPath to JSONata. Use when the user is building, authoring, debugging, or migrating a Step Functions state machine or ASL definition, or orchestrating multi-step workflows with branching, retries, or human-approval callbacks, even if they don't say 'Step Functions.' Do NOT use for general Lambda function code, API Gateway, EventBridge wiring, or SAM/CDK application packaging.
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Business logic vulnerability playbook. Use when reasoning about workflows, race conditions, price manipulation, coupon abuse, state machines, and multi-step authorization gaps.
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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.
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Execute Python code locally with marketplace API access for 90%+ token savings on bulk operations. Activates when user requests bulk operations (10+ files), complex multi-step workflows, iterative processing, or mentions efficiency/performance.
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Delegate complex, long-running tasks to Manus AI agent for autonomous execution. Use when user says 'use manus', 'delegate to manus', 'send to manus', 'have manus do', 'ask manus', 'check manus sessions', or when tasks require deep web research, market analysis, product comparisons, stock analysis, competitive research, document generation, data analysis, or multi-step workflows that benefit from autonomous agent execution with parallel processing.
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Create dynamic schema-based forms using @delon/form (SF component). Use this skill when building complex forms with validation, conditional rendering, async data loading, custom widgets, and multi-step workflows. Ensures forms follow JSON Schema standards, integrate with Angular reactive forms, support internationalization, and maintain consistent validation patterns across the application.
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