Agently-Skills

Route ambiguous product, document, or Agentic work to the right design or implementation skill. Use for unresolved owner/project shape, mixed specialties or explicit low-frequency TaskDAG or DynamicTask requests. Clear tasks use their specialist directly; conversation expression, progress and handoffs use agently-collaboration alongside any task.

Use to design, understand, tune, or audit a non-trivial model workflow, including framework-undecided designs, partial implementations, and production reviews: model-node responsibilities, input/output completeness, data-flow correctness or redundancy, model-versus-Host/workflow ownership, topology, evidence, lifecycle, concurrency, or observed execution effects. The user need not say Prompt review or name Agently. Use agently-request for one request family and agently-triggerflow for already-decided executable orchestration details.

Use for coding-agent conversation communication across any project or task: explain the current task and outcome, report progress, maintain the complete plan, present decisions or blockers, and resume or hand off long work. Applies alongside coding, design, research and writing skills without requiring Agently. Brief factual answers stay brief; application runtime progress and deliverable design remain with their task owners.

Deprecated compatibility entry for callers that explicitly name the former agently-design skill. Continue Agentic system design with agently-agentic-design; human product, interface and document design uses agently-product-design.

Use when migrating an existing LangChain, LangGraph, LlamaIndex, or CrewAI system into Agently and mapping each source behavior to its actual request, runtime, context/storage, or TriggerFlow owner.

从真实需求场景出发设计应用和方案，按角色走查交互、视觉或文档阅读体验，并用同一 checklist 修订复验。用于方案比较或重设计、项目交互规范与公共组件、界面优化、文稿起草重构、中文应用文润色、读者逻辑检查、STE 写作及画板表达；统一执行共同方法，按需读取方案设计、角色行为覆盖、应用体验、文档表达模块。普通代码修错、纯后端诊断、简单纠错、文学创作或纯插画不单独触发。

Use for Agently request-side setup and contracts: model settings, Prompt/input/output design, effect tuning, missing or redundant context, structured output, LongContent, auto_continue, response reuse, streaming, TTS/STT audio, session memory, embeddings, and retrieval within one request family. Use agently-agentic-design for cross-node data flow and model/Host ownership.

Use for Agently runtime extensions: AgentExecution plugins and final review/artifact policies, Actions and MCP, Shell/BashExecutor and PowerShell permissions, ExecutionResource lifecycle, TaskWorkspace, RecordStore, auto_func and KeyWaiter, FastAPIHelper, or optional DevTools observation.

Use for Agently-Stage process-local task lifetime and sync/async interop: Stage scopes and handles, settlement/cancellation, StageCallBridge and StageStream, Tunnel replay channels, or local EventEmitter listeners. Choose this even inside TriggerFlow when a provider-owned sync wrapper bridges an async SDK; use TriggerFlow for application workflow orchestration or persistence.

Use when developer-owned execution needs inspectable branching, concurrency, joins, waits, approval, retry, runtime streams, pause/resume, recovery, or mixed sync/async orchestration. Use agently-stage instead when a provider-owned sync wrapper only bridges an async SDK.

Use when a business metric comparison must be written from structured evidence with explicit evidence references and limitations.