agently-migration

name	agently-migration
description	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.

Agently Migration

Use this Skill only when a source-framework system already exists. Do not translate class names one for one. Inventory the source's observable semantics, assign each to an Agently owner, and preserve those semantics with representative before/after evidence.

Read the Source-Specific Map

• LangChain agents, models, prompts, structured output, tools, retrieval, or short-term memory: langchain-to-agently.md.
• LangGraph graphs, state, checkpoints, interrupts, streams, or subgraphs: langgraph-to-triggerflow.md.
• LlamaIndex agents, loaders, indexes, retrievers, query engines, memory, or Workflows: llamaindex-to-agently.md.
• CrewAI Agents, Tasks, Crews, Processes, Flows, tools, memory, or knowledge: crewai-to-agently.md.

Agently Owner Map

Source behavior	Agently owner
One model call, prompt contract, structured result, or response stream	agently-request / ModelRequest
Model-callable tool, MCP server, sandbox, browser, database, or live client	agently-runtime / ActionRuntime + ExecutionResource
Conversation continuity	Session / SessionMemory
Durable records, links, retrieval, checkpoints, or snapshots	RecordStore
Cross-source task evidence and bounded reads	TaskContext + ContextSource + ContextReader
Stable multi-stage topology, branches, joins, loops, waits, resume, or runtime events	agently-triggerflow / TriggerFlow
Model-owned bounded planning, evidence, verification, and replan	AgentTask through AgentExecution

Do not add TriggerFlow around a single request or Action. Do not flatten a real workflow into one prompt. A source “agent” is not automatically an Agently AgentTask, and a nominal source “workflow” is not automatically orchestration; classify its behavior.

Migration Method

1. Record source inputs/outputs, model calls, tool calls and side effects, state keys and lifetimes, topology, concurrency, retry/error behavior, stream events, checkpoint/resume behavior, memory, retrieval, and authorization.
2. Separate semantic work from deterministic work. Model-owned intent, relevance, planning, and synthesis use ModelRequest output control; host code owns types, arithmetic, offered-key membership, authorization, and effects.
3. Draw the target owner, node, and edge ledgers before choosing files. Preserve externally consumed event and result contracts or introduce an explicit adapter at the boundary.
4. Migrate one representative vertical slice. Compare source and target traces, final artifacts, state transitions, interruption/recovery behavior, and failure semantics before broad replacement.
5. Remove source-framework shims once their last real consumer is migrated. Keep a compatibility adapter only when it owns a released external contract.

Required Cautions

• Preserve checkpoint, interrupt, idempotency, streaming, and subflow semantics explicitly; matching node names is not evidence of equivalent behavior.
• Keep live resources and secrets out of serialized execution state. Persist descriptors and reconstruct through host-owned providers.
• Keep identity joins host-owned. Give the model one offered selection key and rejoin canonical records after validation.
• Do not replace source semantic routing or evaluation with keywords, regex, snapshots, or hardcoded business mappings.
• If Agently lacks a protocol seam needed to preserve an essential source behavior, report the capability gap. Do not conceal it behind a prompt or a deterministic substitute.