agentera/agently-migration
skills/agently-migration/SKILL.md
Use when the user wants to migrate an existing LangChain, LangGraph, LlamaIndex, CrewAI, or similar system into Agently, including choosing whether the source belongs to request/agent-side Agently behavior or TriggerFlow orchestration.
$ install --global
skillsauthnpx skillsauth add agentera/agently-skills agently-migrationInstall this skill globally with one command. Works with Claude Code, Cursor, and Windsurf.
Security Scan Results
3 of 9 scanners reported clean
Some scanners were skipped, did not run, or reported a non-clean status. Review each row below.
3
Scanners Passed
9
Scanners in report
Clean
TrivyContainer and dependency vulnerability scanner
95%
Clean
SemgrepStatic code analysis for vulnerabilities
95%
Clean
mcp-scan (Snyk)Model Context Protocol security validation
95%
Skipped
Snyk (dep)Open source security scanning
50%
Skipped
Socket.devSupply chain security analysis
50%
Skipped
VirusTotalMulti-engine malware detection
50%
Skipped
CrowdStrikeAdvanced threat intelligence
50%
Skipped
OSV-ScannerOpen Source Vulnerability database check
50%
Skipped
OWASP Dep-Check
50%
Last scanned: Jun 9, 2026, 4:12 AM419.3s6 files scanned
SKILL.md
- name:
- agently-migration
- description:
- Use when the user wants to migrate an existing LangChain, LangGraph, LlamaIndex, CrewAI, or similar system into Agently, including choosing whether the source belongs to request/agent-side Agently behavior or TriggerFlow orchestration.
Agently Migration
Use this skill for framework migration work. Start here when the source system already exists and the main decision is how to map it into Agently-native layers.
If the user is not migrating an existing framework, start with
agently.
Route Inside This Skill
- unresolved migration ownership or mixed LangChain/LangGraph source ->
references/migration-playbook.md - LangChain agent-side setup, tools, structured output, retrieval, or short-term memory ->
references/langchain-to-agently.md - LangGraph orchestration, stages, checkpoints, interrupts, persistence, streaming, or subgraphs ->
references/langgraph-to-triggerflow.md
Native-First Rules
- classify the source system before producing implementation steps
- map LangChain agent-side behavior into
agently-requestandagently-runtime - map LangGraph orchestration behavior into
agently-triggerflow - preserve explicit checkpoints, interrupts, persistence, and streaming semantics when they exist in the source
- use migration-specific compatibility notes only when the source API forces them
Anti-Patterns
- do not flatten graph orchestration into one large request
- do not preserve old abstractions when Agently has a direct native surface
- do not mix agent-side and orchestration-side migration guidance without naming the owner layer first
Read Next
references/migration-playbook.mdreferences/langchain-to-agently.mdreferences/langgraph-to-triggerflow.md
Related Skills
agentera/agently
tools
VerifiedTrustedCommunity
Use when the user wants to build, initialize, validate, optimize, or refactor a model-powered assistant, internal tool, automation, evaluator, or workflow from a business scenario or common problem statement, including project-structure refactors or starter skeletons that may separate model setup, prompt config, and orchestration, even if the request also mentions a UI, app shell, or local model service such as Ollama, and it is still unclear whether the solution should stay a single request, add supporting capabilities, or become orchestration. The user does not need to mention Agently explicitly.
16SKILL.mdUpdated Jun 9, 2026
agentera/agently-dynamic-task
data-ai
VerifiedTrustedCommunity
Use when the user needs Agently TaskDAG / Dynamic Task, model-generated or app-submitted DAG planning, TaskDAG validation, DynamicTaskResolver handlers, TaskDAGExecutor execution, or the Agently.create_dynamic_task compatibility facade. TaskDAG is the DAG foundation capability; Dynamic Task is the convenience facade over it and uses TriggerFlow as the execution substrate.
16SKILL.mdUpdated May 21, 2026
agentera/agently-runtime
tools
VerifiedTrustedCommunity
Use when the user wants Agently runtime extension capabilities: Action Runtime, built-in action packages, legacy tool compatibility, MCP access, Execution Environment lifecycle, FastAPIHelper or streaming API exposure, auto-function helpers, KeyWaiter, or optional agently-devtools observation, evaluation, and playground integration.
16SKILL.mdUpdated May 17, 2026
agentera/agently-request
development
VerifiedTrustedCommunity
Use when the user is shaping Agently request-side behavior: model setup, settings files, prompt management, structured output, response reuse, streaming consumption, session memory, embeddings, knowledge-base indexing, retrieval, or retrieval-backed answers within one request family.
16SKILL.mdUpdated May 17, 2026