inngest-agentslisted
Install: claude install-skill DrOlu/agent-skills
# Inngest Agents
Use this skill when the user wants to build, migrate, or debug an AI agent,
multi-step AI workflow, tool-calling loop, support agent, research agent,
human-in-the-loop review flow, or realtime agent UI.
Inngest's AgentKit defines agents with `createAgent`; when an AgentKit run is
owned by an Inngest function, model calls use Inngest `step.ai` so they retry
and cache model results durably. Use the lower-level Inngest step primitives
around the agent for database reads/writes, tool side effects, waits,
approvals, realtime progress, and flow control.
Official references:
- AgentKit agents: https://agentkit.inngest.com/concepts/agents
- `createAgent`: https://agentkit.inngest.com/reference/create-agent
- AI inference and `step.ai`: https://www.inngest.com/docs/features/inngest-functions/steps-workflows/step-ai-orchestration
- Agent Evals: https://www.inngest.com/docs/learn/agent-evals
- AgentKit realtime hooks: https://www.inngest.com/changelog/2025-09-24-agentkit-use-agent
## Copyable Example
When starting a durable support or tool-calling agent from scratch, inspect the
companion example at `../../examples/durable-agent`. It shows the expected
agent-first shape: quick HTTP trigger, typed events, AgentKit inside an
Inngest function, step-scoped context loading, human approval with
`step.waitForEvent`, and durable side effects after approval.
## When to Use Inngest for Agents
Good fit:
- Agent can take longer than one HTTP request.
- Agent calls tools, A