Jinba
Shanone’s Jinba integration gives your agent 1 tool: running a published Jinba Flow workflow with custom input arguments. Jinba Flow itself is a no-code, natural-language workflow builder — Shanone’s role is simply to trigger workflows you’ve already built and published there.Getting Started
1
Get your Jinba API Key
Generate a key from Settings → API in your Jinba account.
2
Add it to Shanone
Open Integrations in the Shanone dashboard, select Jinba, and paste in your API Key.
3
Retry your request
Once saved,
shanone_execute_tool calls for jinba_run_workflow will succeed.Available Tools
Shanone provides 1 tool for Jinba:Workflow execution
Workflow execution
jinba_run_workflow — execute a published Jinba Flow workflow by its UUID, optionally passing a JSON array of {name, value} input arguments defined by the workflow’s INPUT_ configurationCommon Use Cases
Chat-triggered automation
Let a chat request kick off a pre-built Jinba workflow instead of rebuilding logic elsewhere
Parameterized runs
Pass different input arguments to the same published workflow for different requests
Cross-tool orchestration
Use a Jinba workflow as one step in a larger agent task that spans multiple integrations
Long-running task delegation
Hand off complex multi-step logic to a workflow built visually in Jinba rather than in-prompt
Troubleshooting
jinba_run_workflow fails saying the workflow can't be found
jinba_run_workflow fails saying the workflow can't be found
The workflow must be published in Jinba Flow before it’s runnable via the API — a workflow only saved as a draft in the editor won’t be reachable, and double-check the UUID from the Jinba Flow dashboard.
jinba_run_workflow returns an error about missing or invalid arguments
jinba_run_workflow returns an error about missing or invalid arguments
args must be a JSON string representing an array of {"name": ..., "value": ...} objects — check the workflow’s INPUT_ tools configuration in Jinba to see which argument names it expects.jinba_run_workflow takes a long time to return
jinba_run_workflow takes a long time to return
Execution time depends on workflow complexity; the underlying request allows up to 120 seconds, so a complex multi-step workflow may legitimately take that long before returning a result.