LangGraph runs
An agent run is a stream of events over HTTP, which means a request tool can debug one — if it knows how to render what comes back. Tinspec treats LangGraph runs as a first-class protocol for exactly that.
There is no new request path underneath: the engine sends it as plain HTTP with SSE. What is new is the authoring form and the run view.
Author a run
Section titled “Author a run”LangGraph requests are not in the generic protocol switcher — they have their own editor and their own navigator section, the way chains do. The editor gives you:
- Input — the JSON payload template for the run.
{{variables}}resolve as usual. - Stream mode —
stream(events as they arrive) orbuffered. - Events version — the event schema version to request.
- Custom fields — dot-paths into each raw event, surfaced as extra columns in the timeline. This is the part that makes a specific graph readable: name the fields your nodes actually set and they appear on every event.
Read the run
Section titled “Read the run”The run replaces the generic response pane with a dedicated view of five tabs:
| Tab | What it shows |
|---|---|
| Timeline | Every event in order, with your custom fields as columns |
| Messages | The conversation as messages rather than raw events |
| Tool calls | Each tool invocation and its result |
| State | Graph state, with nested sections collapsible |
| Raw | The undecoded stream |
Runs are kept in their own per-run history, so you can reopen an earlier run and compare.
Limits
Section titled “Limits”- Not chainable. A run is a multi-event stream, not one response, so a LangGraph request cannot be a chain step. It is excluded from the request picker for the same reason WebSocket is.
- Not exposed to agents. The MCP tools do not cover LangGraph runs at v0.1.0-preview.9.
- A missing custom-field path renders blank rather than erroring, so a path that does not match simply shows nothing.
In the file format
Section titled “In the file format”- name: Support agent run protocol: langgraph method: POST url: "{{baseUrl}}/threads/{{threadId}}/runs/stream" langgraph: input: '{"messages":[{"role":"user","content":"refund my order"}]}' streamMode: stream customFields: - name: node path: metadata.langgraph_node - name: step path: metadata.langgraph_stepcustomFields[].path is a simple dot-path into the raw event’s data.