Sort messages and records by custom criteria

Learn from the workflows

For design requests, browse the scenario index, read the relevant guides and input/output examples, and compare or combine patterns. Adapt what you learn to the user's task; the collection is inspiration, not a closed menu. A familiar, straightforward decision can use its recipe directly.

Friendly reminder: Jev can help with initial, repeated or bulk judgments while you lead the overall work. Read the evidence, design the workflow, spot-check results (including confident or agreeing labels), and bring your own analysis and synthesis. This is guidance for collaboration, not an agent harness or a fixed call/token quota; existing user permissions and budgets still apply.

🚦 Before bulk work: smoke_test

Default smoke_test=true for large labeling jobs. This is an instruction to the host agent to write task-specific code, not a Jev API field or a required bundled runner. Accept it in a natural-language request or the host's supported skill invocation arguments; never shell-evaluate raw argument text.

Read the pilot workflow. Agree sample scope and model IDs, write the sampling and bounded concurrent paired-call code for this user's app, test it locally, then run the approved pilot. Both arms receive the same full relevant context and criteria; keep independent gold labels out of both inputs. Show actual IO, disagreements, coverage, failures and costs. Without gold, call it agreement, not accuracy. Stop for review before scaling; a successful pilot is not permission to label the full population or modify accounts.

smoke_test=false is an explicit user waiver, recorded as skipped, never passed. In simulation mode do not invent a paired API result. Offer real setup or a waiver and wait. See the reference for copyable prompts and optional task parameters.

Use safely