Discover LLM Workflows

You are labeling this repository's LLM workflows for Caveman Cloud. A workflow is a job the code performs, "answer a support ticket", "build the nightly digest", "run the eval suite", not a technology. Every gateway request can carry a workflow label; unlabeled traffic all lands in one unlabeled-workflow bucket. Your job: find the workflows, name them well, wire the labels, and verify nothing broke.

This changes code, so it goes through the user's normal review: propose the table first, apply after the user agrees. Re-running on an already-labeled repo must change nothing (idempotent).

This skill is operator-invoked. An unlabeled-traffic Cave Plan observation is review-only and does not create an advisory file, proposal, or Draft PR. Do not infer that telemetry selected a callsite or authorized an edit. Independently inventory the repository, present the labeling table, and wait for the user's approval before changing code.

Step 1, Inventory the workflows

Walk the repo from its entry points, not from its imports:

• HTTP/RPC handlers that call an LLM (directly or through layers)
• Scheduled jobs: cron definitions, queue consumers, workers, GitHub Actions that invoke LLM code
• CLI commands and scripts (scripts/, bin/, package.json scripts)
• Eval / test harnesses that burn real tokens
• Distinct agents or chains inside a framework (each LangGraph graph, each crew, each agent definition is usually its own workflow)

One workflow = one job a human would name. Ten callsites inside the same request handler are one workflow; one shared llm.ts helper used by three jobs is three workflows (label at the callers, never the shared helper).

Step 2, Name them

Slug grammar (the gateway enforces this): lowercase [a-z0-9_-], 1, 96 chars. Name the job, not the tech: