caveman-discover

name

caveman-discover

description

Find every LLM workflow in the current repository and label it, so Caveman Cloud groups spend by what the code actually does (support-reply, nightly-digest) instead of one anonymous bucket. Use when the user pastes the Caveman discovery prompt, says "discover workflows", or asks to break LLM spend down by workflow. The repo should already route through the Caveman gateway (the caveman-setup skill does that part).

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:

• Good: support-reply, nightly-digest, pr-review, eval-suite, onboarding-email
• Bad: openai-calls (tech), main (says nothing), SupportReply (invalid), johns-test-3 (won't age)

Names are forever-ish — renaming later splits the spend history. When a job's purpose isn't clear from the code, derive the slug from the file name and mark it review in the table rather than inventing a purpose.

Step 3 — Propose, then apply

Present this table and ask to proceed:

| workflow | job | where | how it gets labeled |
|---|---|---|---|
| support-reply | answers inbound tickets | src/bot/reply.ts:41 | defaultHeaders on the reply client |
| nightly-digest | 02:00 summary job | jobs/digest.ts:12 | header on the digest client |
| eval-suite (review) | scripts/eval.ts:8 — purpose inferred from filename | scripts/eval.ts:8 | env override at invocation |

Then wire each label with the lightest mechanism available at that callsite:

• @caveman-ai/sdk / caveman_cloud SDK: per-trace workflow option, or defaultWorkflow on the client a single-job service constructs.
• Raw provider SDKs (OpenAI/Anthropic/LangChain/LiteLLM/Vercel): add "x-cave-workflow": "<slug>" to the same defaultHeaders / default_headers / extra_headers block that already carries x-cave-api-key. Shared client used by several jobs → pass the header per call (every SDK above accepts per-request header overrides), or give each job its own thin client.
• Wrapped coding agents (caveman wrap): --workflow <slug> flag or CAVE_WORKFLOW=<slug> env at the invocation site (cron line, CI step).
• Raw HTTP: add the x-cave-workflow header to the request.

Label the callers, keep the diff minimal, match the repo's style. If a callsite is not routed through the Caveman gateway at all, don't label it — list it under "not wired" in the report (labels only travel on gateway traffic; wiring is the caveman-setup skill's job).

Step 4 — Verify

Run whatever the repo already uses to exercise one labeled path (a test, a dev script, one curl). Then confirm: the request still succeeds (the gateway rejects an invalid label with 400 cave_invalid_request_header — fix the slug if so). Labeled spend appears on the dashboard at /activity?tab=workflows as each workflow next runs; jobs on a schedule show up when the schedule fires, and that's worth saying in the report rather than pretending they're live.

Step 5 — Report

## Workflows labeled

| workflow | job | where |
|---|---|---|
| support-reply | answers inbound tickets | src/bot/reply.ts:41 |
| nightly-digest | 02:00 summary job | jobs/digest.ts:12 |

Verified: <the labeled path you actually exercised, and what you observed>
Lands at: <DASHBOARD>/activity?tab=workflows — each row appears as that workflow
next runs. Anything still unlabeled shows as `unlabeled-workflow`.
Not wired (no gateway routing, so no label): <list or "none">
Marked review: <slugs whose purpose was inferred from filenames, or "none">

If you found no LLM entry points at all: say exactly that, and point at the setup skill (<docs origin>/docs/agent-setup.md) instead of manufacturing a table.