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web/.agents/skills/caveman-discover/SKILL.md

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+---
+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.