caveman-setup
Wire a repository through the Caveman Cloud gateway so every LLM request is measured, with no behavior change. Use for "set up caveman" or adding LLM spend observability.
By juliusbrussee · 45,344 installs
npx skills add juliusbrussee/caveman --skill caveman-setup
Source repository · Upstream listing
You are wiring this repository through the Caveman gateway. Caveman is a
byte preserving LLM proxy: in record mode it measures what your app sends and
what it costs, and changes nothing else. Your job is a minimal, verified
integration — not a refactor.
The prompt that sent you here provides four values. Refer to them as:
GATEWAY — the gateway base URL (e.g. https://gateway.caveman.so or http://127.0.0.1:8787 )
CAVE API KEY — the gateway auth secret (treat like any API key: env var only, never committed, never printed in full)
PROVIDER KEYS — stored (provider keys live encrypted in Caveman Cloud) or byok (this app sends its own provider key per request)
DASHBOARD — the dashboard base URL (e.g. https://app.caveman.so )
If any value is missing, stop and ask for it. Do not guess a URL or mint a key.
Rules (non negotiable)
1. Coherent integration. Wire every live LLM callsite through existing
configuration and responsible seams. Touch each layer correctness requires.
No drive by refactors or formatting sweeps; add an abstraction only when it
clarifies ownership or lowers lifecycle cost.
2. Secrets stay in env vars. CAVE API KEY goes into the env file the repo
already uses ( .env , .env.local , …). If that file isn't gitignored, add it
to .gitignore and say so. Never hardcode the key in source.
3. Report only what you observed. The final report states the HTTP status
and usage numbers from the real verification response — never assumed
success. If verification fails, report the failure template instead.
4. Record mode only. You are adding measurement. You do not enable any
optimization, and you do not claim any savings — verified savings are $0
until an optimizer is explicitly turned on and passes its eval gate.
5. Provider keys are not your business. With PROVIDER KEYS: stored you
never see one. With byok , the app's existing provider key stays exactly
where it already is.
Step 1 — Find every live LLM callsite
Read dependency files ( package.json , requirements.txt , pyproject.toml ,
go.mod , lockfiles) and search the source for LLM clients:
SDK imports: openai , @anthropic ai/sdk , anthropic , ai +
@ai sdk/ (Vercel), langchain , litellm , google genai /
@google/genai , crewai , pydantic ai , openai agents / agents
Raw HTTP to api.openai.com , api.anthropic.com , generativelanguage.googleapis.com
Existing base URL env vars: OPENAI BASE URL , OPENAI API BASE ,
ANTHROPIC BASE URL , GEMINI BASE URL , GOOGLE GEMINI BASE URL
List what you found (file:line per callsite) before changing anything. If you
find no LLM callsites, stop and report the "nothing to wire" template at
the end of this file — do not invent an integration.
Step 2 — Pick the app slug
One slug names this app in the gateway path: GATEWAY/w/<app . Derive it from
the package/module name (e.g. support bot , acme api ). Grammar:
lowercase [a z0 9] first, then [a z0 9. ] , max 64 chars. Spend for this
whole app groups under that slug on the dashboard.
Step 3 — Wire each callsite
The pattern is always the same: base URL → the gateway with /w/<app ,
plus one auth header. Gateway auth is x cave api key: CAVE API KEY
( Authorization: Bearer CAVE API KEY also works where a header is awkward).
With PROVIDER KEYS: byok , also send x cave upstream key: <the provider key
the app already uses .
Two facts that make the wiring safe (both are gateway enforced, not hopes):
the gateway rebuilds upstream auth headers from scratch, so a client's
Authorization / x api key value is never forwarded to the provider; and with
stored , upstream auth comes from the encrypted connection server side. So in
stored mode, where an SDK insists on an api key parameter, set it to the
Cave key — it authenticates the gateway and goes no further.
Exact shapes (use the one matching each callsite — these are the product's
published recipes, not suggestions):
OpenAI SDK (TS) — Chat Completions and Responses both route through:
OpenAI SDK (Python) — same shape: base url=f"{gw}/w/<app /openai/v1" ,
default headers={"x cave api key": ..., "x cave upstream key": ...} .
Anthropic SDK (TS/Python) — the SDK appends /v1/messages itself. The
x cave api key header is required here in both modes (this SDK's own key
param rides x api key , which is not a gateway auth header):
Vercel AI SDK — createOpenAICompatible({ baseURL: ${gw}/w/<app /openai/v1 ,
headers: { "x cave api key": ... } }) ; Anthropic models via
createAnthropic({ baseURL: ${gw}/w/<app /v1 , headers: { ... } }) .
LangChain / LangGraph — ChatOpenAI(base url=f"{gw}/w/<app /openai/v1",
default headers={...}) ; ChatAnthropic(base url=f"{gw}/w/<app ",
default headers={...}) . LangGraph inherits whatever model you pass it.
LiteLLM — per call api base=f"{gw}/w/<app /openai/v1" +
extra headers={...} , or fleet wide in the LiteLLM proxy config.yaml .
Raw HTTP / anything else — swap the host, keep the provider's native path:
GATEWAY/w/<app /v1/chat/completions (OpenAI protocol) or
GATEWAY/w/<app /v1/messages (Anthropic protocol), add the header(s).
Concretely, with slug support bot and the hosted gateway, an OpenAI SDK base
URL reads https://gateway.caveman.so/w/support bot/openai/v1 . And in stored
mode, drop every x cave upstream key line entirely — it is byok only.
For frameworks not listed (google genai, crewai, pydantic ai, openai agents),
fetch the matching page under <docs origin /docs/integrations/ — same origin
this skill came from — and follow it.
Add to the repo's env file (and reference from code — no literals):
Step 4 — Verify with one real request
The user pasted the setup prompt to authorize exactly this: one small
verification request. Send it now — do not pause to ask permission for it.
An integration that ends unverified because you hesitated is a worse outcome
than one tiny request; finishing the verification and the report autonomously
is the point of this skill.
Send one minimal request through the wiring you just built — the app's own
cheapest path if it has a script for it, otherwise curl on the path matching
the protocol you just wired with the app's own model and a small cap
( max tokens ≤ 32):
(byok: add H "x cave upstream key: $PROVIDER KEY" .) This is one real,
billable provider request — that is the point: real traffic, real measurement.
Read the response. Success = HTTP 200 with a usage block. Anything else =
the matching failure template below.
Step 5 — Report
End with exactly this shape, values filled from what you actually did and saw:
Failure templates (use verbatim, filled in — never soften)
Nothing to wire : "I found no LLM callsites in this repo (searched SDKs,
raw provider HTTP, base URL env vars). If this repo runs a coding agent
rather than shipping LLM code, use caveman wrap <agent instead — see
<DASHBOARD /getting started."
Gateway unreachable : "The verification request could not reach GATEWAY
(<error ). Wiring is in place but unverified — nothing will be measured
until the gateway is reachable. Check the URL and network, then re run the
verification curl above."
401 cave invalid api key : "The gateway rejected CAVE API KEY. Mint a new
key at <DASHBOARD /getting started and update the env file; the wiring
itself is unchanged."
404 cave route not found : "The gateway matched no route — usually a
malformed /w/<app slug (lowercase [a z0 9] first, then [a z0 9. ], max 64)
or a path that doesn't match the SDK's protocol. Fix the URL and re verify."
Provider error (4xx/5xx via gateway) : report status + body verbatim; the
gateway is reachable and auth passed, the upstream call failed — usually a
provider key or model name issue in the app itself.
Never report success on any of these. An unverified integration is reported as
unverified.