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/caveman-manage

Inspect Caveman Cloud's experiment lifecycle and block unsafe execution. Use when asked to start, approve, cancel, promote or roll back a Caveman experiment.

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caveman
105k20 skills3 agents7 commands
Install
$ npx -y skills add JuliusBrussee/caveman --skill caveman-manage --agent claude-code

How it fires

How this skill gets triggered: by you, by Claude, or both.

  • Fires itselfAuto-invocation. Claude auto-loads it when your prompt matches the work.Auto-invocation is when the right skill fires by itself at the right moment, driven by a FLOW.md router and a hook, instead of you invoking it by name. It is the difference between a skill being installed and a skill actually getting used.Read the full definition →
  • You can call itInvoke it directly when you want it.
  • Slash command/caveman-manage

Context preview

The summary Claude sees to decide when to auto-load this skill.

Inspect Caveman Cloud's experiment lifecycle and block unsafe execution. Use when asked to start, approve, cancel, promote or roll back a Caveman experiment.

SKILL.md

caveman-manage.SKILL.md
name: caveman-manage
description: >
  Inspect Caveman Cloud's experiment lifecycle and block unsafe execution. Use
  when asked to start, approve, cancel, promote or roll back a Caveman
  experiment.

Manage eval-gated experiments

Treat every lifecycle change as a production control action. Read current state and results, then report one supported recommendation or block. Current agent MCP is intentionally read-only: control-api does not yet enforce a complete lifecycle transition table and evidence gate atomically.

Non-negotiable gates

1. A request to review, inspect, explain, or recommend authorizes reads only. 2. Never approve an experiment whose results are pending, whose required guardrails are absent, or whose evidence reports a breach. 3. Never convert experiment lift into `verified_savings`. Only active real traffic plus provider-causal, provider-complete ledger evidence can do that. 4. Never supply an organization id. Project and tenant scope come from the logged-in Caveman identity and server RBAC. 5. Never execute a lifecycle mutation, even after user approval. Exact `<action>:<experiment_id>` strings are agent-generatable and are not proof of human intent. 6. Unknown states and server errors fail closed. Report exact `cave_snake_code`.

Step 1 — Load project and experiment

Prefer MCP:

caveman_context {}
caveman_experiment_get {"action":"get","experiment_id":"<id>"}
caveman_experiment_get {"action":"results","experiment_id":"<id>"}

Use `{"action":"list"}` when the user has not named an id.

CLI fallback:

caveman cloud experiments list
caveman cloud experiments show <id>
caveman cloud experiments results <id>

Stop if login, project, experiment, or results are unavailable.

Step 2 — Evaluate evidence

Report:

  • current lifecycle state and safety class;
  • control and candidate sample sizes;
  • quality or eval result;
  • latency, error, cost, retry, drop, and escalation guardrails when present;
  • evidence cost;
  • rollback or hold reason;
  • whether result is pending, failed, promotable, or active.

Absence is not a pass. If a required field is absent, state `evidence incomplete` and do not propose approval.

Step 3 — Propose one action

Allowed actions:

  • `start` — only from a startable draft or queued state with configured graders;
  • `approve` — only with complete passing evidence and a safety class the

current role may approve;

  • `cancel` — stop a non-active experiment the user no longer wants;
  • `rollback` — revert an active or harmful change through the server's linked

policy path. Current deployments may reject this honestly with `cave_not_implemented`; never describe that response as a rollback.

Show recommendation and id:

Proposed action: approve experiment 7f...
Reason: candidate passed quality and every configured guardrail.
Execution: blocked until server-authoritative lifecycle and evidence gates ship.

Do not treat earlier generic statements such as "manage it" or "do what is best" as mutation approval.

Step 4 — Block unsafe execution

Do not emit or run an executable lifecycle command. Explain that current server does not yet enforce every evidence/state transition atomically. CLI and MCP agent surfaces therefore expose experiment reads only.

Step 5 — Re-read after external operator action

If operator says they executed command, read detail and results again. Report server-observed post-state, audit or result response, and any policy-delivery status returned. Never infer success from operator intent alone.

Use this close:

Action: <action> <experiment-id>
Before: <state>
Server response: <status and cave_snake_code if any>
After: <re-read state>
Basis: experiment evidence only. Verified savings unchanged unless the signed
ledger independently records active, provider-causal real-traffic savings.
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