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caveman-manage

by @juliusbrusseev
4.8(120)

此技能管理评估门控的实验生命周期,提供基于证据的实验审批建议,并阻止未经授权的变更,确保实验安全合规。适用于A/B测试、模型实验等场景,帮助团队降低风险,提高实验管理效率。

experiment-managementeval-gatedmlopssafetygovernanceGitHub
安装方式
npx skills add https://github.com/juliusbrussee/caveman --skill caveman-manage
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Before / After 效果对比

1 组
使用前

在没有此技能之前,团队手动检查实验结果和状态,容易遗漏安全门禁,导致有缺陷的变更被批准,审批流程耗时较长。

使用后

使用此技能后,它自动读取实验证据,提供明确的推荐并阻止不安全操作,审批时间大幅缩短,错误率显著降低。

SKILL.md

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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统计数据

安装量101.9K
评分4.8 / 5.0
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更新日期2026年10月24日
对比案例1 组

用户评分

4.8(120)
5
37%
4
43%
3
13%
2
5%
1
2%

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创建2026年8月13日
最后更新2026年10月24日
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