caveman-manage
Inspect Caveman Cloud's experiment lifecycle and block unsafe execution
Install / Use
npx skills add JuliusBrussee/caveman --skill caveman-manageInstalls into whichever agent you are using.
SKILL.md
Installable skill definition
Quality Score
Category
Customer SupportSupported Platforms
Our assessment of caveman-manage
caveman-manage scores 91/100 on our quality scale, 122nd of 324 Customer Support skills we index (top 38%).
Its SKILL.md is 3.8 KB long, split into 7 sections with 4 code examples: a solid amount of guidance for an agent.
With 110,210 GitHub stars, it is one of the more widely adopted skills in the catalogue.
Maintenance, license and trust
- The repository was last updated 7 days ago, so caveman-manage is actively maintained.
- Our last check on 2026-10-05 found the source still online.
- It is released under the Apache-2.0 license, a permissive license that allows use, modification and commercial use with attribution.
- Its trust signals score 100/100, with no cautions. These come from repository metadata, not a code audit — read the skill file before letting an agent act on it.
Safety scan
No issues foundOur scan of the whole file found no instruction hijacking, hidden characters, credential access, data exfiltration or destructive commands. An AI review of the same text found nothing harmful.
AI review by kimi-k2.7-code on 2026-09-26. Automated pattern scan on 2026-09-25. It catches known dangerous patterns, not every risk — read a skill before letting an agent act on it.
caveman-manage compared with similar skills
All 4 of these similar skills score higher than caveman-manage; compare them before choosing.
| Skill | Score | Stars | Updated | Format |
|---|---|---|---|---|
| caveman-manage (this skill)by JuliusBrussee | 91 | 110.2k | 7d ago | SKILL.md |
| Agent-Reachby Panniantong | 100 | 97.0k | 5d ago | CLAUDE.md |
| headroomby headroomlabs-ai | 100 | 75.2k | today | CLAUDE.md |
| CowAgentby zhayujie | 100 | 47.4k | today | CLAUDE.md |
| Scraplingby D4Vinci | 100 | 87.3k | 1d ago | MCP Server |
Frequently asked questions
- How do I install caveman-manage?
- Run
npx skills add JuliusBrussee/caveman --skill caveman-manage. The install tabs above show the steps for each supported agent. - Which AI agents does caveman-manage work with?
- It is written for Universal, as a SKILL.md file. Other agents that read the same format can often use it too.
- Is caveman-manage safe to use?
- Our scan of the whole file found no instruction hijacking, hidden characters, credential access, data exfiltration or destructive commands. An AI review of the same text found nothing harmful. It is Apache-2.0-licensed and scores 100/100 on trust signals. Skills are instructions an agent will follow, so read the file before installing it and do not approve commands you do not understand.
- Is caveman-manage still maintained?
- The repository was last updated 7 days ago, so caveman-manage is actively maintained.
Skill content
View source on GitHubname: 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
- A request to review, inspect, explain, or recommend authorizes reads only.
- Never approve an experiment whose results are pending, whose required guardrails are absent, or whose evidence reports a breach.
- Never convert experiment lift into
verified_savings. Only active real traffic plus provider-causal, provider-complete ledger evidence can do that. - Never supply an organization id. Project and tenant scope come from the logged-in Caveman identity and server RBAC.
- Never execute a lifecycle mutation, even after user approval. Exact
<action>:<experiment_id>strings are agent-generatable and are not proof of human intent. - 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 withcave_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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Languages
Trust signals
From repository metadata: license, adoption, age and documentation. Not a code audit — see the Safety scan above for what the skill file itself contains.
