Getting it into your agent
One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.
npx agentmods add skills/microsoft/hve-core/cavemannpx skills add microsoft/hve-core --skill cavemangit clone --depth 1 https://github.com/microsoft/hve-coreWhat it costs to keep this loaded
Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5 | $0.00029 | $0.01248 |
| Opus 5 | $0.00015 | $0.00624 |
| Sonnet 5 | $0.00006 | $0.00250 |
| Haiku 4.5 | $0.00003 | $0.00125 |
Grade C, and why
caveman scanned grade C with 1 finding against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 3d ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Recursive force deletehighDestructive command
rm -rf with a variable or a broad path is one typo away from removing the wrong tree.
* Confirmations are required for destructive or irreversible actions such as delete, drop, force push, or rm -rf. How it starts
The opening of the file, as written. The whole thing — 105 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Caveman Skill
Overview
Caveman is an opt-in response style that reduces output verbosity while keeping technical content fully intact. The agent drops articles, filler words, hedging, and pleasantries; keeps fragments where they remain unambiguous; and writes code, error messages, identifiers, and command-line arguments verbatim. Use it when the user explicitly requests a terser response.
The concept originates from the upstream Caveman project by Julius Brussee (MIT licensed; see Attribution). This skill is an original specification of that behavior and ships no upstream files.
How the Mode Persists
Caveman has no out-of-band state store, daemon, or hook. Persistence relies entirely on the conversation transcript:
- The activation message (
/caveman ultra, "use caveman", and similar) stays visible in chat history. - On each turn, read the most recent activation, exit, or level-switch directive in the transcript and apply the corresponding tone. The latest matching directive wins.
- The skill file is loaded on demand. Once the rules are in context, keep applying them without reloading. If context is trimmed and the rules drop out, reload
caveman/SKILL.mdthe next time an active directive appears. - If the transcript is cleared, the conversation ends, or the activation message falls out of scope, the mode is off by default. The user re-invokes to turn it back on.
State lives in chat, not in a file. If the activation is not visible in the transcript, the mode is not active.
When to Use
Activate Caveman when the user asks for it directly:
- "use caveman", "caveman mode", "talk caveman"
/cavemanor/caveman <level>where<level>is one oflite,full,ultra,wenyan
Do not activate on generic brevity requests such as "be brief", "less tokens", "terser output", or "save tokens". Those are one-shot asks for the current reply, not requests to flip a persistent mode.
Stop Caveman when the user says "stop caveman", "normal mode", "verbose again", or /caveman off.
What this file has done since we first saw it
Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.
- 3d ago First seen · 105 lines · 29 tokens per session scan C 5f1026bb171b
caveman is a skill published in the GitHub repository microsoft/hve-core (1,411 stars, last pushed yesterday), licensed MIT. It adds 29 tokens to every session and 1,248 once invoked, about $0.0001 per session on Opus 5. A static security scan graded it C with 1 finding (recursive force delete). No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-30.
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