No, you should not infer lower total cost from 65%, because that number describes output savings in a specific benchmark.

• The README’s “The numbers” section separates tokens the agent writes from tokens it reads and says reading is usually the larger billing source.
• The project insight says 65% came from output comparisons across ten specific tasks, with input and reasoning tokens unchanged; the Skill itself also adds roughly 1,000–1,500 input tokens.
• The Proxy targets input-context compression, with project data reporting about 33% input-token savings, but that is not a guarantee for every agent, model, or session.
• The project provides /caveman-stats to inspect local Claude Code session usage and estimated savings. That is more relevant than multiplying 65% by your bill.

No, ultra should not be your default because your tasks require complete risk disclosure, while the project explicitly warns that aggressive compression can become too terse.

• The Skill provides lite, full, and ultra intensities; ultra optimizes brevity rather than producing a complete review record.
• The project insight says ultra-like modes may omit explanations, assumptions, risks, or verification results.
• Its limitations specifically call out security reviews, production migrations, and high-risk operations: optimizing for short answers can remove necessary reasoning and warnings.
• You can still use safe-refactor, migration, and verify-and-stop, but the README does not guarantee that these modes emit every audit field you require.

Yes, the Skill fits because it compresses the agent’s wording without rewriting code or exact error messages.

• The README’s React example reduces a normal explanation from 69 tokens to 19 while preserving the same diagnosis and useMemo fix.
• It explicitly says, “Code, commands, file paths, and exact error messages never get cavemanned,” which matches your debugging constraint.
• Claude Code is supported, and the Skill offers lite, full, ultra, and off modes, so you do not have to begin with the most aggressive setting.
• However, the rule file itself adds input tokens. The README’s 65% figure concerns output savings, not guaranteed total-session or billing savings.

It depends: the runtime prerequisite is achievable, but sensitive-data governance and the commercial license may still rule out the Proxy.

• The README says the Proxy runs between the agent and the AI provider and compresses what the agent reads before each call, directly targeting input-context usage.
• Compressed content is backed up on local disk so the agent can recover the original. Source code, logs, or data near credentials could therefore be stored locally.
• The full installer requires Node.js 22.13+, and the licensing differs: the CLI is MIT while the runtime is BSL-1.1.
• If your organization cannot accept local raw-content backups, a middle-layer proxy, or BSL-1.1, do not enable the Proxy directly; the MIT Skill is a narrower alternative.

Yes, the README supports this setup with a Windows installer, a Gemini extension path, and a Qwen Code package-plus-wrapper path.

• The Windows route explicitly requires PowerShell 5.1+ and provides an install.ps1 command pinned to v2.6.0.
• Gemini CLI has its own command, gemini extensions install https://github.com/JuliusBrussee/caveman, rather than using the Claude Code plugin flow.
• Qwen Code is installed with npm and then launched through the caveman qwen wrapper, matching the unified CLI entry points listed in the README.
• However, the full installer discovers agents and configures hooks and a statusline. The README does not say whether those extras behave identically for Gemini and Qwen on Windows.

Yes, provided the agents can all accept a shared concise-response policy.

• The README says the Small rock works with 30+ agents and explicitly lists Claude Code, Codex, Gemini, Cursor, Windsurf, Cline, and Copilot.
• The same Skill exposes /caveman, /caveman-review, /caveman-commit, and work patterns such as investigate-first, safe-refactor, and migration, enabling a common workflow vocabulary.
• The README also gives agent-specific installation commands, such as npx skills add ... -a codex --yes for Codex. This indicates shared Skill content, but potentially different deployment entry points.
• If the team requires agent-specific output schemas or completely separate prompt governance, Caveman’s common rules may be too coarse.