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Get Started Free →Compress natural language memory files (CLAUDE.md, todos, preferences) into caveman format to save input tokens. Preserves all technical substance, code, URLs, and structure. Compressed version overwrites the original file. Human-readable backup saved as FILE.original.md. Trigger: /caveman:compress <filepath> or "compress memory file"
.claude/skills/hoangnguyen0403-caveman-compress/SKILL.md| Test case | Without → With | Effect | Δ tokens | Δ turns |
|---|---|---|---|---|
| case-02 | ✗→✓ | ▲ Improved | 215% | 0% |
| case-04 | ✗→✓ | ▲ Improved | 27% | 0% |
| case-05 | ✗→✓ | ▲ Improved | -1% | 0% |
| case-07 | ✗→✓ | ▲ Improved | -33% | 0% |
| case-09 | ✗→✓ | ▲ Improved | -30% | 0% |
Compress natural language files (CLAUDE.md, todos, preferences) into caveman-speak to reduce input tokens. Compressed version overwrites original. Human-readable backup saved as <filename>.original.md.
/caveman:compress <filepath> or when user asks to compress a memory file.
caveman-compress/scripts/ (adjacent to this SKILL.md). If the path is not immediately available, search for caveman-compress/scripts/__main__.py.cd caveman-compress && python3 -m scripts <absolute_filepath>
and indented)backtick content)/src/components/..., ./config.yaml)npm install, git commit, docker build)$HOME, NODE_ENV)CRITICAL RULE: Anything inside ... must be copied EXACTLY. Do not:
Inline code (...) must be preserved EXACTLY. Do not modify anything inside backticks.
If file contains code blocks:
Original: > You should always make sure to run the test suite before pushing any changes to the main branch. This is important because it helps catch bugs early and prevents broken builds from being deployed to production.
Compressed: > Run tests before push to main. Catch bugs early, prevent broken prod deploys.
Original: > The application uses a microservices architecture with the following components. The API gateway handles all incoming requests and routes them to the appropriate service. The authentication service is responsible for managing user sessions and JWT tokens.
Compressed: > Microservices architecture. API gateway route all requests to services. Auth service manage user sessions + JWT tokens.
| Case | Status | Duration (ms) | Turns | Tokens | Tool calls | ||||||||
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| Without | With | Δ | Without | With | Δ | Without | With | Δ | Without | With | Δ | ||
case-01 | fail→fail | 7,324 | 8,361 | +14% | 1 | 1 | 0% | 367 | 1,380 | +276% | 0 | 0 | — |
case-02 | fail→pass | 5,137 | 14,449 | +181% | 1 | 1 | 0% | 912 | 2,873 | +215% | 0 | 0 | — |
case-03 | fail→fail | 6,033 | 6,078 | +1% | 1 | 1 | 0% | 447 | 1,358 | +204% | 0 | 0 | — |
case-04 | fail→pass | 6,379 | 1,781 | -72% | 1 | 1 | 0% | 1,042 | 1,323 | +27% | 0 | 0 | — |
case-05 | fail→pass | 8,184 | 2,349 | -71% | 1 | 1 | 0% | 1,432 | 1,418 | -1% | 0 | 0 | — |
case-06 | pass→fail | 9,855 | 3,248 | -67% | 1 | 1 | 0% | 1,625 | 1,521 | -6% | 0 | 0 | — |
case-07 | fail→pass | 13,650 | 3,323 | -76% | 1 | 1 | 0% | 2,189 | 1,471 | -33% | 0 | 0 | — |
case-08 | pass→pass | 3,913 | 1,742 | -55% | 1 | 1 | 0% | 594 | 1,268 | +113% | 0 | 0 | — |
case-09 | fail→pass | 11,862 | 2,261 | -81% | 1 | 1 | 0% | 1,981 | 1,388 | -30% | 0 | 0 | — |
case-10 | pass→pass | 12,334 | 2,335 | -81% | 1 | 1 | 0% | 2,027 | 1,393 | -31% | 0 | 0 | — |
case-11 | pass→pass | 8,045 | 3,818 | -53% | 1 | 1 | 0% | 1,317 | 1,620 | +23% | 0 | 0 | — |
case-12 | pass→pass | 11,708 | 3,059 | -74% | 1 | 1 | 0% | 2,025 | 1,458 | -28% | 0 | 0 | — |
case-13 | pass→fail | 9,001 | 2,125 | -76% | 1 | 1 | 0% | 1,450 | 1,268 | -13% | 0 | 0 | — |
case-14 | pass→pass | 14,669 | 4,008 | -73% | 1 | 1 | 0% | 2,522 | 1,696 | -33% | 0 | 0 | — |
case-15 | fail→pass | 13,537 | 3,812 | -72% | 1 | 1 | 0% | 2,287 | 1,649 | -28% | 0 | 0 | — |
case-16 | pass→pass | 9,988 | 2,262 | -77% | 1 | 1 | 0% | 1,662 | 1,359 | -18% | 0 | 0 | — |
case-17 | fail→pass | 5,740 | 1,866 | -67% | 1 | 1 | 0% | 898 | 1,262 | +41% | 0 | 0 | — |
case-18 | pass→pass | 10,164 | 2,724 | -73% | 1 | 1 | 0% | 1,636 | 1,443 | -12% | 0 | 0 | — |
case-19 | fail→pass | 10,848 | 2,619 | -76% | 1 | 1 | 0% | 1,845 | 1,423 | -23% | 0 | 0 | — |
case-20 | fail→pass | 14,096 | 2,742 | -81% | 1 | 1 | 0% | 2,483 | 1,412 | -43% | 0 | 0 | — |
case-21 | pass→pass | 8,050 | 3,286 | -59% | 1 | 1 | 0% | 1,357 | 1,574 | +16% | 0 | 0 | — |
case-22 | pass→pass | 10,532 | 3,073 | -71% | 1 | 1 | 0% | 1,664 | 1,482 | -11% | 0 | 0 | — |
case-23 | fail→pass | 2,381 | 2,535 | +6% | 1 | 1 | 0% | 344 | 1,437 | +318% | 0 | 0 | — |
case-24 | fail→pass | 4,420 | 2,839 | -36% | 1 | 1 | 0% | 750 | 1,463 | +95% | 0 | 0 | — |
case-25 | fail→pass | 9,743 | 2,849 | -71% | 1 | 1 | 0% | 1,684 | 1,444 | -14% | 0 | 0 | — |
DecimalAI ran this skill against gemini-3.6-flash twice over the same eval suite — once with the skill loaded and once without — and compared the two runs case by case. 25 cases were attempted, and 23 counted toward the lift figure. The other 2 produced results that are not comparable between the two arms, so they are excluded from the headline rather than averaged into it. The headline lift of +40 percentage points is the difference between those two pass rates over the 23 comparable cases. 2 cases got worse with the skill loaded, and they are included in that figure.
Without the skill loaded, the model failed this case. With it loaded, the same prompt on the same model passed. This is one improved case from the latest verified run; every case, including any that regressed, is in the table above.
Other measured skills in the registry, with their headline benchmark lift.