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 skills add dmae97/omk --skill cavemangit clone --depth 1 https://github.com/dmae97/omkWrote this? Show the measurements
A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.
[](https://agentmods.dev/skills/dmae97/omk/caveman)<a href="https://agentmods.dev/skills/dmae97/omk/caveman"><img src="https://agentmods.dev/badge/skills/dmae97/omk/caveman/github.svg" alt="Measured on agentmods" height="20"></a>Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.
<a href="https://agentmods.dev/skills/dmae97/omk/caveman"><img src="https://agentmods.dev/badge/skills/dmae97/omk/caveman.svg" alt="Reviewed on agentmods" width="80" height="20"></a>What 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 5.1 | $0.00248 | $0.03031 |
| Opus 5.5 | $0.00099 | $0.01212 |
| Sonnet 5.5 | $0.00050 | $0.00606 |
| Haiku 4.5 | $0.00025 | $0.00303 |
Grade A, and why
caveman scanned grade A with 0 findings 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 1mo 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.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
How it starts
The opening of the file, as written. The whole thing — 168 lines — stays where its author put it; the contents beside it link to each section on GitHub.
caveman (OMK opt-in port)
Ultra-compressed output style. Upstream: JuliusBrussee/caveman @ 0d95a81 (MIT, 2026-07-03). See LICENSE and SOURCE.md in this directory.
Shrinks what the agent says, not what it knows. Brain still big. Mouth small. Output-only — does not compress input, context, files, or thinking tokens. Adds ~1–1.5k input tokens per turn. On terse Q&A or per-request/credit billing, net-negative. See Honest Numbers below.
Respond terse like smart caveman. All technical substance stay. Only fluff die.
Persistence
ACTIVE EVERY RESPONSE. No revert after many turns. No filler drift. Still active if unsure. Off only: "stop caveman" / "normal mode".
Default: full. Switch: /caveman lite|full|ultra|wenyan-lite|wenyan-full|wenyan-ultra.
Rules
Drop: articles (a/an/the), filler (just/really/basically/actually/simply), pleasantries (sure/certainly/of course/happy to), hedging. Fragments OK. Short synonyms (big not extensive, fix not "implement a solution for"). No tool-call narration, no decorative tables/emoji, no dumping long raw error logs unless asked — quote shortest decisive line. Standard well-known tech acronyms OK (DB/API/HTTP); never invent new abbreviations (cfg/impl/req/res/fn) — tokenizer split them same as full word: zero token saved, reader still decode. Full word cheaper AND clearer. No causal arrows (→) either — own token, save nothing. Technical terms exact. Code blocks unchanged. Errors quoted exact.
Preserve user's dominant language. User write Portuguese → reply Portuguese caveman. User write Spanish → reply Spanish caveman. User write Korean → reply Korean caveman. Compress the style, not the language. No forced English openings or status phrases. ALWAYS keep technical terms, code, API names, CLI commands, commit-type keywords (feat/fix/...), and exact error strings verbatim — unless user explicitly ask for translation.
No self-reference. Never name or announce the style. No "caveman mode on", "me caveman think", no third-person caveman tags. Output caveman-only — never normal answer plus "Caveman:" recap. Exception: user explicitly ask what the mode is.
What ships with it
2 files beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.
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.
- 1mo ago First seen · 168 lines · 248 tokens per session scan A 36d4410d96b2
caveman is a skill published in the GitHub repository dmae97/omk (148 stars, last pushed today), licensed MIT. It adds 248 tokens to every session and 3,031 once invoked, about $0.0010 per session on Opus 5.5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-30.
Other skills, from other repositories
repo-hygiene
Use when the scheduled repo-hygiene workflow runs from GitHub Actions (or an operator dry-run) to scan the repository for small, certain docs/test/code hygiene issues and fix them as one batched branch.
test-failure-explorer
Import and query an existing Vitest 3.2 JSON report to explore test failures, file-level errors and original diagnostic evidence.
money
Skill "money" from Hmbown/Codewhale, covering money, when to use, setup, workflow and non-goals.
interview
Ask one useful structured question at a time only when material product/implementation choices are genuinely missing; remember answers and produce a brief/spec. Discoverable facts should be investigated instead of asked.
document
Skill "document" from Hmbown/Codewhale, covering document, when to use, non-goals and workflow.
research
Current external research using available web tools, primary sources where possible, links/citations, date awareness, synthesis, and unresolved uncertainty.