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/rafmacalaba/armada/armada-cavemannpx skills add rafmacalaba/armada --skill armada-cavemangit clone --depth 1 https://github.com/rafmacalaba/armadaWrote 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/rafmacalaba/armada/armada-caveman)<a href="https://agentmods.dev/skills/rafmacalaba/armada/armada-caveman"><img src="https://agentmods.dev/badge/skills/rafmacalaba/armada/armada-caveman.svg" alt="Measured on agentmods" 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 | $0.00025 | $0.00180 |
| Opus 5 | $0.00013 | $0.00090 |
| Sonnet 5 | $0.00005 | $0.00036 |
| Haiku 4.5 | $0.00003 | $0.00018 |
Grade A, and why
armada-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 5d 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.
What it actually says
Armada Caveman
Ultra-compressed, high-density communication mode for non-code writing agents (Caravel, documentation writers, architectural reviewers).
Principles
- Zero Fluff: Remove pleasantries ("Sure!", "Happy to help!"), sign-offs ("Let me know if you need anything else!"), and conversational filler ("What this means is...", "In order to...").
- High Signal: Lead with direct technical facts, file:line references, and concise bullet points.
- 100% Technical Accuracy: Keep exact variable names, API path signatures, terminal commands, and structural details completely intact.
- Maximum Token Efficiency: Cut word count by up to 75% without losing precision or clarity.
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.
- 5d ago First seen · 16 lines · 25 tokens per session scan A 79a976e137aa
armada-caveman is a skill published in the GitHub repository rafmacalaba/armada (93 stars, last pushed 8d ago), licensed MIT. It adds 25 tokens to every session and 180 once invoked, about $0.0001 per session on Opus 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
aoe
Use when launching, monitoring, or controlling AI coding agents (Claude Code, Codex, OpenCode, etc.) in tmux via Agent of Empires (aoe). Covers creating sessions, capturing agent output, running parallel worktree agents, and organizing work into groups and profiles. Prefer aoe over raw tmux for agent management.
aoe
Manage AI coding agent sessions via Agent of Empires (aoe).
app-builder-v2
App Builder - Application Building Orchestrator workflow skill. Use this skill when the user needs Main application building orchestrator. Creates full-stack applications from natural language requests. Determines project type, selects tech stack, coordinates agents and the operator should preserve the upstream…
debate
Structured adversarial analysis protocol. Quick single-agent modes (challenge, panel, pre-mortem, red team) plus a decision-review protocol where one agent proposes, one critiques, the proposer revises, and a binding/advisory judge panel decides ADOPT/REVISE/REJECT/ESCALATE.
reader-report
Reader-first writing for any deliverable a human reads to understand a result: HTML reports, MD design docs, debate-result summaries, survey dashboards, executive briefs, handoff notes, panel-review syntheses. Writes for a reader who has NOT read the preceding material. NOT for: bug reports, incident reports, status…
update-to-latest
Safety-critical operational pipeline for analyzing and executing OpenCode/OMO updates with explicit approval, patch preservation, rollback capability, and evidence-state discipline.