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 alivirgo/Major-AI-Skills --skill compressed-system-promptsgit clone --depth 1 https://github.com/alivirgo/Major-AI-SkillsWrote 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/alivirgo/major-ai-skills/compressed-system-prompts)<a href="https://agentmods.dev/skills/alivirgo/major-ai-skills/compressed-system-prompts"><img src="https://agentmods.dev/badge/skills/alivirgo/major-ai-skills/compressed-system-prompts/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/alivirgo/major-ai-skills/compressed-system-prompts"><img src="https://agentmods.dev/badge/skills/alivirgo/major-ai-skills/compressed-system-prompts.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 | $0.00023 | $0.01237 |
| Opus 5 | $0.00012 | $0.00619 |
| Sonnet 5 | $0.00005 | $0.00247 |
| Haiku 4.5 | $0.00002 | $0.00124 |
Grade A, and why
compressed-system-prompts 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 yesterday.
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 — 113 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Compressed System Prompts (Prompt Minification Protocol)
Overview
Many production system prompts suffer from Rhetorical Bloat: long-winded, repetitive paragraphs written in conversational English ("You are a polite, helpful AI assistant. It is very important that you always strive to write clean, maintainable code, and please make sure to never introduce bugs or hallucinations...").
Rhetorical bloat dilutes attention weights, increases baseline turn latency, and wastes thousands of input tokens on every single turn.
The Compressed System Prompt Protocol minifies natural language instructions into high-density imperative grammar and structured XML tags, reducing system prompt token count by 70% while increasing model adherence and determinism.
Rhetorical Bloat vs. Minified Imperative Grammar
┌─────────────────────────────────────────────────────────────┐
│ System Prompt Density Mapping │
│ │
│ Wordy Rhetorical System Prompt (480 Tokens): │
│ "You are a coding assistant. Whenever a user asks you to │
│ edit code, you should please make sure to read the file │
│ carefully. It is critically important that you do not │
│ make assumptions about functions that might not exist. │
│ Always strive to write comprehensive unit tests with 100% │
│ coverage and please provide clean explanations..." │
│ ↳ 480 tokens of polite fluff, diffuse attention │
│ │
│ Minified Imperative Token Structure (95 Tokens - 80% Cut): │
│ <role>Autonomous Senior Software Engineer</role> │
│ <rules> │
│ 1. Ingest line slices via `view_file` before editing. │
│ 2. Mutate files using `replace_file_content` (atomic). │
│ 3. Verify changes with unit tests (100% passing). │
│ 4. Zero conversational preamble. Pure code/diffs. │
│ </rules> │
│ ↳ 95 tokens, 100% crisp deterministic instruction weights │
└─────────────────────────────────────────────────────────────┘
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.
- yesterday Changed · -13 tokens per session 8875abe00098
- 7d ago First seen · 113 lines · 36 tokens per session scan A 94724ebf77ee
compressed-system-prompts is a skill published in the GitHub repository alivirgo/Major-AI-Skills (1 stars, last pushed today), licensed MIT. It adds 23 tokens to every session and 1,237 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 2026-09-05.
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