System Prompts Leaks is a collection of captured system instructions used to guide AI chatbots and coding agents before they receive user messages. It serves researchers and developers studying how different AI assistants are directed.
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 asgeirtj/system_prompts_leaks --skill initgit clone --depth 1 https://github.com/asgeirtj/system_prompts_leaksWrote 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/asgeirtj/system_prompts_leaks/init)<a href="https://agentmods.dev/skills/asgeirtj/system_prompts_leaks/init"><img src="https://agentmods.dev/badge/skills/asgeirtj/system_prompts_leaks/init/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/asgeirtj/system_prompts_leaks/init"><img src="https://agentmods.dev/badge/skills/asgeirtj/system_prompts_leaks/init.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- Snyk pass
- NVIDIA SkillSpector pass
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 | $0.00014 | $0.00532 |
| Opus 5.5 | $0.00006 | $0.00213 |
| Sonnet 5.5 | $0.00003 | $0.00106 |
| Haiku 4.5 | $0.00001 | $0.00053 |
Grade B, and why
init scanned grade B with 1 finding 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.
Reads agent configuration directoriesmediumAgent snooping
.claude/, .codex/, .gemini/ hold keys, settings and other credentials a mod has no legitimate need for.
- If you find an OpenAI Codex config (~/.codex/config.toml or ./.codex/) or a Gemini CLI config (~/.gemini/settings.json or ./.gemini/ or a GEMINI.md), offer to import it now — tell the user to reply `/import` to scan an What it actually says
Please analyze this codebase and create a CLAUDE.md file, which will be given to future instances of Claude Code to operate in this repository.
What to add:
- Commands that will be commonly used, such as how to build, lint, and run tests. Include the necessary commands to develop in this codebase, such as how to run a single test.
- High-level code architecture and structure so that future instances can be productive more quickly. Focus on the "big picture" architecture that requires reading multiple files to understand.
Usage notes:
- If there's already a CLAUDE.md, suggest improvements to it.
- When you make the initial CLAUDE.md, do not repeat yourself and do not include obvious instructions like "Provide helpful error messages to users", "Write unit tests for all new utilities", "Never include sensitive information (API keys, tokens) in code or commits".
- Avoid listing every component or file structure that can be easily discovered.
- Don't include generic development practices.
- If there are Cursor rules (in .cursor/rules/ or .cursorrules) or Copilot rules (in .github/copilot-instructions.md), make sure to include the important parts.
- If there is a README.md, make sure to include the important parts.
- If you find an OpenAI Codex config (
/.codex/config.toml or ./.codex/) or a Gemini CLI config (/.gemini/settings.json or ./.gemini/ or a GEMINI.md), offer to import it now — tell the user to reply/importto scan and list what's importable (MCP servers, slash commands, subagents, skills, instructions), then/import --yes=<digest>(the scan output names the digest) to apply the user-level items. Do NOT read the foreign-agent config files or write Claude Code config yourself — the deterministic import (triggered by--yes) applies the same safe-name and path-traversal guards as the terminal picker. If/importisn't available on this surface, tell the user to runclaude importfrom a terminal instead. - Do not make up information such as "Common Development Tasks", "Tips for Development", "Support and Documentation" unless this is expressly included in other files that you read.
- Be sure to prefix the file with the following text:
# CLAUDE.md
This file provides guidance to Claude Code (claude.ai/code) when working with code in this repository.
What ships with it
1 file 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 Changed · +2 lines scan A → B bceba8aa1c1f
- 1mo ago First seen · 26 lines · 14 tokens per session scan A c61adc5b55cf
init is a skill published in the GitHub repository asgeirtj/system_prompts_leaks (70,162 stars, last pushed yesterday), licensed CC0-1.0. It adds 14 tokens to every session and 532 once invoked, about $0.0001 per session on Opus 5.5. A static security scan graded it B with 1 finding (reads agent configuration directories). No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-30.
Other skills, from other repositories
comps-analysis
Build comparable-company valuation workbooks in Excel.
anatomy
Explain an idea as an interactive isometric machine figure.
pretext
Build creative browser demos with DOM-free text layout.
weights-and-biases
W&B: log ML experiments, sweeps, model registry, dashboards.
nemo-curator
Curate LLM training data: dedupe, filter, PII redaction.
subagent-driven-development
Execute plans via delegatetask subagents (2-stage review).