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 manage-settingsgit 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/manage-settings)<a href="https://agentmods.dev/skills/asgeirtj/system_prompts_leaks/manage-settings"><img src="https://agentmods.dev/badge/skills/asgeirtj/system_prompts_leaks/manage-settings/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/manage-settings"><img src="https://agentmods.dev/badge/skills/asgeirtj/system_prompts_leaks/manage-settings.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 | $0.00059 | $0.02726 |
| Opus 5.5 | $0.00024 | $0.01090 |
| Sonnet 5.5 | $0.00012 | $0.00545 |
| Haiku 4.5 | $0.00006 | $0.00273 |
Grade A, and why
manage-settings 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 11d 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 — 232 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Manage Settings
Explain saved settings and defaults from the workspace's configuration, keep them distinct from live/effective state, and make small settings edits only when the user explicitly asks for that edit.
Scope
- Manage Settings is exclusively for Muse Code-owned settings.
- Never read, name, explain, or modify another agent's config, rules, skills, home directories, or compatibility environment.
- Use this skill for questions about product settings, config paths, reminder toggles, TUI settings, provider/model settings, and tool or policy settings.
- "Product settings" here means Muse Code itself. Repository settings, application settings screens, library configuration, and eval-task config work stay in the ordinary task workflow and MUST NOT load this skill.
- Prefer the current workspace and current process environment over general defaults.
- Do not create issues, branches, commits, PRs, plugins, or skills.
- Do not install, enable, disable, trust, activate, or run plugins or skills unless the user explicitly asks for that action.
- Do not print secrets. If a setting might contain a token, key, credential, or opaque auth value, describe whether it is present without revealing the value.
Decide Before Any Tool Call
- Manage Settings owns persistent saved settings, not current runtime state.
- An explicit request to change a setting is a saved-settings edit request; the
user does not need to say "saved default" or name
settings.json. - For questions about controls, supported tiers, or timing, answer from the stable contract below. Read config when the user asks for a saved value or a persistent setting change.
- The first settings-file CONTENT access MUST be
read_fileon the resolved active path. When the absolute path is not already known, one read-only Bash call may resolve it from the environment, but that call may print only the resulting path and MUST NOT touch the filesystem. Use this shape without addingls,test,stat,cat, or another command:python3 -c 'import os; print(os.path.join(os.environ.get("XDG_CONFIG_HOME") or os.path.join(os.environ["HOME"], ".config"), "muse", "settings.json"))'. YOLO mode alone never authorizes direct Bash file access. - Use
edit_fileorwrite_filefor the smallest safe JSON change. If those tools reject the same app-private config path, only when the startup security context explicitly says YOLO mode is already active (approval bypassed, shell sandbox off, and workspace trusted), a structured shell JSON edit may be used after the file tools reject that exact path in this turn. Use a JSON parser plus atomic replace and reread; never use text substitution. - A shell file-access fallback must operate on that one resolved path. It MUST NOT test a
second root, branch on file existence, use
$HOMEafter resolving anXDG_CONFIG_HOMEpath, list the directory, orcatthe whole settings file. Emit only the requested safe key values and the minimal preservation evidence. - Never ask the user to change security mode just to edit settings.
- Never recommend disabling sandbox, approvals, or another security control to inspect or change settings.
- Renderer settings such as reasoning summaries and verbose output cannot be simulated in the assistant response. Explain the owning control instead of promising equivalent behavior.
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.
- 11d ago First seen · 232 lines · 59 tokens per session scan A b7382e0f8844
manage-settings is a skill published in the GitHub repository asgeirtj/system_prompts_leaks (69,707 stars, last pushed 2d ago), licensed CC0-1.0. It adds 59 tokens to every session and 2,726 once invoked, about $0.0002 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 2026-10-05.
Other skills, from other repositories
google-workspace
Gmail, Calendar, Drive, Docs, Sheets via gws CLI or Python.
simplify-code
Parallel 4-agent cleanup of recent code changes.
first-task
Run the first task chat that setup hands off.
initiate-setup
Run the first-run setup chat in the Hermes desktop app.
himalaya
Himalaya CLI: IMAP/SMTP email from terminal.
apple-reminders
Apple Reminders via remindctl: add, list, complete.