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 simplifygit 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/simplify)<a href="https://agentmods.dev/skills/asgeirtj/system_prompts_leaks/simplify"><img src="https://agentmods.dev/badge/skills/asgeirtj/system_prompts_leaks/simplify/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/simplify"><img src="https://agentmods.dev/badge/skills/asgeirtj/system_prompts_leaks/simplify.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 | $0.00042 | $0.00656 |
| Opus 5 | $0.00021 | $0.00328 |
| Sonnet 5 | $0.00008 | $0.00131 |
| Haiku 4.5 | $0.00004 | $0.00066 |
Grade A, and why
simplify 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 9d 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.
Copies of this mod
1 near-identical copy found in the catalogue:
- at-simplify — 89% identical, 25 lines differ
How it starts
The opening of the file, as written. The whole thing — 67 lines — stays where its author put it; the contents beside it link to each section on GitHub.
/simplify → 4 cleanup agents in parallel → apply the fixes
You are improving the quality of the changed code, not hunting for bugs. Review
it for reuse, simplification, efficiency, and altitude issues, then fix what you
find. Do not look for correctness bugs — that is what /code-review is for.
Phase 0 — Gather the diff
Run git diff @{upstream}...HEAD (or git diff main...HEAD / git diff HEAD~1
if there's no upstream) to get the unified diff under review. If there are
uncommitted changes, or the range diff is empty, also run git diff HEAD and
include the working-tree changes in scope — the review often runs before the
commit. If a PR number, branch name, or file path was passed as an argument,
review that target instead. Treat this diff as the review scope.
Phase 1 — Review (4 cleanup agents in parallel)
Launch 4 independent review agents via the Agent tool, all in a
single message so they run concurrently. Pass each agent the diff and one of
the four angles below. Each returns its findings with file, line, a
one-line summary, and the concrete cost (what is duplicated, wasted, or
harder to maintain).
Reuse
Flag new code that re-implements something the codebase already has — Grep shared/utility modules and files adjacent to the change, and name the existing helper to call instead.
Simplification
Flag unnecessary complexity the diff adds: redundant or derivable state, copy-paste with slight variation, deep nesting, dead code left behind. Name the simpler form that does the same job.
Efficiency
Flag wasted work the diff introduces: redundant computation or repeated I/O, independent operations run sequentially, blocking work added to startup or hot paths. Also flag long-lived objects built from closures or captured environments — they keep the entire enclosing scope alive for the object's lifetime (a memory leak when that scope holds large values); prefer a class/struct that copies only the fields it needs. Name the cheaper alternative.
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.
- 9d ago First seen · 67 lines · 42 tokens per session scan A 2e4628a62193
simplify is a skill published in the GitHub repository asgeirtj/system_prompts_leaks (64,511 stars, last pushed today), licensed CC0-1.0. It adds 42 tokens to every session and 656 once invoked, about $0.0002 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
simplify-code
Parallel 4-agent cleanup of recent code changes.
requesting-code-review
Pre-commit review: security scan, quality gates, auto-fix.
opencode
Delegate coding to OpenCode CLI (features, PR review).
github
GitHub via gh CLI: PRs, issues, reviews, repos, auth.
gitnexus-explorer
Serve an interactive codebase knowledge graph web UI.
ha-code-review
Hope-native review of uncommitted, staged, commit, branch, or PR changes: discover concrete regressions, independently verify candidates, and report actionable findings first without speculative noise.