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 datavizgit 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/dataviz)<a href="https://agentmods.dev/skills/asgeirtj/system_prompts_leaks/dataviz"><img src="https://agentmods.dev/badge/skills/asgeirtj/system_prompts_leaks/dataviz/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/dataviz"><img src="https://agentmods.dev/badge/skills/asgeirtj/system_prompts_leaks/dataviz.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- 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 | $0.00232 | $0.01974 |
| Opus 5 | $0.00116 | $0.00987 |
| Sonnet 5 | $0.00046 | $0.00395 |
| Haiku 4.5 | $0.00023 | $0.00197 |
Grade A, and why
Data Visualization 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.
Copies of this mod
1 near-identical copy found in the catalogue:
- dataviz — 86% identical, 88 lines differ
How it starts
The opening of the file, as written. The whole thing — 129 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Data Visualization
A chart is read by people and executed by you. This skill turns "make it look good" into a procedure with checks, so the result is right by construction rather than by taste.
The method here is design-system-agnostic. Nothing in the procedure, the form
heuristic, the six checks, or the mark specs is specific to one product. A design
system supplies a small set of parameters (its ramps, a categorical order, a
diverging pair, a status palette, a texture, its surfaces, its filter components);
the method consumes them unchanged. A validated default palette is the
reference instance, fully specified in references/palette.md. To target your
brand, read that file's structure and substitute its values - touch nothing else.
The single most important habit: the color part is computable, so compute it. Never eyeball whether a palette is colorblind-safe - run
scripts/validate_palette.js.
The procedure - do these in order
Color comes LAST. Most bad charts pick colors first.
- Pick the form. What is the data's job - magnitude, identity, polarity, a
single headline, change-over-time? The job picks the chart type, and sometimes
the answer is not a chart (a stat tile or hero number). ->
references/choosing-a-form.md - Assign color by the job it does. Categorical (identity), sequential
(magnitude), diverging (polarity), or status (state) - each has one rule.
Assign categorical hues in fixed order, never cycled. ->
references/color-formula.md - VALIDATE the palette - run the script, don't reason about Delta E.
node scripts/validate_palette.js "<hex,hex,...>" --mode light(relative to this skill's base directory - or load it as<script type="module">in the chart's own page, where it readsdata-paletteoff<body>and logs aconsole.tablereport). It returns pass/fail on the lightness band, chroma floor, adjacent-pair CVD separation, the normal-vision floor, and contrast. Fix anything that FAILs before continuing. Re-run for--mode darkwith that mode's surface. - Apply mark specs & spacers. Thin marks, 4px rounded data-ends anchored to
the baseline, 2px lines, >=8px markers, a 2px surface gap between fills (stacked
segments and adjacent bars alike) and a 2px surface ring on overlapping marks,
selective direct labels. ->
references/marks-and-anatomy.md - Add the hover layer - by default. An HTML/SVG chart is interactive; ship
a crosshair+tooltip on line/area and a per-mark hover tooltip on bar/dot/cell.
The only form that skips it is a bare stat tile with no plot. Hit targets bigger
than the mark; filters in one row above the charts. ->
references/interaction.md - Final accessibility pass. For >= 2 series a legend is always present and <= 4 are also direct-labeled (a single series needs no legend box - the title names it), so identity is never color-alone; a table view exists; dark mode is selected - its own steps from the same ramps, validated against the dark surface, not an automatic flip; texture is available for the CVD/print/forced-colors case.
- Render it and look at it. The validator checks color, not layout - open or screenshot the output and eyeball it for label collisions, geometry, and overflow before calling it done.
What ships with it
9 files 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.
- references/anti-patterns.md 6.0 KB
- references/choosing-a-form.md 3.0 KB
- references/color-formula.md 8.0 KB
- references/components.md 2.1 KB
- references/interaction.md 3.7 KB
- references/marks-and-anatomy.md 5.9 KB
- references/palette.md 8.8 KB
- scripts/validate_palette.js 18 KB runs code
- scripts/validate_palette.py 15 KB runs code
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 · 129 lines · 232 tokens per session scan A 7c0d30f047fa
Data Visualization is a skill published in the GitHub repository asgeirtj/system_prompts_leaks (64,614 stars, last pushed yesterday), licensed CC0-1.0. It adds 232 tokens to every session and 1,974 once invoked, about $0.0012 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
claude-design
Design one-off HTML artifacts (landing, deck, prototype).
tldraw-offline
Drive and script tldraw offline canvases with an agent.
baoyu-infographic
An infographic generator that turns supplied content into a visual summary using different information layouts and visual styles. It supports standard and custom image proportions and multiple languages.
sketch
Throwaway HTML mockups: 2-3 design variants to compare.
adversarial-ux-test
Roleplay a hostile user to find and triage UX pain points.
design-md
Author/validate/export Google's DESIGN.md token spec files.