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 qfoldit/Protein-Design-MCP --skill l-systemsgit clone --depth 1 https://github.com/qfoldit/Protein-Design-MCPWrote 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/qfoldit/protein-design-mcp/l-systems)<a href="https://agentmods.dev/skills/qfoldit/protein-design-mcp/l-systems"><img src="https://agentmods.dev/badge/skills/qfoldit/protein-design-mcp/l-systems/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/qfoldit/protein-design-mcp/l-systems"><img src="https://agentmods.dev/badge/skills/qfoldit/protein-design-mcp/l-systems.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 | $0.00135 | $0.00895 |
| Opus 5 | $0.00068 | $0.00447 |
| Sonnet 5 | $0.00027 | $0.00179 |
| Haiku 4.5 | $0.00014 | $0.00089 |
Grade A, and why
qfoldit-l-systems 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 10d 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 — 55 lines — stays where its author put it; the contents beside it link to each section on GitHub.
L-systems (Lindenmayer systems)
What this skill does
Expands an L-system (axiom + substitution rules + iteration count) into a string and renders it as SVG via turtle graphics. Suitable for: classic fractals (Koch curve, dragon curve, Sierpinski triangle), procedural plants/branches, generative graphics for game scenes (e.g. a "virtual lab" / plant generation in a VR demo).
This is a deterministic mathematical algorithm — unlike other qFoldIT modules, there are no empirical assumptions or literature ranges that need to be caveated here. The result is fully predictable given the specified rules.
When to use
- The user asks to generate a fractal (Koch, dragon, Sierpinski triangle, etc.).
- The user asks to generate a procedural plant/bush/branching structure.
- The user gives their own grammar (axiom and substitution rules) and wants to see what it looks like.
- The context is vegetation/fractal generation for a game scene, VR demo, or visualization.
How to work
- If the user wants something standard ("Koch fractal", "tree", "bush", "dragon", "Sierpinski triangle") — use the ready-made preset from
scripts/lsystem.py(--preset koch|dragon|sierpinski|plant|bush), don't reinvent the rules. - If the user provides their own grammar — pass it via
--axiom,--rules(a JSON string like{"F":"F+F-F-F+F"}),--angle,--iterations. - Run the script; it saves an SVG file and prints metadata (expanded string length, number of segments).
- If the string comes out very long (>~50,000 characters) at the given iteration count — warn the user that rendering may be slow/heavy, and suggest reducing the iteration count.
- Open the resulting SVG (via
view) to confirm it isn't empty or doesn't look like a single point (a typical bug — wrong turtle argument order, or draw_chars not matching the rules' alphabet). - Show the result to the user — as an artifact (SVG renders directly in the interface) or as a file, depending on the conversation context.
Example call
What ships with it
4 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.
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.
- 10d ago First seen · 55 lines · 135 tokens per session scan A 47d354106b7a
qfoldit-l-systems is a skill published in the GitHub repository qfoldit/Protein-Design-MCP (1 stars, last pushed 13d ago), licensed Apache-2.0. It adds 135 tokens to every session and 895 once invoked, about $0.0007 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 2026-08-31.
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