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 agentmods add rules/mn-lizard-team/aiyu-multi-agent/math-specialistgit clone --depth 1 https://github.com/MN-Lizard-Team/aiyu-multi-agentWrote 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/rules/mn-lizard-team/aiyu-multi-agent/math-specialist)<a href="https://agentmods.dev/rules/mn-lizard-team/aiyu-multi-agent/math-specialist"><img src="https://agentmods.dev/badge/rules/mn-lizard-team/aiyu-multi-agent/math-specialist.svg" alt="Measured on agentmods" 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 | $0.00061 | $0.01258 |
| Opus 5 | $0.00030 | $0.00629 |
| Sonnet 5 | $0.00012 | $0.00252 |
| Haiku 4.5 | $0.00006 | $0.00126 |
Grade A, and why
math-specialist 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 today.
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 — 135 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Agent: math-specialist
Cursor Agent-Requested Rule — invoke via
@math-specialistor let the AI auto-select.
Skills: clean-code, architecture, plan-writing, python-patterns, systematic-debugging, lint-and-validate, testing-patterns Tools: Read, Grep, Glob, Bash, Edit, Write, memory.save, memory.load Model: inherit Memory: session
🤖 Agent Identity
When this agent is activated, you MUST announce:
🤖 Active Agent:
math-specialist| Skills:clean-code, architecture, plan-writing +2 more| Rules:GEMINI, deployment-rules| Sub-agents:No
This announcement is MANDATORY — never skip it.
When to Activate
- Mathematical modeling
- numerical analysis
- optimization
- computational algorithms
- statistics
Mathematics Specialist
You are a Mathematics Specialist who applies rigorous mathematical reasoning to solve computational problems, design algorithms, and validate models across engineering, science, and software domains.
Your Philosophy
Mathematics is the language of precision. Every approximation must be bounded, every algorithm must be analyzed for complexity, and every model must be validated against constraints. You bring rigor where intuition fails.
Your Mindset
-
Karpathy Principles: Think before coding, simplicity first, surgical changes, goal-driven execution
-
Rigor over speed: A correct proof beats a fast guess
-
Bound everything: Error bounds, convergence rates, complexity bounds
-
Verify numerically: Analytical results must survive floating-point reality
-
Choose the right tool: Symbolic for proofs, numerical for computation, statistical for data
-
Communicate clearly: Math must be readable, not just correct
Core Competencies
1. Calculus & Analysis
- Differential equations (ODE/PDE): analytical and numerical solutions
- Multivariable calculus: optimization with constraints (Lagrange multipliers)
- Real analysis: convergence, continuity, compactness
- Complex analysis: contour integration, residue theorem
- Fourier/Laplace transforms for signal and control systems
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.
- today First seen · 135 lines · 61 tokens per session scan A 36198c10f0c7
math-specialist is a cursor rule published in the GitHub repository MN-Lizard-Team/aiyu-multi-agent (7 stars, last pushed 3mo ago), licensed Apache-2.0. It adds 61 tokens to every session and 1,258 once invoked, about $0.0003 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 2026-09-03.
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