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 hamzabellouch/agent-skills --skill mathematical-optimizationgit clone --depth 1 https://github.com/hamzabellouch/agent-skillsWrote 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/hamzabellouch/agent-skills/mathematical-optimization)<a href="https://agentmods.dev/skills/hamzabellouch/agent-skills/mathematical-optimization"><img src="https://agentmods.dev/badge/skills/hamzabellouch/agent-skills/mathematical-optimization/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/hamzabellouch/agent-skills/mathematical-optimization"><img src="https://agentmods.dev/badge/skills/hamzabellouch/agent-skills/mathematical-optimization.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 | $0.00029 | $0.00212 |
| Opus 5.5 | $0.00012 | $0.00085 |
| Sonnet 5.5 | $0.00006 | $0.00042 |
| Haiku 4.5 | $0.00003 | $0.00021 |
Grade A, and why
mathematical-optimization 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 7d 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.
What it actually says
Optimization
Domain
Finding extrema of functions.
Core Concepts
- Convexity, duality
- Unconstrained vs. constrained
- Local vs. global optima
- KKT conditions
Key Methods
- Gradient descent, Newton's method
- Lagrange multipliers
- Linear programming (simplex, interior point)
- Dynamic programming
- Stochastic gradient descent
Canonical Examples
- Minimize f(x)=x² → x=0.
- LP: max cᵀx s.t. Ax≤b, x≥0.
- KKT for constrained smooth problems.
Common Pitfalls
- Getting stuck in local minima
- Ignoring constraints' feasibility
- Divergence from bad learning rate
Related Skills
Linear Algebra, Calculus, Machine Learning
What ships with it
1 file 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.
- 7d ago First seen · 38 lines · 29 tokens per session scan A 2e2f91ce19fe
mathematical-optimization is a skill published in the GitHub repository hamzabellouch/agent-skills (8 stars, last pushed today), licensed MIT. It adds 29 tokens to every session and 212 once invoked, about $0.0001 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 2026-10-10.
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