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 Orkas-AI/Orkas-Awesome-AgentSkills --skill math-tutorgit clone --depth 1 https://github.com/Orkas-AI/Orkas-Awesome-AgentSkillsWrote 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/orkas-ai/orkas-awesome-agentskills/math-tutor)<a href="https://agentmods.dev/skills/orkas-ai/orkas-awesome-agentskills/math-tutor"><img src="https://agentmods.dev/badge/skills/orkas-ai/orkas-awesome-agentskills/math-tutor/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/orkas-ai/orkas-awesome-agentskills/math-tutor"><img src="https://agentmods.dev/badge/skills/orkas-ai/orkas-awesome-agentskills/math-tutor.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 | $0.00003 | $0.01274 |
| Opus 5.5 | $0.00001 | $0.00510 |
| Sonnet 5.5 | $0.00001 | $0.00255 |
| Haiku 4.5 | $0.00000 | $0.00127 |
Grade A, and why
math-tutor 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 1mo 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 — 154 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Math Tutor
When To Use
- The user asks for K12 math explanation, concept clarification, worked examples, or step-by-step tutoring within a grade/curriculum boundary.
- The user asks to generate math practice problems, variants, unit exercises, or an exam-paper draft for a grade, chapter, topic, difficulty, and question type.
- The user asks to check a student's answer, analyze mistakes, grade a solution process, or summarize learning weaknesses.
- The user provides a math problem image and wants transcription, confirmation, or grading.
Do not use for open-ended mathematical modeling, Python/local expression calculation, Wolfram-style symbolic computation, university-level research math, or generic homework tutoring outside math. Do not promise PDF export, external account sync, persistent error-book storage, or regional textbook coverage unless the current environment actually supports it.
How To Call
- Identify the mode:
concept_explanation,guided_solution,question_generation,answer_check,error_analysis,exam_draft,learning_report, orimage_problem. - Determine grade/stage and topic. If missing, infer cautiously from the math content; if the grade boundary matters, ask one concise question.
- Check curriculum boundaries with
references/curriculum-boundaries.md. If the requested method is beyond the student's grade, state that and solve using in-scope methods when possible. - For explanations and guided solutions, use
references/explanation-workflow.md. - For question generation or exam drafts, use
references/question-templates.mdand verify every generated answer before showing it. - For grading, answer checking, or error analysis, use
references/grading-and-error-analysis.md. Always solve independently first, then compare with the student's work. - For images, use
references/attachment-policy.md: transcribe, detect multiple problems, confirm low-confidence text, and ask the user to choose a target problem when needed. - For learning reports, use
references/report-templates.md. Use only available data; if data is insufficient, say so. - Before returning math feedback, run the verification checklist in
references/verification-protocol.md.
What ships with it
7 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.
- 1mo ago First seen · 154 lines · 3 tokens per session scan A 1a66ad8a946b
math-tutor is a skill published in the GitHub repository Orkas-AI/Orkas-Awesome-AgentSkills (13 stars, last pushed 3mo ago), licensed MIT. It adds 3 tokens to every session and 1,274 once invoked, about $0.0000 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 2026-08-30.
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