MathModeling-skills is a collection of Claude Code and Codex skills for mathematical modeling competitions, guiding users through data analysis, method-specific checks, reproducible computations, figures, and paper audits without taking over modeling decisions. It is for contestants who want AI to handle mechanical checks while they retain responsibility for choosing methods and interpreting results. The catalogue entries form the project's skills, instructions, hook, setting, and plugin workflow.
Borrowing it
Nothing to install: this file belongs to zhnnky329/MathModeling-skills. Take a copy, put it at the same path in your own repository, and replace the rules that are about this project with yours.
curl -O https://raw.githubusercontent.com/zhnnky329/MathModeling-skills/main/.claude/skills/problem-classifier/SKILL.mdgit clone --depth 1 https://github.com/zhnnky329/MathModeling-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/zhnnky329/mathmodeling-skills/problem-classifier)<a href="https://agentmods.dev/skills/zhnnky329/mathmodeling-skills/problem-classifier"><img src="https://agentmods.dev/badge/skills/zhnnky329/mathmodeling-skills/problem-classifier/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/zhnnky329/mathmodeling-skills/problem-classifier"><img src="https://agentmods.dev/badge/skills/zhnnky329/mathmodeling-skills/problem-classifier.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 | $0.00039 | $0.00521 |
| Opus 5.5 | $0.00016 | $0.00208 |
| Sonnet 5.5 | $0.00008 | $0.00104 |
| Haiku 4.5 | $0.00004 | $0.00052 |
Grade A, and why
problem-classifier 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 2mo 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 — 80 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Preconditions
planning/parse/problem_parse.jsonexists and maps every Qx to an output.- Material framing ambiguities are visible.
Read legacy parse paths only during migration.
Task Types
- evaluation/ranking;
- prediction/estimation;
- optimization/decision;
- mechanism/dynamics;
- classification/clustering;
- graph/routing/network;
- simulation/scenario;
- descriptive/inference;
- mixed.
Detailed cues are in references/task-type-guide.md.
Workflow
- Classify from the required output, decision structure, constraints, and relationships—not keywords alone.
- Assign:
- primary type;
- optional secondary type;
- confidence;
- evidence from the parse;
- consequences for validation and deliverables.
- Identify mixed or ambiguous framings that would change what the team can claim.
- For a load-bearing ambiguity, invoke one choice card explaining consequences. Do not silently settle it.
- Save
planning/classification/problem_classification.json. - Record the human framing decision in
methods/Qx/qx_decisions.jsonl, or inplanning/framing_decisions.jsonlwhen the Qx method directory does not yet exist.
Output Contract
{
"schema_version": 1,
"subquestions": [
{
"id": "Q1",
"primary_type": "evaluation",
"secondary_type": null,
"confidence": "high",
"evidence": [],
"required_validation": [],
"framing_decision_id": null,
"risks": []
}
]
}
Rules
- Do not propose or choose methods.
- Do not classify only from nouns such as “forecast” or “optimal”; verify the required output.
- A subquestion may be mixed, but avoid listing many types without prioritization.
- Human framing is required when alternative classifications lead to materially different outputs or claims.
- Do not create a long taxonomy report when the JSON record is sufficient.
Verification
- Every Qx has one primary type.
- Mixed/secondary types are justified.
- Classification evidence resolves to the parse.
- Ambiguous framing is human-confirmed or remains a blocker.
- No algorithm selection leaked into classification.
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.
- 2mo ago First seen · 80 lines · 39 tokens per session scan A 6de755f37026
problem-classifier is a skill published in the GitHub repository zhnnky329/MathModeling-skills (1,080 stars, last pushed 1mo ago), licensed MIT. It adds 39 tokens to every session and 521 once invoked, about $0.0002 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.
problem-classifier compared with skills from other repositories
| Mod | Type | Stars | Last push | Licence | Scan | Tokens | Works with |
|---|---|---|---|---|---|---|---|
| problem-classifierzhnnky329/MathModeling-skills | Skill | 1.1k | 1mo ago | MIT | A | 39 | Claude Code |
| instrument-data-to-allotropeanthropics/knowledge-work-plugins | Skill | 35k | 2d ago | Apache-2.0 | A | 123 | Claude Code |
| exploratory-data-analysisK-Dense-AI/scientific-agent-skills | Skill | 56k | 4d ago | MIT | A | 83 | Claude Code |
| matlabK-Dense-AI/scientific-agent-skills | Skill | 56k | 4d ago | MIT | A | 44 | Claude Code |
| phylogeneticsK-Dense-AI/scientific-agent-skills | Skill | 56k | 4d ago | MIT | A | 71 | Claude Code, Codex |
| research-engineerdavila7/claude-code-templates | Skill | 33k | yesterday | MIT | A | 43 | Claude Code, Codex |
| mapping-to-snomedmaziyarpanahi/openmed | Skill | 5.8k | yesterday | Apache-2.0 | A | 205 | Claude Code |