MathModeling-skills: Skill for Claude Code

.claude/skills/model-assumptions-builder/SKILL.md

model-assumptions-builder is a skill for Claude Code from zhnnky329/MathModeling-skills. It costs 44 tokens per session (400 once invoked), scanned A, original, MIT.

A documentation tool that extracts mathematical assumptions from the problem, chosen methods, data description, and risk checks.

In plain words
What is it for?
Use it to track each assumption’s source, purpose, scope, validation evidence, impact if violated, and possible fallback across subquestions.
Why use it?
It makes assumptions and their possible effects visible without silently deciding whether each one is necessary or merely simplifying.

Skill for Claude Code

Written for Claude Code: installed under .claude/.

This is zhnnky329/MathModeling-skills's own configuration. It tells Claude Code how to work on MathModeling-skills itself, so it is not a mod to install elsewhere. Copy it as a starting point and replace the rules that are about this project. Everything MathModeling-skills configures →

About the project

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.

zhnnky329/MathModeling-skills · 1,080 stars · on GitHub

Reuse

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.

Copy the file
curl -O https://raw.githubusercontent.com/zhnnky329/MathModeling-skills/main/.claude/skills/model-assumptions-builder/SKILL.md
Clone the repo
git clone --depth 1 https://github.com/zhnnky329/MathModeling-skills

Made for: Claude Code.

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README.md
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Per session 44 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 400 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. A grade says what 26 rules found in the file — not that it is safe. Third-party audits
  • NVIDIA SkillSpector pass 7 Sept 2026
How audits are shown
Origin original No closer match found in the catalogue.
Token cost

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.

ModelPer sessionOnce invoked
Fable 5.1 $0.00044 $0.00400
Opus 5.5 $0.00018 $0.00160
Sonnet 5.5 $0.00009 $0.00080
Haiku 4.5 $0.00004 $0.00040

Measured 2mo ago against content hash 59ca7b43eef3, method: parsed. Prices are Anthropic first-party input rates as of 2026-10-07, from the pricing page.

Security

Grade A, and why

model-assumptions-builder 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.

.claude/skills/model-assumptions-builder/SKILL.md · 56 lines

What it actually says

Inputs

  • problem parse;
  • active method cards;
  • data profile and risk-probe summaries;
  • question dependency map;
  • existing assumptions and human decisions.

Read legacy candidate pools only during migration.

Workflow

  1. Extract explicit problem assumptions and method-induced assumptions.
  2. Remove filler statements that do not affect model validity or interpretation.
  3. For each assumption record:
    • scope and source;
    • modeling need;
    • applicable method/Qx;
    • validation evidence;
    • mitigation or fallback link.
  4. Identify conflicts across Qx.
  5. Present unresolved necessity/impact trade-offs in one compact choice card where possible.
  6. Log human assumption_necessity decisions in qx_decisions.jsonl.
  7. Save planning/model_assumptions.md, transcribing settled human labels and impacts with decision IDs.

Assumption Fields

  • ID;
  • statement;
  • scope;
  • source and modeling need;
  • human-confirmed type: necessary or simplifying;
  • validation method/evidence;
  • impact if violated;
  • mitigation/fallback;
  • decision ID.

Rules

  • Do not invent generic assumptions such as “data are accurate” unless they affect a real dependency.
  • Do not finalize necessary/simplifying or impact judgments for the human.
  • Do not leave many repeated sentinels in the final file; collect missing judgments through a choice card and stop finalization until answered.
  • Revisit an assumption only when its method, evidence, or downstream use materially changes.

Verification

  • Every assumption has a modeling need and source.
  • Human-owned labels trace to decisions.
  • Probe/robustness evidence addresses load-bearing assumptions.
  • Cross-Qx conflicts are resolved or explicit.
Changes

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.

  1. 2mo ago First seen · 56 lines · 44 tokens per session scan A 59ca7b43eef3

Subscribe to this mod's changes

model-assumptions-builder is a skill published in the GitHub repository zhnnky329/MathModeling-skills (1,080 stars, last pushed 1mo ago), licensed MIT. It adds 44 tokens to every session and 400 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.

Related

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model-assumptions-builder next to 6 skills from other repositories
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