MathModeling-skills: Skill for Claude Code

.claude/skills/robustness-checker/SKILL.md

robustness-checker is a skill for Claude Code from zhnnky329/MathModeling-skills. It costs 42 tokens per session (490 once invoked), scanned A, original, MIT.

A process for testing whether an approved mathematical model remains reliable when its inputs, assumptions, data, or settings change.

In plain words
What is it for?
Use it to run risk-focused stability, sensitivity, error, and comparison checks and save the results for review.
Why use it?
It reveals claims that depend too heavily on one choice, random seed, split of the data, or treatment of errors and unusual values.

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 →

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/robustness-checker/SKILL.md
Clone the repo
git clone --depth 1 https://github.com/zhnnky329/MathModeling-skills

Made for: Claude Code.

Wrote 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.

agentmods badge for robustness-checker

README.md
[![agentmods](https://agentmods.dev/badge/skills/zhnnky329/mathmodeling-skills/robustness-checker/github.svg)](https://agentmods.dev/skills/zhnnky329/mathmodeling-skills/robustness-checker)
Your own site
<a href="https://agentmods.dev/skills/zhnnky329/mathmodeling-skills/robustness-checker"><img src="https://agentmods.dev/badge/skills/zhnnky329/mathmodeling-skills/robustness-checker/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.

agentmods 80×15 button for robustness-checker

Your own site · 80×15
<a href="https://agentmods.dev/skills/zhnnky329/mathmodeling-skills/robustness-checker"><img src="https://agentmods.dev/badge/skills/zhnnky329/mathmodeling-skills/robustness-checker.svg" alt="Reviewed on agentmods" width="80" height="20"></a>
Per session 42 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 490 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 $0.00042 $0.00490
Opus 5 $0.00021 $0.00245
Sonnet 5 $0.00008 $0.00098
Haiku 4.5 $0.00004 $0.00049

Measured 12d ago against content hash 42052bcea072, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-11, from the pricing page.

Security

Grade A, and why

robustness-checker 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 12d 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/robustness-checker/SKILL.md · 68 lines

How it starts

The opening of the file, as written. The whole thing — 68 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Purpose

Test the claims most likely to fail. Choose checks from the model's assumptions and decision risks rather than filling a generic checklist.

Preconditions

  • Approved main and usable baseline executed.
  • Run summary, method card, probe summary, and relevant outputs exist.
  • Claim or decision to be tested is known.

Workflow

  1. Identify load-bearing assumptions and claims.
  2. Select applicable checks:
    • parameter or weight perturbation;
    • alternate split or resampling;
    • seed stability;
    • outlier/missing-data treatment;
    • constraint/capacity perturbation;
    • baseline comparison;
    • output concentration/rank stability;
    • error and uncertainty analysis.
  3. State perturbation ranges and why they are meaningful before interpreting results.
  4. Run checks with fixed seeds where stochastic.
  5. Save compact metrics to:

robustness/Qx/qx_robustness_summary.json

  1. In submission, also save:

robustness/Qx/qx_robustness_report.md

  1. If the stability verdict affects method continuation or claim scope, invoke one choice card and log the human answer in qx_decisions.jsonl.

Summary Contract

Record:

  • tested claim/assumption;
  • input and result source paths;
  • perturbation;
  • metric and threshold if predeclared;
  • observed value;
  • status PASS, CONDITIONAL, or FAIL;
  • limitation;
  • fallback-trigger relevance.

Rules

  • Do not run irrelevant checks merely to reach a count.
  • Do not invent a threshold after seeing the result without labeling it exploratory.
  • Do not convert stability metrics into the human confidence verdict.
  • Do not create robustness-checker_modeler_decision.md.
  • A failed robustness check is evidence for adjust/fallback/claim downgrade, not permission for AI to decide.

Verification

  • Every major final claim has a supporting check or explicit limitation.
  • Perturbations are justified and reproducible.
  • Baseline and main comparisons remain metric-compatible.
  • Concentration/degeneracy risks are revisited when relevant.
  • Submission report sources its numbers from the summary and experiment artifacts.

Read the full file on GitHub · 68 lines

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. 12d ago First seen · 68 lines · 42 tokens per session scan A 42052bcea072

Subscribe to this mod's changes

robustness-checker is a skill published in the GitHub repository zhnnky329/MathModeling-skills (882 stars, last pushed 18d ago), licensed MIT. It adds 42 tokens to every session and 490 once invoked, about $0.0002 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 2026-08-30.