What is final-method-explainer?

A method-writing tool that creates the final explanation of a selected mathematical method for one subquestion, using the recorded decision, code plan, results, and robustness checks.

Use it to document the method’s scope, inputs, outputs, constraints, procedure, baseline, fallback, validation, robustness, and applicable limits.

It brings the approved reasoning, equations, assumptions, implementation, evidence, and limitations into one submission-ready explanation.

How zhnnky329/MathModeling-skills configures Claude Code

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/final-method-explainer/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.

README.md

[![agentmods](https://agentmods.dev/badge/skills/zhnnky329/mathmodeling-skills/final-method-explainer/github.svg)](https://agentmods.dev/skills/zhnnky329/mathmodeling-skills/final-method-explainer)

Your own site

<a href="https://agentmods.dev/skills/zhnnky329/mathmodeling-skills/final-method-explainer"><img src="https://agentmods.dev/badge/skills/zhnnky329/mathmodeling-skills/final-method-explainer/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.

Your own site · 80×15

<a href="https://agentmods.dev/skills/zhnnky329/mathmodeling-skills/final-method-explainer"><img src="https://agentmods.dev/badge/skills/zhnnky329/mathmodeling-skills/final-method-explainer.svg" alt="Reviewed on agentmods" width="80" height="20"></a>

Per session 37 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.

When invoked 443 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.

Model	Per session	Once invoked
Fable 5.1	$0.00037	$0.00443
Opus 5.5	$0.00015	$0.00177
Sonnet 5.5	$0.00007	$0.00089
Haiku 4.5	$0.00004	$0.00044

Measured 2mo ago against content hash 04fe1af554ac, method: parsed. Prices are Anthropic first-party input rates as of 2026-10-07, from the pricing page.

Security

Grade A, and why

final-method-explainer 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/final-method-explainer/SKILL.md · 62 lines

What it actually says

Purpose

Explain the selected method completely without re-authoring why the human chose it.

Preconditions

rigor_profile is submission or writer handoff is explicitly requested.
Human method choice and result verdicts are recorded in qx_decisions.jsonl.
Approved code ran and final result/robustness evidence exists.

Sources

Use:

qx_method_card.md
qx_decisions.jsonl
planning/model_assumptions.md
planning/symbol_table.md
qx_code_plan.md
final run summary and result analysis
robustness summary/report

Read legacy candidate and iteration logs only for migration.

Workflow

Resolve the final method and baseline from the latest non-stale human decisions.
Transcribe the human's selection rationale faithfully and cite its decision_id.
Explain:
- goal and scope;
- assumptions, including human-confirmed necessity labels;
- symbols and units;
- mathematical formulation;
- inputs, outputs, objective/criteria, and constraints;
- solution procedure;
- baseline and why it is valid;
- fallback trigger and whether it fired;
- validation, robustness, limitations, and applicable range.
Ensure formulas match code and symbol table.
Save methods/Qx/qx_final_method_explanation.md.

Rules

Do not infer the chosen method from best metrics.
Do not invent the why-this-method narrative.
Do not create a new pending decision artifact.
Do not restate a long iteration diary; include only material eliminated alternatives and evidence.
Do not include unsupported numerical claims.

Verification

Final method and rationale trace to decision IDs.
Assumptions, symbols, formulas, units, and code agree.
Baseline is usable rather than merely diagnostic.
Risks, fallback behavior, and limitations are explicit.
The explanation is self-contained enough for the writer.

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.

2mo ago First seen · 62 lines · 37 tokens per session scan A 04fe1af554ac

Subscribe to this mod's changes

final-method-explainer is a skill published in the GitHub repository zhnnky329/MathModeling-skills (1,080 stars, last pushed 1mo ago), licensed MIT. It adds 37 tokens to every session and 443 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 2026-08-30.

Scientific Writing and docs

final-method-explainer next to 6 skills from other repositories
Mod	Type	Stars	Last push	Licence	Scan	Tokens	Works with
final-method-explainerzhnnky329/MathModeling-skills	Skill	1.1k	1mo ago	MIT	A	37	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

MathModeling-skills: Skill for Claude Code