final-method-explainer

final-method-explainer is a skill for Claude Code from zhnnky329/MathModeling-skills. It costs 37 tokens per session (443 once invoked), scanned A, original, MIT.

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.

In plain words
What is it for?
Use it to document the method’s scope, inputs, outputs, constraints, procedure, baseline, fallback, validation, robustness, and applicable limits.
Why use it?
It brings the approved reasoning, equations, assumptions, implementation, evidence, and limitations into one submission-ready explanation.

Skill for Claude Code

Written for Claude Code: installed under .claude/.

Install

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.

agentmods
npx agentmods add skills/zhnnky329/mathmodeling-skills/final-method-explainer
Any agent
npx skills add zhnnky329/MathModeling-skills --skill final-method-explainer
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 final-method-explainer

README.md
[![agentmods](https://agentmods.dev/badge/skills/zhnnky329/mathmodeling-skills/final-method-explainer.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.svg" alt="Measured on agentmods" 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. Scan, not verified.
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 $0.00037 $0.00443
Opus 5 $0.00018 $0.00221
Sonnet 5 $0.00007 $0.00089
Haiku 4.5 $0.00004 $0.00044

Measured 6d ago against content hash 04fe1af554ac, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-06, 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 6d 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

  1. Resolve the final method and baseline from the latest non-stale human decisions.
  2. Transcribe the human's selection rationale faithfully and cite its decision_id.
  3. 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.
  4. Ensure formulas match code and symbol table.
  5. 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.

  1. 6d 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 (731 stars, last pushed 12d ago), licensed MIT. It adds 37 tokens to every session and 443 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.

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