Final Method Explainer

CommunityPopular

zhnnky329

final-method-explainer

Build the authoritative final method explanation for a submission-ready subquestion from the method card, human decision ledger, code plan, final results, and robustness evidence.

Overview

Publisher	zhnnky329
Repository	`MathModeling-skills`
Skill name	`final-method-explainer`
Stars	1.1K
Forks	42
Bundled files	Instructions only
License	MIT
Links	Skill source Repository

Markdown instructions
A SKILL.md file the model loads on demand, so it only costs tokens when a request actually matches.
Works with any LLM
AI skills are plain Markdown, not provider-specific code, so this works with GPT, Claude, Gemini, Grok, or a local model.
Self-contained
Everything the model needs lives in the instructions — no extra files to sync.
Open source
Published by zhnnky329 on GitHub. Read the source before you install it.

Installation

Install the Final Method Explainer AI skill in TypingMind to use it with any LLM, or drop it into another agent that reads SKILL.md.

Install in TypingMind

TypingMind installs a skill straight from its GitHub folder — it reads SKILL.md, bundles the resource files, and stores the result locally.

Open the app and go to Plugins → Skills.
Choose "Install from GitHub".
Paste the skill folder URL below and confirm.
https://github.com/zhnnky329/MathModeling-skills/tree/main/.claude/skills/final-method-explainer
Enable the skill in any chat where you want it available.

Store

Installed

Skills

Add skills

Import one or more skills from a public GitHub folder or a local .skill or .zip archive, or SKILL.md file.

From GitHub URLFrom .skill, .zip, or SKILL.md

GitHub repo or folder

https://github.com/zhnnky329/MathModeling-skills/tree/main/.claude/skills/final-method-explainer

Points to a single skill folder, or any folder that contains multiple skills. Public repos only.

CancelContinue

Plugins → Skills → Add skill → From GitHub URL, then paste the folder URL and press Continue.

Install in another agent

Any agent that reads the Agent Skills format can use this skill — copy the folder into that agent's skills directory.

Claude Code — .claude/skills

git clone --depth 1 https://github.com/zhnnky329/MathModeling-skills.git /tmp/MathModeling-skills
mkdir -p .claude/skills
cp -r /tmp/MathModeling-skills/.claude/skills/final-method-explainer .claude/skills/final-method-explainer

Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Final Method Explainer in any TypingMind chat and the model takes it from there. Its name and description sit in the system prompt, and the moment a request matches, the model loads the full instructions itself — you never invoke it by hand, and it costs no tokens until it is actually used.

The model loads Final Method Explainer on its own as soon as a request matches it.

Works with any AI model

AI skills are plain Markdown instructions rather than provider-specific code, so Final Method Explainer is not tied to the model it was written for. Install it once in TypingMind and use it with GPT-5, Claude, Gemini, Grok, DeepSeek, Mistral, Llama, or a local model you run yourself — all on your own API keys.

Loaded only when it is needed
The system prompt carries just the name and description. The instructions are fetched on the first matching request, so an idle skill costs nothing.
Switch models mid-chat
Because the skill is instructions rather than code, changing model does not break it — the next model reads the same SKILL.md.

Skill instructions

This is the SKILL.md content the model loads. Read it before installing — a skill is instructions your model will follow.

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.

Frequently asked questions

What does the Final Method Explainer AI skill do?

Build the authoritative final method explanation for a submission-ready subquestion from the method card, human decision ledger, code plan, final results, and robustness evidence.

Why use Final Method Explainer on TypingMind?

Because you install it once and use it with any model. Final Method Explainer is plain Markdown rather than provider-specific code, so the same skill runs on GPT-5, Claude, Gemini, Grok, or a local model — and you can switch model mid-chat without it breaking. TypingMind runs on your own API keys, so you pay providers directly instead of a per-seat subscription, and your skills and chats stay in your own storage.

How do I install Final Method Explainer in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/zhnnky329/MathModeling-skills/tree/main/.claude/skills/final-method-explainer. TypingMind reads its SKILL.md and installs it as a skill you can enable per chat.

Which AI models can use Final Method Explainer?

Any model you connect in TypingMind. AI skills are plain Markdown instructions rather than provider-specific code, so GPT, Claude, Gemini, Grok, and local models can all load this skill when a request matches it.

How many AI models can I use with Final Method Explainer?

As many as you like. As long as a model supports skills, you can use Final Method Explainer with it — GPT, Claude, Gemini, Grok, DeepSeek, Mistral, Llama and more — all on TypingMind with your own API keys.

Is the Final Method Explainer AI skill free?

Yes. It is published on GitHub by zhnnky329 under the MIT license. You only pay your own AI provider for the tokens you use.

What are AI skills?

An AI skill is a reusable instruction bundle that teaches an AI model how to do one specific task. It follows the open Agent Skills format: a SKILL.md file with a name and description, plus any scripts, templates or reference files the model may need. The model reads the instructions only when your request matches the skill, so an installed skill costs nothing until it is used.

How are AI skills different from plugins or MCP servers?

A plugin or MCP server gives a model new tools to call — code that runs somewhere and returns a result. An AI skill gives the model knowledge and process instead: how to approach a task, which steps to follow, what good output looks like. Skills are plain Markdown, so they need no server, no API key and no runtime, and they work with any model.

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Overview

Installation

Install in TypingMind

Install in another agent

Use it in TypingMind

Works with any AI model

Skill instructions

Purpose

Preconditions

Sources

Workflow

Rules

Verification

Frequently asked questions

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