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Academic Discussion Polisher

Community
GuangyaoYin
academic-discussion-polisher

Translate, polish, draft, restructure, or diagnose academic-paper Discussion sections, with emphasis on evidence-to-mechanism reasoning, alternative explanations, limitations, claim-strength calibration, and journal-ready English. Use for Chinese-to-English or English-to-English Discussion work; do not use for Introductions, Methods, Results, abstracts, or general document formatting unless the user explicitly includes them.

Overview

PublisherGuangyaoYin
Repositoryskills
Skill nameacademic-discussion-polisher
Stars
64
Forks
2
Bundled files
6
Links
  • 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.

  • 6 bundled files

    Scripts, templates, and references the model can read while it works. Files are read-only and never executed.

  • Open source

    Published by GuangyaoYin on GitHub. Read the source before you install it.

Installation

Install the Academic Discussion Polisher AI skill in TypingMind to use it with any LLM, or drop it into another agent that reads SKILL.md.

1

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.

  1. Open the app and go to Plugins → Skills.
  2. Choose "Install from GitHub".
  3. Paste the skill folder URL below and confirm.
    https://github.com/GuangyaoYin/skills/tree/main/skills/academic-discussion-polisher
  4. Enable the skill in any chat where you want it available.
Plugins → Skills → Add skill → From GitHub URL, then paste the folder URL and press Continue.
2

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/GuangyaoYin/skills.git /tmp/skills
mkdir -p .claude/skills
cp -r /tmp/skills/skills/academic-discussion-polisher .claude/skills/academic-discussion-polisher
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Academic Discussion Polisher 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 Academic Discussion Polisher 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 Academic Discussion Polisher 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.

Academic Discussion Polisher

Improve only the Discussion unless the user explicitly expands the scope. Preserve the author's scientific meaning, evidence strength, citations, terminology, numerical values, uncertainty, and causal boundaries. Do not invent results, mechanisms, literature, parameter tests, limitations, novelty, or practical implications.

Choose the mode

  • Diagnose: identify repeated Results, missing reasoning steps, unsupported mechanisms, unaddressed alternatives, vague limitations, and overclaimed implications.
  • Translate: produce idiomatic academic English from Chinese while preserving logical relationships and uncertainty; do not translate word for word.
  • Polish: improve reasoning visibility, paragraph unity, cohesion, concision, syntax, and academic tone without changing substantive meaning.
  • Restructure: reorder or rebuild paragraphs around findings, mechanisms, evidence, alternatives, boundaries, and implications.
  • Draft: write a Discussion from the user's results, figures, literature, model tests, and stated interpretations; flag missing support instead of filling gaps with invented content.

When modes are combined, diagnose the logic first, then restructure, translate, or polish. For short sentence-level edits, preserve the local paragraph's intended function and avoid expanding scope.

Core workflow

  1. Identify the one to three findings that genuinely require interpretation. Separate direct observations or model outputs from mechanism inference and causal attribution.
  2. Map each paragraph to one primary function: key finding, mechanism, literature comparison, alternative explanation, robustness/limitation, theoretical significance, hazard/management implication, or testable future work.
  3. Repair reasoning before wording. Make the path from evidence to interpretation explicit, and ensure every however, therefore, although, and consistent with represents a real logical relation.
  4. Calibrate claim verbs to the support available. Use stronger verbs only for direct and robust evidence; use suggest, may, is consistent with, or likely for inference.
  5. Test each important interpretation against an independent constraint, a plausible alternative, or a stated applicability boundary. If none is supplied, flag the gap.
  6. For models, distinguish robust spatial or temporal patterns from parameter-dependent absolute magnitudes. Do not present model output as direct observation.
  7. For induced/triggered-event attribution, require converging temporal, spatial, mechanical, and independent evidence. Temporal proximity alone does not establish causation.
  8. End at the evidence-supported level of theory, hazard, management, or a specific testable prediction. Avoid generic claims of importance or generic calls for more research.
  9. Check terminology, tense, subject continuity, modifier attachment, parallelism, equation/figure references, citation placement, and consistency of abbreviations.
  10. Return the revised text first unless the user asked only for diagnosis. Add only consequential notes, alternatives, or author-verification items.

Non-negotiable writing rules

  • Do not turn the Discussion into a second Results section. Repeat only the result needed to support the current interpretation.
  • Do not collapse correlation, mechanism support, and causation into one claim.
  • Do not use prove, clearly, obviously, very, or unsupported significantly to manufacture certainty.
  • Use show for directly supported results, indicate or support for converging evidence, and suggest or may reflect for mechanism inference.
  • Treat demonstrate as stronger than show; reserve it for evidence that directly rules in the stated relationship within the tested scope.
  • A limitation should state what is limited, which inference it affects, and whether the main conclusion remains intact.
  • Future work should identify the object, method or observation, and discriminating prediction—not merely say that more studies are needed.
  • Treat “top-journal style” as compression, logical force, evidential precision, and controlled generalization—not ornate vocabulary or exaggerated novelty.
  • Preserve hedging that carries scientific meaning. Remove only empty or repetitive hedging.
  • Preserve citation ownership: do not make the user's study appear to establish a result that belongs to cited work.

References

Read only the references relevant to the request. A short English edit usually needs no supporting reference; a full Chinese Discussion about induced seismicity normally needs the logic, translation, and geoscience references.

Default output

For a full Discussion, provide:

  1. the revised or translated English Discussion;
  2. a concise paragraph-by-paragraph logic map;
  3. a short list of consequential changes and claims, terminology, citations, or causal steps requiring author verification.

For translation-only requests, return the translation first and omit commentary unless the source is ambiguous or scientifically overstrong. For diagnosis-only requests, do not rewrite the full text unless requested; give prioritized problems and representative revisions. When useful, provide one conservative and one stronger-but-still-supported alternative for a pivotal sentence.

Bundled files

The model reads these on demand while the skill is loaded. They are exposed as readable files and are never executed.

Frequently asked questions

What does the Academic Discussion Polisher AI skill do?

Translate, polish, draft, restructure, or diagnose academic-paper Discussion sections, with emphasis on evidence-to-mechanism reasoning, alternative explanations, limitations, claim-strength calibration, and journal-ready English. Use for Chinese-to-English or English-to-English Discussion work; do not use for Introductions, Methods, Results, abstracts, or general document formatting unless the user explicitly includes them.

Why use Academic Discussion Polisher on TypingMind?

Because you install it once and use it with any model. Academic Discussion Polisher 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 Academic Discussion Polisher in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/GuangyaoYin/skills/tree/main/skills/academic-discussion-polisher. TypingMind reads its SKILL.md and bundles its files and installs it as a skill you can enable per chat.

Which AI models can use Academic Discussion Polisher?

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 Academic Discussion Polisher?

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

Is the Academic Discussion Polisher AI skill free?

It is published on GitHub by GuangyaoYin. Check the repository for licensing terms. 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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