Academic Reviser

Community

joshua-zyy

academic-reviser

Self-review, audit, or verify CS/AI/ML paper drafts as a critical peer reviewer. Three-round review (evidence→argument→style) with Verification Status and debt tracking. Use when: reviewing a paper draft before submission, checking evidence compliance of claims, simulating peer reviewer feedback, verifying citation closure and evidence debts, performing cross-section consistency checks. Triggers on: self review, 自查, verification, 审稿, evidence compliance, peer review, 论文审查, draft audit, 验证论文, 检查引用, cross-section review, 审修, draft verification.

Overview

Publisher	joshua-zyy
Repository	`academic-paper-writer`
Skill name	`academic-reviser`
Stars	115
Forks	1
Bundled files	14
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.
14 bundled files
Scripts, templates, and references the model can read while it works. Files are read-only and never executed.
Open source
Published by joshua-zyy on GitHub. Read the source before you install it.

Installation

Install the Academic Reviser 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/joshua-zyy/academic-paper-writer/tree/main/skills/academic-reviser
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.

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/joshua-zyy/academic-paper-writer.git /tmp/academic-paper-writer
mkdir -p .claude/skills
cp -r /tmp/academic-paper-writer/skills/academic-reviser .claude/skills/academic-reviser

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

Use it in TypingMind

Enable Academic Reviser 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 Reviser 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 Reviser 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 Reviser

将此 skill 视为"挑剔审稿人代理"——像 peer reviewer 一样审查草稿，按证据→论证→风格三轮顺序执行。

Router Protocol

Read manifest.yaml. It declares always_load files, axes, and references.on_demand.
Read every file listed under always_load. These are the skill's binding rules — not reference material.
Apply the loaded material as constraints:
- stance.md defines non-negotiable rules, bounded assessment, termination conditions, and scope.
- red-lines.md defines absolute prohibitions. Do not negotiate these.
- output-contract.md defines deliverables, debt types, and Verification Status format.
- anti-patterns.md defines known failure modes, correct alternatives, and self-deception signals.
Detect the mode using the manifest's mode axis. When input materials are incomplete, declare a Bounded Assessment before proceeding.
Echo the selected mode to the user before executing.
Reach for references/ only when the manifest's references.on_demand condition is satisfied.

Debt types tracked: prose_debt, section_contract_debt, citation_debt, evidence_debt, figure_debt, protocol_debt, result_debt, rationale_debt. Schema: skills/shared/schemas/verification-report.md.

Modes

Mode	Use when
`full-section-review`	Complete 3-round review + Verification for a single section
`cross-section-review`	Cross-section consistency check
`verification-only`	Verdict only, no re-review
`targeted-review`	Specific issue (e.g. citation closure only)
`targeted-evidence-mode`	Evidence compliance only (orchestrator Step 9.5)
`mock-reviewer-package`	Optional pre-submission 3-reviewer package

Agent Dispatch

agents/reviser_agent.md dispatched by orchestrator at Step 9.5 or Step 9.8. Subagent returns structured review content; must not modify project files or invent reviewer identities, experiments, citations, or unprovided evidence.

Independent Use

Input	Mode	Priority	Behavior
Section draft	full-section-review	2 (path trigger)	Full 3-round review
Multiple sections	cross-section-review	2 (path trigger)	Consistency only
"只用 verdict"	verification-only	1 (explicit)	Verdict only
Specific issue	targeted-review	1 (explicit)	Targeted check
Evidence focus	targeted-evidence-mode	1 (explicit)	Evidence compliance
"审稿包" / pre-submission	mock-reviewer-package	1 (explicit)	Optional reviewer package

Scenario	Recommended
Just reviewing a draft	This skill (standalone)
During paper drafting	academic-paper-writer orchestrator
After polishing pass	academic-polishing → this skill

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 Reviser AI skill do?

Why use Academic Reviser on TypingMind?

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

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/joshua-zyy/academic-paper-writer/tree/main/skills/academic-reviser. 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 Reviser?

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 Reviser?

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

Is the Academic Reviser AI skill free?

Yes. It is published on GitHub by joshua-zyy 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

Academic Reviser

Router Protocol

Modes

Agent Dispatch

Independent Use

Bundled files

Frequently asked questions

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