Proposal Final Review

Organization

Optima-CityU

proposal-final-review

Use when assembling a completed staged Typst proposal and checking its evidence, logic, citations, structure, and export readiness.

Overview

Publisher	Optima-CityU
Repository	`LLM4AD_Next`
Skill name	`proposal-final-review`
Stars	596
Forks	41
Bundled files	1
License	BSD-3-Clause
Links	Skill source Repository Homepage

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.
1 bundled files
Scripts, templates, and references the model can read while it works. Files are read-only and never executed.
Open source
Published by Optima-CityU on GitHub. Read the source before you install it.

Installation

Install the Proposal Final Review 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/Optima-CityU/LLM4AD_Next/tree/main/skills/openair-proposal/proposal-final-review
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/Optima-CityU/LLM4AD_Next/tree/main/skills/openair-proposal/proposal-final-review

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/Optima-CityU/LLM4AD_Next.git /tmp/LLM4AD_Next
mkdir -p .claude/skills
cp -r /tmp/LLM4AD_Next/skills/openair-proposal/proposal-final-review .claude/skills/proposal-final-review

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

Use it in TypingMind

Enable Proposal Final Review 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 Proposal Final Review 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 Proposal Final Review 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.

Proposal Assembly and Final Review

Use this skill only for the final proposal stage. Edit only the proposal entry document specified in the task prompt.

Read the method reference completely before acting: references/full-proposal-review.md.

You may read any project source file for context. You may modify only the entry document. Project documents are optional context. Their names describe their role; decide whether and when to read each one from the current stage and request. The presence of a project document does not make it mandatory input.

Workflow

The proposal foundation, entry document, section files, and bibliography describe the assembled proposal. Select the material needed for the checks performed in this review.
Ensure the entry document includes the completed section files in this logical order:
- sections/01-rationale.typ
- sections/02-literature.typ
- sections/03-value.typ
- sections/04-objectives.typ
- sections/05-methods.typ
- sections/07-plan.typ
- sections/06-feasibility.typ
Preserve the layout system established in the first stage. Modify only assembly, document metadata, bibliography wiring, and other entry-level Typst configuration.
Apply the complete cross-section review and dependency checks from the reference.
Check citation keys, terminology, symbols, section order, and unresolved foundation questions. Do not silently rewrite another stage's section.
If a substantive or blocking section problem remains, describe it in findings with its severity, owning stage, exact file, and required correction; keep its source untouched so the author can return to that stage.
Call publish_stage_result from the enabled LLM4AD stage MCP server with the entry path, summary, findings, ready_for_export, context_patch, and a stable idempotency key. Use the patch only for durable context explicitly corrected or established during final interaction; use stable model-defined keys and empty arrays when nothing changed.
Set ready_for_export to false when any blocking finding remains. A successful publication then records a needs_revision review outcome instead of pretending the proposal is complete. Set it to true only when the entry document is structurally compilable and no blocking finding remains. Repair and retry only schema, path, or source-validation errors returned by the tool; do not retry merely because the valid review outcome requires revision.

Constraints

Do not weaken or override the project foundation.
Do not fabricate missing references, results, resources, or author facts.
Do not copy section content into the entry file; include the owned section files.
A warning may remain in findings while the document is exportable, provided the Typst assembly is structurally complete.

Bundled files

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

references/full-proposal-review.md4 KB

Frequently asked questions

What does the Proposal Final Review AI skill do?

Use when assembling a completed staged Typst proposal and checking its evidence, logic, citations, structure, and export readiness.

Why use Proposal Final Review on TypingMind?

Because you install it once and use it with any model. Proposal Final Review 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 Proposal Final Review in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/Optima-CityU/LLM4AD_Next/tree/main/skills/openair-proposal/proposal-final-review. 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 Proposal Final Review?

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 Proposal Final Review?

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

Is the Proposal Final Review AI skill free?

Yes. It is published on GitHub by Optima-CityU under the BSD-3-Clause 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.

View all

Autoreview

openclaw

OrganizationPopular

Structured code review when explicitly requested, preferring OpenAI/Codex before Claude.

Channel Message Flows

openclaw

OrganizationPopular

Use when running QA Lab channel message flow evidence.

Claw Score

Audit or refresh OpenClaw maturity scorecard docs from root taxonomy, maturity scores, and QA evidence artifacts without using maintainer discrawl data or committed inventory reports.

Clawdtributor

Clawtributor PRs here, last week or another window: discover conversation refs, recheck GitHub, rank by impact.

Overview

Installation

Install in TypingMind

Install in another agent

Use it in TypingMind

Works with any AI model

Skill instructions

Proposal Assembly and Final Review

Workflow

Constraints

Bundled files

Frequently asked questions

Related AI Skills

Set up your own AI workspace now