Grant Writing

Community

beita6969

grant-writing

Assists with research grant proposal writing including specific aims, significance framing, innovation articulation, approach design, and budget justification for NIH, NSF, ERC, and other funding agencies; trigger when users discuss grant proposals, funding applications, or research funding strategy.

Overview

Publisher	beita6969
Repository	`ScienceClaw`
Skill name	`grant-writing`
Stars	950
Forks	106
Bundled files	Instructions only
License	MIT
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.
Self-contained
Everything the model needs lives in the instructions — no extra files to sync.
Open source
Published by beita6969 on GitHub. Read the source before you install it.

Installation

Install the Grant Writing 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/beita6969/ScienceClaw/tree/main/skills/grant-writing
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/beita6969/ScienceClaw.git /tmp/ScienceClaw
mkdir -p .claude/skills
cp -r /tmp/ScienceClaw/skills/grant-writing .claude/skills/grant-writing

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

Use it in TypingMind

Enable Grant Writing 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 Grant Writing 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 Grant Writing 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.

When to Trigger

Activate this skill when the user mentions:

Grant proposal, research funding, grant application
Specific aims, significance, innovation, approach (NIH format)
R01, R21, K award, NSF CAREER, ERC grants
Budget justification, personnel effort, subcontracts
Preliminary data, feasibility, research plan
Broader impacts, dissemination plan
Resubmission, reviewer critiques, summary statement

Step-by-Step Methodology

Identify the funding mechanism - Determine agency (NIH, NSF, DOD, ERC, private foundation), mechanism (R01, R21, CAREER, etc.), and specific FOA/RFA if applicable. Note page limits, formatting requirements, and review criteria.
Craft Specific Aims - Write a one-page aims document with four elements: (a) Opening paragraph establishing the problem and knowledge gap, (b) "What is known / what is missing" paragraph, (c) 2-3 specific aims with clear hypotheses and approaches, (d) Impact statement. Each aim should be independent yet synergistic.
Significance section - Articulate the burden of the problem (prevalence, cost, impact). Identify the critical barrier or knowledge gap. Explain how the proposed work will shift current understanding or practice. Cite relevant literature to establish context.
Innovation section - Highlight what is new: novel concepts, approaches, methodologies, or technologies. Distinguish from incremental advances. Position relative to the state of the art.
Approach section - For each aim: state rationale, describe methods in detail, present preliminary data, define expected outcomes, identify potential pitfalls with alternative strategies, and provide a timeline. Include rigor and reproducibility elements (biological variables, authentication of key resources).
Budget preparation - Justify personnel (% effort, roles), equipment, supplies, travel, and other costs. Align budget items with specific aims. Ensure modular budget vs. detailed budget used correctly.
Review and refinement - Check against review criteria (Significance, Investigators, Innovation, Approach, Environment for NIH). Ensure each criterion is explicitly addressed. Review for clarity, conciseness, and logical flow.

Key Resources

NIH Reporter - Funded grants database for benchmarking
NSF Award Search - Funded NSF proposals
Grants.gov - Federal funding opportunities
Specific FOA/RFA pages - Agency-specific requirements
NIAID sample applications - Example funded proposals

Output Format

Specific Aims as a structured one-page document.
Section drafts with clear headers matching agency format.
Budget as a table with line items, costs, and justification.
Timeline as a Gantt chart or milestone table by aim and year.
Reviewer-response table for resubmissions (critique, response, changes made).

Quality Checklist

Specific aims are independent (failure of one does not sink the project)
Knowledge gap clearly defined with supporting citations
Preliminary data supports feasibility of each aim
Potential pitfalls identified with concrete alternative approaches
Budget aligned with proposed experiments
Page limits and formatting requirements met
Rigor and reproducibility addressed (NIH requirement)
Broader impacts / translational potential articulated
All required sections and attachments included

Frequently asked questions

What does the Grant Writing AI skill do?

Why use Grant Writing on TypingMind?

Because you install it once and use it with any model. Grant Writing 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 Grant Writing in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/beita6969/ScienceClaw/tree/main/skills/grant-writing. TypingMind reads its SKILL.md and installs it as a skill you can enable per chat.

Which AI models can use Grant Writing?

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 Grant Writing?

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

Is the Grant Writing AI skill free?

Yes. It is published on GitHub by beita6969 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

When to Trigger

Step-by-Step Methodology

Key Resources

Output Format

Quality Checklist

Frequently asked questions

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