Mmcp.market

research-grants skill

by K-Dense-AI·K-Dense-AI/scientific-agent-skills·47k stars·MIT

Write competitive research proposals for NSF, NIH, DOE, DARPA, and Taiwan NSTC. Agency-specific formatting, review criteria, budget preparation, broader impacts, significance statements, innovation narratives, and compliance with submission requirements.

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Install the research-grants skill

A skill is a folder. Copy it into your agent's skills folder and the agent loads it when the task matches its description. 

git clone --depth 1 https://github.com/K-Dense-AI/scientific-agent-skills.git /tmp/scientific-agent-skills
mkdir -p ~/.claude/skills
cp -r /tmp/scientific-agent-skills/skills/research-grants ~/.claude/skills/research-grants
available in every project

In the Claude apps, zip the folder and upload it from the Skills settings. The folder on GitHub

The instructions your agent would load

SKILL.md as published, without the frontmatter. Read it on GitHub

Research Grant Writing

Overview

Research grant writing is the process of developing competitive funding proposals for federal agencies and foundations. Master agency-specific requirements, review criteria, narrative structure, budget preparation, and compliance for NSF (National Science Foundation), NIH (National Institutes of Health), DOE (Department of Energy), DARPA (Defense Advanced Research Projects Agency), and Taiwan's NSTC (National Science and Technology Council) submissions.

Critical Principle: Grants are persuasive documents that must simultaneously demonstrate scientific rigor, innovation, feasibility, and broader impact. Each agency has distinct priorities, review criteria, formatting requirements, and strategic goals that must be addressed.

When to Use This Skill

This skill should be used when:

  • Writing research proposals for NSF, NIH, DOE, DARPA, or NSTC programs
  • Preparing project descriptions, specific aims, or technical narratives
  • Developing broader impacts or significance statements
  • Creating research timelines and milestone plans
  • Preparing budget justifications and personnel allocation plans
  • Responding to program solicitations or funding announcements
  • Addressing reviewer comments in resubmissions
  • Planning multi-institutional collaborative proposals
  • Writing preliminary data or feasibility sections
  • Preparing biosketches, CVs, or facilities descriptions

Visual Enhancement (Optional)

Strong proposals often include 1–3 figures (timelines, workflow diagrams, preliminary data). Figures support review but are not a substitute for clear aims and methods.

When figures help:

  • Research methodology and workflow diagrams
  • Project timeline or Gantt charts
  • Conceptual framework or system architecture (technical proposals)
  • Experimental design flowcharts
  • Broader impacts activity diagrams
  • NSTC CM03 research architecture diagrams (often expected)

How to create figures:

  • Preferred: Use the scientific-schematics skill (--doc-type grant) for AI-generated diagrams from a natural-language description
  • Alternative: Build figures in your usual tools (matplotlib, Illustrator, PowerPoint, etc.)

Run from the repository root, with OPENROUTERAPIKEY set:

python skills/scientific-schematics/scripts/generate_schematic.py "project timeline with Year 1-3 milestones" -o figures/timeline.png --doc-type grant

Disclosure: AI schematic generation sends your prompt to OpenRouter (a third-party API). Do not include unpublished sensitive details unless that transmission is appropriate for your project.

Agency-Specific Overview

NSF (National Science Foundation)

Mission: Promote the progress of science and advance national health, prosperity, and welfare

Key Features:

  • Follow PAPPG 24-1 (effective May 20, 2024) unless a solicitation overrides it
  • Intellectual Merit + Broader Impacts (equally weighted)
  • 15-page project description limit (most programs; includes Results from Prior NSF Support, max 5 pages)
  • Emphasis on education, diversity, and societal benefit
  • Collaborative research encouraged
  • Open data and open science emphasis
  • Merit review process with panel + ad hoc reviewers

NIH (National Institutes of Health)

Mission: Enhance health, lengthen life, and reduce illness and disability

Key Features:

  • Specific Aims (1 page) + Research Strategy (12 pages for R01)
  • Significance, Innovation, Approach as core review criteria
  • Preliminary data typically required for R01s
  • Emphasis on rigor, reproducibility, and clinical relevance
  • Modular budgets ($250K increments) for most R01s
  • Multiple resubmission opportunities

DOE (Department of Energy)

Mission: Ensure America's security and prosperity through energy, environmental, and nuclear challenges

Key Features:

  • Focus on energy, climate, computational science, basic energy sciences
  • Often requires cost sharing or industry partnerships
  • Emphasis on national laboratory collaboration
  • Strong computational and experimental integration
  • Energy innovation and commercialization pathways
  • Varies by office (ARPA-E, Office of Science, EERE, etc.)

DARPA (Defense Advanced Research Projects Agency)

Mission: Make pivotal investments in breakthrough technologies for national security

Key Features:

  • High-risk, high-reward transformative research
  • Focus on "DARPA-hard" problems (what if true, who cares)
  • Emphasis on prototypes, demonstrations, and transition paths
  • Often requires multiple phases (feasibility, development, demonstration)
  • Strong project management and milestone tracking
  • Teaming and collaboration often required
  • Varies dramatically by program manager and BAA (Broad Agency Announcement)

NSTC (National Science and Technology Council - Taiwan)

Mission: Advance scientific breakthrough, industrial application, and societal impact in Taiwan.

Key Features:

  • CM03 Form: The core technical proposal format.
  • Bilingual: Abstract required in both Chinese and English.
  • Innovation & Feasibility: Primary review focus.
  • Preliminary Data: Highly critical for credibility.
  • Research Architecture Diagram: A mandatory visual element for clarity.

Core Components of Research Proposals

Section-by-section guidance for every standard proposal component — specific aims, significance, innovation, approach, preliminary data, timeline, budget and justification, biosketch, facilities, data management and sharing, and broader impacts — with structure, length targets, and worked language, is in references/core_components.md.

Review Criteria, Writing Principles, and Proposal Types

DARPA score proposals, and what each criterion actually rewards.

  • references/review_criteria.md: how NIH, NSF, DOE, and

funded proposals from competent ones — framing, specificity, reviewer psychology, and readability.

  • references/writing_principles.md: what separates

the common proposal types and how to handle a resubmission, including responding to a summary statement.

  • references/proposaltypesand_resubmission.md:

Common Mistakes to Avoid

Conceptual Mistakes

  1. Failing to Address Review Criteria: Not explicitly discussing significance, innovation, approach, etc.
  2. Mismatch with Agency Mission: Proposing research that doesn't align with agency goals
  3. Unclear Significance: Failing to articulate why the research matters
  4. Insufficient Innovation: Incremental work presented as transformative
  5. Vague Objectives: Goals that are not specific or measurable

Writing Mistakes

  1. Poor Organization: Lack of clear structure and flow
  2. Excessive Jargon: Inaccessible to broader review panel
  3. Verbosity: Unnecessarily complex or wordy writing
  4. Missing Context: Assuming reviewers know your field deeply
  5. Inconsistent Terminology: Using different terms for same concept

Technical Mistakes

  1. Inadequate Methods: Insufficient detail to judge feasibility
  2. Overly Ambitious: Too much proposed for timeline/budget
  3. No Preliminary Data: For mechanisms requiring demonstrated feasibility
  4. Poor Timeline: Unrealistic or poorly justified schedule
  5. Misaligned Budget: Budget doesn't support proposed activities

Formatting Mistakes

  1. Exceeding Page Limits: Automatic rejection
  2. Wrong Font or Margins: Non-compliant formatting
  3. Missing Required Sections: Incomplete application
  4. Poor Figure Quality: Illegible or unprofessional figures
  5. Inconsistent Citations: Formatting errors in references

Strategic Mistakes

  1. Wrong Program or Mechanism: Proposing to inappropriate opportunity
  2. Weak Team: Insufficient expertise or missing key collaborators
  3. No Broader Impacts: For NSF, failing to adequately address
  4. Ignoring Program Priorities: Not aligning with current emphasis areas
  5. Late Submission: Technical issues or rushed preparation

Workflow for Grant Development

Phase 1: Planning and Preparation (2-6 months before deadline)

Activities:

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