research-grants
Supports research proposal preparation and review for NSF, NIH, DOE, DARPA, and Taiwan NSTC, including opportunity-specific requirements, aims, review criteria, budgets, broader impacts, forms, and resubmissions.
Install / Use
npx skills add K-Dense-AI/scientific-agent-skills --skill research-grantsInstalls into whichever agent you are using.
SKILL.md
Installable skill definition
Quality Score
Category
Content & MediaSupported Platforms
Our assessment of research-grants
research-grants scores 96/100 on our quality scale, 54th of 1,186 Content & Media skills we index (top 5%).
Its SKILL.md is 14 KB long, well organised into 28 sections with 1 code example: a thorough specification that gives an agent plenty to work with.
With 46,441 GitHub stars, it is one of the more widely adopted skills in the catalogue.
Maintenance, license and trust
- The repository was last updated about 2 months ago, so research-grants is actively maintained.
- Our last check on 2026-10-23 found the source still online.
- It is released under the MIT license, a permissive license that allows use, modification and commercial use with attribution.
- Its trust signals score 100/100, with no cautions. These come from repository metadata, not a code audit — read the skill file before letting an agent act on it.
Safety scan
No issues foundOur scan of the whole file found no instruction hijacking, hidden characters, credential access, data exfiltration or destructive commands. An AI review of the same text found nothing harmful.
AI review by kimi-k2.7-code on 2026-09-25. Automated pattern scan on 2026-09-25. It catches known dangerous patterns, not every risk — read a skill before letting an agent act on it.
research-grants compared with similar skills
All 4 of these similar skills score higher than research-grants; compare them before choosing.
| Skill | Score | Stars | Updated | Format |
|---|---|---|---|---|
| research-grants (this skill)by K-Dense-AI | 96 | 46.4k | 48d ago | SKILL.md |
| siyuanby siyuan-note | 100 | 47.1k | today | MCP Server |
| algorithmic-artby anthropics | 100 | 177.9k | 47d ago | SKILL.md |
| pptxby anthropics | 100 | 177.9k | 47d ago | SKILL.md |
| designby nextlevelbuilder | 100 | 143.4k | 8d ago | SKILL.md |
Frequently asked questions
- How do I install research-grants?
- Run
npx skills add K-Dense-AI/scientific-agent-skills --skill research-grants. The install tabs above show the steps for each supported agent. - Which AI agents does research-grants work with?
- It is written for Universal, as a SKILL.md file. Other agents that read the same format can often use it too.
- Is research-grants safe to use?
- Our scan of the whole file found no instruction hijacking, hidden characters, credential access, data exfiltration or destructive commands. An AI review of the same text found nothing harmful. It is MIT-licensed and scores 100/100 on trust signals. Skills are instructions an agent will follow, so read the file before installing it and do not approve commands you do not understand.
- Is research-grants still maintained?
- The repository was last updated about 2 months ago, so research-grants is actively maintained.
Skill content
View source on GitHubname: research-grants description: 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. allowed-tools: Read Write Edit Bash license: MIT license compatibility: Works in Agent Skills-compatible hosts. Grant-writing guidance needs no network; optional figures via the scientific-schematics skill require OPENROUTER_API_KEY and outbound API access. metadata: version: "1.3" skill-author: K-Dense Inc.
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 OPENROUTER_API_KEY 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
- references/review_criteria.md: how NIH, NSF, DOE, and DARPA score proposals, and what each criterion actually rewards.
- references/writing_principles.md: what separates funded proposals from competent ones — framing, specificity, reviewer psychology, and readability.
- references/proposal_types_and_resubmission.md: the common proposal types and how to handle a resubmission, including responding to a summary statement.
Common Mistakes to Avoid
Conceptual Mistakes
- Failing to Address Review Criteria: Not explicitly discussing significance, innovation, approach, etc.
- Mismatch with Agency Mission: Proposing research that doesn't align with agency goals
- Unclear Significance: Failing to articulate why the research matters
- Insufficient Innovation: Incremental work presented as transformative
- Vague Objectives: Goals that are not specific or measurable
Writing Mistakes
- Poor Organization: Lack of clear structure and flow
- Excessive Jargon: Inaccessible to broader review panel
- Verbosity: Unnecessarily complex or wordy writing
- Missing Context: Assuming reviewers know your field deeply
- Inconsistent Terminology: Using different terms for same concept
Technical Mistakes
- Inadequate Methods: Insufficient detail to judge feasibility
- Overly Ambitious: Too much proposed for timeline/budget
- No Preliminary Data: For mechanisms requiring demonstrated feasibility
- Poor Timeline: Unrealistic or poorly justified schedule
- Misaligned Budget: Budget doesn't support proposed activities
Formatting Mistakes
- Exceeding Page Limits: Automatic rejection
- Wrong Font or Margins: Non-compliant formatting
- Missing Required Sections: Incomplete application
- Poor Figure Quality: Illegible or unprofessional figures
- Inconsistent Citations: Formatting errors in references
Strategic Mistakes
- Wrong Program or Mechanism: Proposing to inappropriate opportunity
- Weak Team: Insufficient expertise or missing key collaborators
- No Broader Impacts: For NSF, failing to adequately address
- Ignoring Program Priorities: Not aligning with current emphasis areas
- Late Submission: Technical issues or rushed preparation
Workflow for Grant Development
Phase 1: Planning and Preparation (2-6 months before deadline)
Activities:
- Identify appropriate funding opportunities
- Review program announcements and requirements
- Consult with program officers (if appropriate)
- Assemble team and confirm collaborations
- Develop preliminary data (if needed)
- Outline research plan and specific aims
- Review successful proposals (if available)
Outputs:
- Selected funding opportunity
- Assembled team with defined roles
- Preliminary outline of specific aims
- Gap analysis of needed preliminary data
Phase 2: Drafting (2-3 months before deadline)
Activities:
- Write specific aims or objectives (start here!)
- Develop project description/research strategy
- Create figures and data visualizations
- Draft timeline and milestones
- Prepare preliminary budget
- Write broader impacts or significance sections
- Request letters of support/collaboration
Outputs:
- Complete first draft of narrative sections
- Preliminary budget with justification
- Timeline and management plan
- Requested letters from collaborators
Phase 3: Internal Review (1-2 months before deadline)
Activities:
- Circulate draft to co-investigators
- Seek feedback from colleagues and mentors
- Request institutional review (if required)
- Mock review session (if possible)
- Revise based on feedback
- Refine budget and budget justification
Outputs:
- Revised draft incorporating feedback
- Refined budget aligned with revised plan
- Identified weaknesses and mitigation strategies
Phase 4: Finalization (2-4 weeks before deadline)
Activities:
- Final revisions to narrative
- Prepare all required forms and documents
- Finalize budget and budget justification
- Compile biosketches, CVs, and current & pending
- Collect letters of support
- Prepare data management plan (if required)
- Write project summary/abstract
- Proofread all materials
Outputs:
- Complete, polished proposal
- All required supplementary documents
- Formatted according to agency requirements
Phase 5: Submission (1 week before deadline)
Activities:
- Institutional review and approval
- Upload to submission portal
- Verify all documents and formatting
- Submit 24-48 hours before deadline
- Confirm successful submission
- Receive confirmation and proposal number
Outputs:
- Submitted proposal
- Submission confirmation
- Archived copy of all materials
Critical Tip: Never wait until the deadline. Portals crash, files corrupt, and emergencies happen. Aim for 48 hours early.
Integration with Other Skills
This skill works effectively with:
- Scientific Schematics: Optional AI-generated grant figures (
--doc-type grant) - Scientific Writing: For clear, compelling prose
- Literature Review: For comprehensive background sections
- Peer Review: For self-assessment before submission
- Research Lookup: For finding relevant citations and prior work
- Data Visualization: For creating effective figures
Resources
This skill includes comprehensive reference files covering specific aspects of grant writing:
- `references/n
Truncated for display — read the full file on GitHub.
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Trust signals
From repository metadata: license, adoption, age and documentation. Not a code audit — see the Safety scan above for what the skill file itself contains.
