Grant Proposal Assistant

A comprehensive tool for writing competitive grant proposals targeting NIH (R01/R21), NSF, and other major funding agencies.

Capabilities

1. Section Templates: Standard templates for all major grant sections
2. Specific Aims Generator: Structured approach to crafting compelling Specific Aims pages
3. Budget Justification Helper: Equipment, personnel, and other cost justifications
4. Review & Critique: Self-assessment checklists for proposal quality

Usage

Command Line

# Generate Specific Aims template
python3 scripts/main.py --section aims --output my_aims.md

# Generate full proposal template
python3 scripts/main.py --section full --agency NIH --type R01 --output proposal.md

# Budget justification helper
python3 scripts/main.py --section budget --category personnel --output budget.md

# Review existing proposal
python3 scripts/main.py --review --input my_proposal.md

As Library

from scripts.main import GrantProposalAssistant

assistant = GrantProposalAssistant(agency="NIH", grant_type="R01")
template = assistant.generate_section("specific_aims")
budget = assistant.generate_budget_justification(category="equipment", items=[...])

Parameters

Parameter	Description	Options
--section	Section to generate	aims, significance, approach, budget, full
--agency	Funding agency	NIH, NSF, DOD, VA
--type	Grant mechanism	R01, R21, R03, SBIR, STTR
--category	Budget category	personnel, equipment, supplies, travel, other
--input	Input file for review	Path to existing proposal
--output	Output file path	Path for generated content

Technical Difficulty

Medium - Requires understanding of grant structure, funding agency requirements, and scientific writing best practices.

References

• references/NIH_R01_template.md - NIH R01 full proposal template
• references/NSF_template.md - NSF standard grant template
• references/budget_templates.xlsx - Budget templates by category
• references/review_checklist.md - Proposal quality checklist
• references/specific_aims_examples.md - Example Specific Aims pages

Best Practices

1. Start with Specific Aims: This 1-page summary drives the entire proposal
2. Follow Page Limits: NIH R01 Research Strategy = 12 pages, Specific Aims = 1 page
3. Use Significance-Innovation-Approach Structure: Standard for NIH applications
4. Justify Everything: Every budget item needs a clear justification
5. Review with Checklist: Use the built-in review tool before submission

Agency-Specific Notes

NIH R01/R21

• Page limits strictly enforced
• Significance, Innovation, Approach structure required
• Vertebrate animals and human subjects sections if applicable
• Resubmission strategy for A1 applications

NSF

• Project Summary (1 page) and Project Description (15 pages)
• Broader impacts criterion weighted equally with intellectual merit
• Data management plan required
• Facilities and resources section

Version

1.0.0 - Initial release with NIH and NSF support

Risk Assessment

Risk Indicator	Assessment	Level
Code Execution	Python/R scripts executed locally	Medium
Network Access	No external API calls	Low
File System Access	Read input files, write output files	Medium
Instruction Tampering	Standard prompt guidelines	Low
Data Exposure	Output files saved to workspace	Low

Security Checklist

• No hardcoded credentials or API keys
• No unauthorized file system access (../)
• Output does not expose sensitive information
• Prompt injection protections in place
• Input file paths validated (no ../ traversal)
• Output directory restricted to workspace
• Script execution in sandboxed environment
• Error messages sanitized (no stack traces exposed)
• Dependencies audited

Prerequisites

No additional Python packages required.

Evaluation Criteria

Success Metrics

• Successfully executes main functionality
• Output meets quality standards
• Handles edge cases gracefully
• Performance is acceptable

Test Cases

1. Basic Functionality: Standard input → Expected output
2. Edge Case: Invalid input → Graceful error handling
3. Performance: Large dataset → Acceptable processing time

Lifecycle Status

• Current Stage: Draft
• Next Review Date: 2026-03-06
• Known Issues: None
• Planned Improvements:
  • Performance optimization
  • Additional feature support