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