grant-proposal-assistant

# 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

```bash
# 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

```python
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