Grant Mock Reviewer

---

name: grant-mock-reviewer

description: Simulates NIH study section peer review for grant proposals. Triggers

when user wants mock review, critique, or evaluation of a grant proposal before

submission. Generates structured critique using official NIH scoring rubric (1-9

scale), identifies weaknesses, provides actionable revision recommendations, and

produces a comprehensive review summary similar to actual NIH Summary Statement.

version: 1.0.0

category: Grant

tags: []

author: AIPOCH

license: MIT

status: Draft

risk_level: Medium

skill_type: Tool/Script

owner: AIPOCH

reviewer: ''

last_updated: '2026-02-06'

---

# Grant Mock Reviewer

A simulated NIH study section reviewer that provides structured, rigorous critique of grant proposals using the official NIH scoring criteria and methodology.

Capabilities

1. **NIH Scoring Rubric Application**: Official 1-9 scale scoring across all 5 criteria

2. **Weakness Identification**: Systematic detection of common proposal flaws

3. **Critique Generation**: Structured written critiques for each review criterion

4. **Summary Statement**: Complete mock Summary Statement output

5. **Revision Guidance**: Prioritized, actionable recommendations for improvement

Usage

Command Line

# Full mock review with Summary Statement
python3 scripts/main.py --input proposal.pdf --format pdf --output review.md

# Review Specific Aims only
python3 scripts/main.py --input aims.pdf --section aims --output aims_review.md

# Targeted review (specific criterion focus)
python3 scripts/main.py --input proposal.pdf --focus approach --output approach_critique.md

# Generate NIH-style scores only
python3 scripts/main.py --input proposal.pdf --scores-only --output scores.json

# Compare before/after revision
python3 scripts/main.py --original original.pdf --revised revised.pdf --compare

As Library

from scripts.main import GrantMockReviewer

reviewer = GrantMockReviewer()
result = reviewer.review(
    proposal_text=proposal_content,
    grant_type="R01",
    section="full"
)
print(result.summary_statement)
print(result.scores)

Parameters

| Parameter | Type | Default | Required | Description |

|-----------|------|---------|----------|-------------|

| `--input` | string | - | Yes | Path to proposal file (PDF, DOCX, TXT, MD) |

| `--format` | string | auto | No | Input file format (pdf, docx, txt, md) |

| `--section` | string | full | No | Section to review (full, aims, significance, innovation, approach) |

| `--grant-type` | string | R01 | No | Grant mechanism (R01, R21, R03, K99, F32) |

| `--focus` | string | - | No | Focus on specific criterion (significance, investigator, innovation, approach, environment) |

| `--scores-only` | flag | false | No | Output scores only (JSON) |

| `--output`, `-o` | string | stdout | No | Output file path |

| `--original` | string | - | No | Original proposal for comparison |

| `--revised` | string | - | No | Revised proposal for comparison |

| `--compare` | flag | false | No | Enable comparison mode |

NIH Scoring System

Overall Impact Score (1-9)

The single most important score reflecting the likelihood of the project to exert a sustained, powerful influence on the research field.

| Score | Descriptor | Likelihood of Funding |

|-------|------------|----------------------|

| 1 | Exceptional | Very High |

| 2 | Outstanding | High |

| 3 | Excellent | Good |

| 4 | Very Good | Moderate |

| 5 | Good | Low-Moderate |

| 6 | Satisfactory | Low |

| 7 | Fair | Very Low |

| 8 | Marginal | Unlikely |

| 9 | Poor | Not Fundable |

Individual Criteria (1-9 each)

1. **Significance**: Does the project address an important problem? Will scientific knowledge be advanced?

2. **Investigator(s)**: Are the PIs well-suited? Adequate experience and training?

3. **Innovation**: Does it challenge current paradigms? Novel concepts, approaches, methods?

4. **Approach**: Sound research design? Appropriate methods? Adequate controls? Address pitfalls?

5. **Environment**: Adequate institutional support? Scientific environment conducive to success?

Score Interpretation

Review Output Format

1. Score Summary

Overall Impact: [Score] - [Descriptor]

Criterion Scores:
- Significance: [Score]
- Investigator(s): [Score]
- Innovation: [Score]
- Approach: [Score]
- Environment: [Score]

2. Strengths

Bullet-point list of major strengths by criterion

3. Weaknesses

Bullet-point list of major weaknesses by criterion

4. Detailed Critique

Paragraph-form critique for each criterion following NIH style

5. Summary Statement

Complete narrative synthesis of the review

6. Revision Recommendations

Prioritized, actionable suggestions for improvement

Common Weaknesses Detected

Significance

Investigator

Innovation

Approach

Environment

Technical Difficulty

**High** - Requires deep understanding of NIH peer review processes, ability to apply standardized scoring rubrics consistently, and generation of clinically/scientifically accurate critique across diverse research domains.

**Review Required**: Human verification recommended before deployment in production settings.

References

Best Practices for Users

1. **Provide Complete Proposals**: The tool works best with full Research Strategy sections

2. **Include Preliminary Data**: Approach critique depends on feasibility evidence

3. **Review Multiple Times**: Use iteratively as you revise

4. **Compare Versions**: Track improvement between drafts

5. **Consider Multiple Perspectives**: Supplement with human reviewer feedback

Limitations

1. Cannot access external literature to verify claims

2. May not capture domain-specific methodological nuances

3. Scoring is simulated and may not match actual study section scores

4. Best used as preparatory tool, not replacement for human review

Version

1.0.0 - Initial release with NIH R01/R21/R03 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

Prerequisites

# Python dependencies
pip install -r requirements.txt

Evaluation Criteria

Success Metrics

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

- Performance optimization

- Additional feature support