AgentSkillsCN

Evaluate Grant Application

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SKILL.md

Skill: Evaluate Grant Application

Domain

social_public_sector

Description

Evaluates grant applications for eligibility, program alignment, and impact potential using structured scoring criteria for funding decisions.

Tags

grants, nonprofit, funding, evaluation, social-impact, philanthropy

Use Cases

  • •Grant eligibility screening
  • •Application scoring
  • •Impact assessment
  • •Budget reasonableness review

Proprietary Business Rules

Rule 1: Eligibility Verification

Organization and project eligibility criteria check.

Rule 2: Program Alignment Scoring

Assessment of fit with funding priorities.

Rule 3: Budget Reasonableness

Evaluation of proposed budget against norms.

Rule 4: Impact Potential Assessment

Projected outcomes and measurement capacity.

Input Parameters

  • •application_id (string): Application identifier
  • •applicant_info (dict): Organization details
  • •project_proposal (dict): Project description
  • •budget_request (dict): Funding request details
  • •impact_metrics (dict): Proposed outcomes
  • •program_priorities (dict): Funding program criteria

Output

  • •eligibility_status (string): Eligibility determination
  • •total_score (float): Application score
  • •scoring_breakdown (dict): Score by category
  • •budget_assessment (dict): Budget analysis
  • •recommendation (string): Funding recommendation

Implementation

The evaluation logic is implemented in grant_evaluator.py and references data from CSV files:

  • •scoring_rubric.csv - Reference data
  • •budget_rules.csv - Reference data
  • •capacity_criteria.csv - Reference data
  • •focus_area_weights.csv - Reference data
  • •geographic_priorities.csv - Reference data
  • •matching_requirements.csv - Reference data
  • •parameters.csv - Reference data.

Usage Example

python
from grant_evaluator import evaluate_grant

result = evaluate_grant(
    application_id="GRT-2026-001",
    applicant_info={"org_type": "501c3", "years_operating": 10, "annual_budget": 2000000},
    project_proposal={"focus_area": "education", "duration_months": 24, "beneficiaries": 5000},
    budget_request={"amount": 250000, "categories": {"personnel": 150000, "program": 80000}},
    impact_metrics={"primary_outcome": "graduation_rate", "target_improvement": 0.15},
    program_priorities={"focus_areas": ["education", "workforce"], "max_award": 500000}
)

print(f"Total Score: {result['total_score']}")

Test Execution

python
from grant_evaluator import evaluate_grant

result = evaluate_grant(
    application_id=input_data.get('application_id'),
    applicant_info=input_data.get('applicant_info', {}),
    project_proposal=input_data.get('project_proposal', {}),
    budget_request=input_data.get('budget_request', {}),
    impact_metrics=input_data.get('impact_metrics', {}),
    program_priorities=input_data.get('program_priorities', {})
)