mcpField
S
subcontractor-prequalification

subcontractor-prequalification

github.com/datadrivenconstructionOther375112 installsUpdated 1w ago
Repository

About subcontractor-prequalification

A Python-based subcontractor prequalification tool for construction procurement. It records applications and supports scoring candidates across criteria such as safety, financial stability, and experience.

Key features

  1. 01Subcontractor application entry
  2. 02Qualification scoring
  3. 03Safety, financial, and experience criteria

Use cases

  1. 01Recording subcontractor applications
  2. 02Scoring candidates during procurement

Install

Copy the command and run it in a terminal.

$npx skills add https://github.com/datadrivenconstruction/ddc_skills_for_ai_agents_in_construction --skill subcontractor-prequalification

After installing, type/subcontractor-prequalificationin Claude Code to confirm it loaded.

Bundled filesclaw.jsoninstructions.md

Details

From the project README

Subcontractor Prequalification

Technical Implementation

import pandas as pd
from datetime import date
from typing import Dict, Any, List
from dataclasses import dataclass, field
from enum import Enum


class QualificationStatus(Enum):
    PENDING = "pending"
    QUALIFIED = "qualified"
    CONDITIONALLY_QUALIFIED = "conditionally_qualified"
    NOT_QUALIFIED = "not_qualified"


@dataclass
class PrequalificationCriteria:
    name: str
    weight: float
    min_score: int
    max_score: int = 10


@dataclass
class SubcontractorApplication:
    app_id: str
    company_name: str
    trade: str
    contact_email: str
    years_in_business: int
    annual_revenue: float
    bonding_capacity: float
    emr_rate: float  # Experience Modification Rate
    status: QualificationStatus
    scores: Dict[str, int] = field(default_factory=dict)
    documents_received: List[str] = field(default_factory=list)
    notes: str = ""

    @property
    def total_score(self) -> float:
        return sum(self.scores.values())


class SubcontractorPrequalification:
    def __init__(self, project_name: str):
        self.project_name = project_name
        self.applications: Dict[str, SubcontractorApplication] = {}
        self.criteria = self._default_criteria()
        self._counter = 0

    def _default_criteria(self) -> List[PrequalificationCriteria]:
        return [
            PrequalificationCriteria("Safety Record", 0.25, 6),
            PrequalificationCriteria("Financial Stability", 0.20, 5),
            PrequalificationCriteria("Experience", 0.20, 6),
            PrequalificationCriteria("References", 0.15, 5),
            PrequalificationCriteria("Capacity", 0.10, 5),
            PrequalificationCriteria("Insurance/Bonding", 0.10, 7)
        ]

    def add_application(self, company_name: str, trade: str, contact_email: str,
                       years_in_business: int, annual_revenue: float,
                       bonding_capacity: float, emr_rate: float) -> SubcontractorApplication:
        self._counter += 1
        app_id = f"PQ-{self._counter:03d}"

        app = SubcontractorApplication(
            app_id=app_id,
            company_name=company_name,
            trade=trade,
            contact_email=contact_email,
            years_in_business=years_in_business,
            annual_revenue=annual_revenue,
            bonding_capacity=bonding_capacity,
            emr_rate=emr_rate,
            status=QualificationStatus.PENDING
        )
        self.applications[app_id] = app
        return app

    def score_application(self, app_id: str, scores: Dict[str, int]):
        if app_id not in self.applications:
            return
        app = self.applications[app_id]
        app.scores = scores
        self._evaluate_qualification(app)

    def _evaluate_qualification(self, app: SubcontractorApplication):
        passed = True
        for criteria in self.criteria:
            score = app.scores.get(criteria.name, 0)
            if score < criteria.min_score:
                passed = False
                break

        if passed and app.total_score >= 60:
            app.status = QualificationStatus.QUALIFIED
        elif app.total_score >= 50:
            app.status = QualificationStatus.CONDITIONALLY_QUALIFIED
        else:
            app.status = QualificationStatus.NOT_QUALIFIED

    def get_qualified(self, trade: str = None) -> List[SubcontractorApplication]:
        qualified = [a for a in self.applications.values()
                    if a.status in [QualificationStatus.QUALIFIED,
                                   QualificationStatus.CONDITIONALLY_QUALIFIED]]
        if trade:
            qualified = [a for a in qualified if a.trade.lower() == trade.lower()]
        return qualified

    def export_register(self, output_path: str):
        data = [{
            'ID': a.app_id,
            'Company': a.company_name,
            'Trade': a.trade,
            'Years': a.years_in_business,
            'Revenue': a.annual_revenue,
            'EMR': a.emr_rate,
            'Status': a.status.value,
            'Score': a.total_score
        } for a in self.applications.values()]
        pd.DataFrame(data).to_excel(output_path, index=False)

Quick Start

prequal = SubcontractorPrequalification("Office Tower")

app = prequal.add_application("ABC Electric", "Electrical", "[email protected]",
                              years_in_business=15, annual_revenue=10000000,
                              bonding_capacity=5000000, emr_rate=0.85)

prequal.score_application(app.app_id, {
    "Safety Record": 8, "Financial Stability": 7, "Experience": 8,
    "References": 7, "Capacity": 8, "Insurance/Bonding": 9
})

qualified = prequal.get_qualified("Electrical")

Resources

  • DDC Book: Chapter 3.4 - Procurement

Comments

Markdown supported