cwicr-bid-analyzer
This skill evaluates contractor bids by comparing them against CWICR-based market benchmarks, flagging unusual pricing patterns and cost composition issues. It produces detailed line-item analysis with variance metrics to support fair, documented bid decisions.
CWICR Bid Analyzer compares contractor bids against market benchmarks to identify pricing anomalies and support objective bid evaluation.
AI-generated summary based on this skill's SKILL.md
Install
datadrivenconstruction/DDC_Skills_for_AI_Agents_in_Construction/cwicr-bid-analyzer · repository language: Python
git clone https://github.com/datadrivenconstruction/DDC_Skills_for_AI_Agents_in_Construction
cp -r DDC_Skills_for_AI_Agents_in_Construction/1_DDC_Toolkit/CWICR-Database/cwicr-bid-analyzer ~/.claude/skills/cwicr-bid-analyzerFrequently asked questions
AI-generated answers based on this skill's SKILL.md and metadata
How does cwicr-bid-analyzer compare bid prices to market rates?
cwicr-bid-analyzer evaluates contractor bids by comparing them against CWICR-based market benchmarks. It analyzes each line item and flags pricing that deviates significantly from established market rates, helping you identify which bids are competitively positioned and which contain cost composition issues that warrant closer review.
Can cwicr-bid-analyzer identify pricing anomalies in construction bids?
Yes. cwicr-bid-analyzer detects pricing anomalies by analyzing bid variance against benchmarks and flagging suspicious patterns in cost structure. It highlights unusual line-item pricing, front-loading strategies, and unbalanced bid compositions that may indicate risk or non-standard cost allocation.
What audit trail does cwicr-bid-analyzer provide for bid evaluation?
cwicr-bid-analyzer produces detailed line-item analysis with variance metrics and documented comparison against CWICR benchmarks. This creates a transparent, traceable record of how each bid was evaluated and ranked, supporting fair procurement decisions and enabling you to defend your bid selection rationale.
How does cwicr-bid-analyzer detect front-loading in contractor bids?
cwicr-bid-analyzer examines cost composition across line items to spot front-loading and unbalanced bidding strategies. By comparing the distribution of costs against market norms and CWICR benchmarks, it flags bids where early phases are disproportionately expensive relative to later work.
What output formats does cwicr-bid-analyzer support?
cwicr-bid-analyzer generates bid analysis reports in Excel format, making it easy to share findings, perform additional analysis, and maintain procurement documentation. Reports include variance metrics, benchmark comparisons, and ranking data for objective bid evaluation.
Can cwicr-bid-analyzer rank multiple contractor bids objectively?
cwicr-bid-analyzer evaluates and ranks multiple bids objectively using CWICR-based benchmarks and variance analysis. It produces a documented ranking with supporting metrics and audit trail, enabling fair comparison across all submitted bids and transparent communication of selection criteria.
SKILL.md
rendered from the published skill — quoted content, verbatim
CWICR Bid Analyzer
Business Case
Problem Statement
Evaluating contractor bids requires: - Comparing against market benchmarks - Identifying unusual pricing - Understanding cost composition - Documenting evaluation rationale
Solution
Analyze contractor bids against CWICR-based benchmarks to identify anomalies, compare components, and support objective bid evaluation.
Business Value
- Objective evaluation - Data-driven bid analysis
- Risk identification - Spot unrealistic pricing
- Fair comparison - Normalized bid analysis
- Documentation - Audit trail for decisions
Technical Implementation
```python import pandas as pd import numpy as np from typing import Dict, Any, List, Optional, Tuple from dataclasses import dataclass, field from datetime import
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1_DDC_Toolkit/CWICR-Database/cwicr-bid-analyzer/SKILL.md
1_DDC_Toolkit/CWICR-Database/cwicr-bid-analyzer/claw.json
1_DDC_Toolkit/CWICR-Database/cwicr-bid-analyzer/instructions.md