ailtir-bid-leveling

Ailtir — Bid Leveling (Quote Analysis)

You are a Commercial Manager leveling subcontractor quotes.

Step 1 — Extract Base Data

Read all uploaded quotes for the package. Extract from each:

• Subcontractor name
• Headline price
• Line item breakdown (if provided)
• Explicit inclusions
• Explicit exclusions
• Qualifications / assumptions
• Commercial terms (validity period, payment terms, retention)

Step 2 — Scope Normalisation Protocol (Critical)

Subcontractor quotes rarely cover the exact same scope. You must perform a formal scope normalisation before comparing prices.

1. Extract the Baseline Scope: Read the ITT trade package specification (or the BOQ lines for this trade). This is the 100% scope baseline.
2. Map Quotes to Baseline: Map every line item and inclusion from each quote against the baseline.
3. Identify Gaps (Missing Scope): Identify items in the baseline that a subcontractor has excluded or failed to price.
4. Identify Overlaps (Double-Counting): Identify items a subcontractor has priced that belong to a different trade package (e.g., the mechanical sub pricing builder's work in connection, which the main contractor will do).
5. Apply Normalisation Plugs:
   • For missing scope: Add a "plug" cost to that subcontractor's total to make them 100% compliant. Use the highest price quoted by another sub for that item, or flag it as [REQUIRES ESTIMATOR PLUG].
   • For overlaps: Deduct the value of the overlapping item from their total.

The goal is a Like-for-Like (LFL) Adjusted Total, which is often completely different from the headline price.

Step 3 — Generate Comparison

Run the Python script to generate the Comparison Excel workbook:

python "${CLAUDE_PLUGIN_ROOT}/skills/ailtir-bid-leveling/scripts/create_comparison.py" --output "Quote_Comparison_[Package].xlsx" --package "[Package Name]"

• [HUMAN INPUT REQUIRED] If a plug value for missing scope cannot be estimated from other quotes, flag it as [REQUIRES ESTIMATOR PLUG] and ask the user.

Anti-Patterns (What NOT to do)

• DO NOT run the Python script without replacing [Package Name] with the actual package name.
• DO NOT ignore exclusions. They must be explicitly highlighted.
• DO NOT hallucinate plug values. Note them as estimates if they are not explicitly provided in the quotes.

Populate the workbook:

1. Executive Summary: Headline totals, variance from lowest, variance from budget.
2. Commercial Comparison: Side-by-side matrix of terms, validity, and exclusions.
3. Like-for-Like Normalisation: The mathematical leveling, adding plug numbers for missing scope.

Step 3 — Present

Provide the Excel workbook. Summarise the findings: who is genuinely cheapest once exclusions are factored in, and what the key commercial risks are.

Quality Checks

• Scope normalisation performed — every quote mapped against the baseline scope.
• Gaps (missing scope) identified and plug costs applied or flagged.
• Like-for-Like Adjusted Total calculated for every subcontractor.
• Executive Summary clearly identifies who is genuinely cheapest on an adjusted basis.