epd-parser

/epd-parser — EPD PDF Parser

Extract structured environmental impact data from EPD (Environmental Product Declaration) PDF files. Uses PyMuPDF for text extraction and Claude's reasoning to parse varying EPD formats into a standardized 42-column schema.

EPDs follow ISO 14025 / ISO 21930 / EN 15804 and report life cycle environmental impacts of building products. This skill reads those PDFs and structures the data for comparison, specification, and LEED documentation.

Input

The user provides EPD PDFs in one of these ways:

1. File paths — one or more PDF file paths
2. Folder path — a directory containing PDFs (will process all .pdf files)
3. Just invoked — ask the user for file paths or a folder

Also ask (or use defaults):

• Output destination — Google Sheet, local CSV, or markdown (default: ask)

Output Schema

EPD data uses a 42-column schema — separate from the 33-column FF&E product schema. When writing to CSV, use the same column order.

Product Identity (columns A-H)

| Col | Field | Description | Format | |-----|-------|-------------|--------| | A | EPD Link | URL to original EPD document | =HYPERLINK(url, "EPD") or blank for local PDFs | | B | Manufacturer | Company that makes the product | Title Case | | C | Product Name | Declared product or product group | Title Case | | D | Description | Brief product description | Sentence case | | E | Declared Unit | Functional/declared unit (e.g., "1 m2", "1 kg", "1 m3") | As stated in EPD | | F | Functional Unit | Functional unit with RSL if different from declared | As stated, blank if same | | G | CSI Division | MasterFormat division number | 03, 05, 07, 08, 09, etc. | | H | Material Category | Normalized material type | See vocabulary below |

EPD Metadata (columns I-P)

| Col | Field | Description | Format | |-----|-------|-------------|--------| | I | EPD Registration No. | Unique EPD identifier | As published | | J | Program Operator | Certifying body | UL, NSF, SCS, IBU, Environdec, etc. | | K | PCR Reference | Product Category Rule reference | Full citation | | L | PCR Expiry | PCR expiration date | YYYY-MM-DD | | M | Standard | Governing standard | ISO 14025, ISO 21930, EN 15804+A2, etc. | | N | System Boundary | Scope of LCA | Cradle-to-gate, Cradle-to-grave, Cradle-to-gate with options | | O | Valid From | EPD publication date | YYYY-MM-DD | | P | Valid To | EPD expiration date | YYYY-MM-DD |

Impact Indicators — Product Stage A1-A3 (columns Q-V)

| Col | Field | Description | Unit | |-----|-------|-------------|------| | Q | GWP-total (A1-A3) | Global Warming Potential, total | kg CO2e | | R | GWP-fossil (A1-A3) | GWP from fossil sources | kg CO2e | | S | GWP-biogenic (A1-A3) | GWP from biogenic sources | kg CO2e | | T | ODP (A1-A3) | Ozone Depletion Potential | kg CFC-11e | | U | AP (A1-A3) | Acidification Potential | kg SO2e | | V | EP (A1-A3) | Eutrophication Potential | kg PO4e |

Impact Indicators — Other Stages (columns W-AB)

| Col | Field | Description | Unit | |-----|-------|-------------|------| | W | GWP (A4-A5) | Construction stage GWP | kg CO2e | | X | GWP (B1-B7) | Use stage GWP | kg CO2e | | Y | GWP (C1-C4) | End-of-life GWP | kg CO2e | | Z | GWP (D) | Beyond system boundary GWP | kg CO2e | | AA | GWP-total (all stages) | Sum of all declared stages | kg CO2e | | AB | POCP (A1-A3) | Photochemical Ozone Creation Potential | kg C2H4e |

Resource Use (columns AC-AH)

| Col | Field | Description | Unit | |-----|-------|-------------|------| | AC | PERE (A1-A3) | Primary Energy, Renewable, energy use | MJ | | AD | PENRE (A1-A3) | Primary Energy, Non-Renewable, energy use | MJ | | AE | Total Energy (A1-A3) | PERE + PENRE | MJ | | AF | FW (A1-A3) | Fresh Water Use | m3 | | AG | Recycled Content | Percentage of recycled content | % | | AH | Waste (A1-A3) | Total waste generated | kg |

Tracking (columns AI-AP)

| Col | Field | Description | Format | |-----|-------|-------------|--------| | AI | LEED Eligible | MRc2 compliance flag | Yes, No, Partial | | AJ | EC3 ID | Building Transparency EC3 identifier | As listed, blank if unknown | | AK | Plant/Facility | Manufacturing plant or facility name | As stated | | AL | Country | Manufacturing country | ISO 3166-1 alpha-2 | | AM | Parsed At | Timestamp of parsing | ISO 8601 | | AN | Tags | User-assigned tags | Comma-separated | | AO | Notes | Additional context | Free text — see below | | AP | Source | Which skill created this row | epd-parser |

Material Category Vocabulary

Use ONE normalized term: Concrete, Steel, Aluminum, Wood/Timber, Insulation, Gypsum, Glass, Ceramic/Tile, Carpet, Resilient Flooring, Roofing Membrane, Sealant, Paint/Coating, Masonry, Stone, Composite Panel, Acoustic, Cladding, Rebar, Cement, Aggregate, Furniture, Other.

EPD-specific data in Notes (col AO)

EPDs contain fields that don't have dedicated columns. Append these to Notes:

• EPD Type: Type: Product-specific or Type: Industry-average or Type: Sector
• Verification: Verified by: [verifier name]
• EN version: EN 15804+A1 or EN 15804+A2 (important for comparability)
• Source File: Source: holcim-readymix-epd.pdf
• LCA Software: LCA: GaBi or LCA: SimaPro or LCA: openLCA
• Biogenic carbon note: If the EPD reports biogenic carbon storage separately

Example Notes cell: Type: Product-specific | Verified by: Underwriters Laboratories | EN 15804+A2 | LCA: GaBi | Source: holcim-readymix-epd.pdf

LEED Eligibility Logic (col AI)

• Yes: Product-specific, third-party verified EPD conforming to ISO 14025
• Partial: Industry-average or sector EPD (counts for LEED Option 1 but not Option 2)
• No: Self-declared, unverified, or non-conforming

Workflow

Step 1: Get input

Parse the user's input to identify PDF file(s) and output preferences.

• If given a folder, list all .pdf files and report count
• If no PDFs found or path is invalid, ask the user
• Report: "Found N EPD PDF(s) to process."

Step 2: Extract text from PDF

Use PyMuPDF (fitz) to extract text from each PDF. Run this Python script via Bash:

import fitz
import sys
import json

pdf_path = sys.argv[1]
doc = fitz.open(pdf_path)
pages = []
for i, page in enumerate(doc):
    text = page.get_text()
    pages.append({"page": i + 1, "text": text})
doc.close()

print(json.dumps({"filename": pdf_path.split("/")[-1], "total_pages": len(pages), "pages": pages}))

For each PDF, extract all pages and save the JSON output.

Step 3: Parse EPD data

Read the extracted text and identify all environmental impact data. This is the core intelligence step.

For small EPDs (<=30 pages): Process all pages at once.

For large EPDs (>30 pages): Process in chunks of 15 pages. Carry forward context between chunks.

Parsing instructions:

1. Identify the EPD structure — EPDs typically have these sections:
2. General information (pages 1-2): manufacturer, product, declared unit, program operator, validity
3. Product description (pages 2-3): materials, manufacturing process, application
4. LCA information: system boundary, data sources, allocation rules
5. Impact indicator tables: the core data — usually 1-3 pages of tables
6. Resource use and waste tables
7. Additional information: scenarios, biogenic carbon, recycled content

1. Extract product identity first — manufacturer, product name, declared unit, functional unit. These are always on page 1-2.

1. Extract EPD metadata — registration number, program operator, PCR, standard, dates, system boundary. Usually on page 1 or in a header/sidebar.

1. Find and parse impact indicator tables — This is the most critical step:
2. Look for tables with life cycle stage columns (A1, A2, A3 or A1-A3 combined, A4, A5, B1-B7, C1-C4, D)
3. Impact categories are rows: GWP, ODP, AP, EP, POCP, ADP (or ADPE/ADPF)
4. EN 15804+A2 EPDs split GWP into: GWP-tot