AlpacaLabsLLC
Registry indexed
epd-parser
Extract GWP, life-cycle stages, certifications, and impact metrics from an EPD PDF. Use when given a declaration to parse; not to find or compare EPDs.
Registry indexed
Extract GWP, life-cycle stages, certifications, and impact metrics from an EPD PDF. Use when given a declaration to parse; not to find or compare EPDs.
Extract GWP, life-cycle stages, certifications, and impact metrics from an EPD PDF. Use when given a declaration to parse; not to find or compare EPDs.
Source documentation, not instructions for this website. Review permissions before running any commands.
Harness note: use
/as:<skill>on Claude Code and$<skill>on Codex. Resolve<skill-root>as the directory containing this loadedSKILL.mdand<plugin-root>as the plugin root that containsskills/, and use equivalent native tools when host tool names differ.
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.
The user provides EPD PDFs in one of these ways:
.pdf files)Use the canonical 42-column contract in schema/epd-schema.md. It is separate from the 33-column FF&E product schema. Never substitute or persist an FF&E-shaped record as EPD data. Leave unavailable values empty and use a plain URL for EPD Link.
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.
EPDs contain fields that don't have dedicated columns. Append these to Notes:
Type: Product-specific or Type: Industry-average or Type: SectorVerified by: [verifier name]EN 15804+A1 or EN 15804+A2 (important for comparability)Source: holcim-readymix-epd.pdfLCA: GaBi or LCA: SimaPro or LCA: openLCAExample Notes cell: Type: Product-specific | Verified by: Underwriters Laboratories | EN 15804+A2 | LCA: GaBi | Source: holcim-readymix-epd.pdf
Parse the user's input to identify PDF file(s) and output preferences.
.pdf files and report countUse 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 keep the JSON output transiently for parsing; do not create a persistent JSON artifact.
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:
Identify the EPD structure — EPDs typically have these sections:
Extract product identity first — manufacturer, product name, declared unit, functional unit. These are always on page 1-2.
Extract EPD metadata — registration number, program operator, PCR, standard, dates, system boundary. Usually on page 1 or in a header/sidebar.
Find and parse impact indicator tables — This is the most critical step:
Extract resource use — PERE, PENRE, fresh water, waste. Usually in a separate table following the impact indicators.
Extract additional data — recycled content %, manufacturing plant, country of origin, LCA software, verifier name.
Determine LEED eligibility — based on EPD type and verification status.
Leave fields blank rather than guessing — if a field isn't in the EPD, leave it empty.
Some EPDs declare impacts for multiple products, product groups, or concrete mix designs. Create one row per product/variant:
Show a summary table for each parsed EPD:
## EPD Parse Results
### holcim-readymix-epd.pdf
| Field | Value |
|-------|-------|
| Product | ReadyMix Concrete — 4000 PSI |
| Manufacturer | Holcim |
| Declared Unit | 1 m3 |
| GWP (A1-A3) | 312 kg CO2e |
| System Boundary | Cradle-to-gate |
| Program Operator | NSF |
| Valid | 2024-01-15 to 2029-01-15 |
| LEED Eligible | Yes |
Products extracted: 3 (3000 PSI, 4000 PSI, 5000 PSI)
The preview is the default result. It can pass directly to /as:epd-compare or /as:epd-to-spec without creating a file.
Do not create a file by default. Only when the user explicitly asks to save reusable records:
PROJECT.md; the target is <project-root>/epd-library.csv.schema/epd-schema.md, with Parsed At as an ISO 8601 timestamp and Source as epd-parser.python3 "<plugin-root>/skills/master-schedule/scripts/csv-library.py" init epd if needed, then invoke python3 "<plugin-root>/skills/master-schedule/scripts/csv-library.py" append epd --row-json <batch.json> exactly once. Never append in a per-record loop. The helper validates the entire file, rejects FF&E or malformed headers, and writes the whole batch atomically.If no project root exists, keep the result in conversation and offer /as:project init; do not invent another CSV destination.
EXPIRED — valid to YYYY-MM-DD. Still parse the data.This policy is shared by all four EPD skills (epd-parser, epd-research, epd-compare, epd-to-spec) and must read identically in each. Industry-average GWP baselines are allowed only when cited with a named source and publication year (e.g., "NRMCA Industry-Wide Member EPD v3.2, 2022" or "AISC Fabricated Hot-Rolled Structural Sections EPD, 2021"). Uncited baseline numbers recalled from memory or training data are banned. If no source-and-year citation is available, ask the user to provide a baseline EPD or find one with /as:epd-research — never guess a baseline.
For this skill: report only values extracted from the parsed EPD itself. When contextualizing a parsed GWP against an industry average (e.g., in the parse-results summary), the baseline must carry a source-and-year citation or be omitted.
After processing, always report:
Parsed: X products from Y EPD PDF(s)
- filename.pdf: N products extracted
- filename2.pdf: M products extracted
Issues: [list any problems — expired, scanned, missing tables, etc.]
name: epd-parser description: Extract GWP, life-cycle stages, certifications, and impact metrics from an EPD PDF. Use when given a declaration to parse; not to find or compare EPDs. allowed-tools: - Read - Write - Edit - Bash - Glob - Grep - AskUserQuestion
---
name: epd-parser
description: Extract GWP, life-cycle stages, certifications, and impact metrics from an EPD PDF. Use when given a declaration to parse; not to find or compare EPDs.
allowed-tools:
- Read
- Write
- Edit
- Bash
- Glob
- Grep
- AskUserQuestion
---
# /as:epd-parser — EPD PDF Parser
<!-- architecture-studio:harness-compatibility -->
> Harness note: use `/as:<skill>` on Claude Code and `$<skill>` on Codex. Resolve `<skill-root>` as the directory containing this loaded `SKILL.md` and `<plugin-root>` as the plugin root that contains `skills/`, and use equivalent native tools when host tool names differ.
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
## Output Schema
Use the canonical 42-column contract in [`schema/epd-schema.md`](../../schema/epd-schema.md). It is separate from the 33-column FF&E product schema. Never substitute or persist an FF&E-shaped record as EPD data. Leave unavailable values empty and use a plain URL for `EPD Link`.
### 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:
```python
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 keep the JSON output transiently for parsing; do not create a persistent JSON artifact.
### 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:
- General information (pages 1-2): manufacturer, product, declared unit, program operator, validity
- Product description (pages 2-3): materials, manufacturing process, application
- LCA information: system boundary, data sources, allocation rules
- Impact indicator tables: the core data — usually 1-3 pages of tables
- Resource use and waste tables
- Additional information: scenarios, biogenic carbon, recycled content
2. **Extract product identity first** — manufacturer, product name, declared unit, functional unit. These are always on page 1-2.
3. **Extract EPD metadata** — registration number, program operator, PCR, standard, dates, system boundary. Usually on page 1 or in a header/sidebar.
4. **Find and parse impact indicator tables** — This is the most critical step:
- Look for tables with life cycle stage columns (A1, A2, A3 or A1-A3 combined, A4, A5, B1-B7, C1-C4, D)
- Impact categories are rows: GWP, ODP, AP, EP, POCP, ADP (or ADPE/ADPF)
- **EN 15804+A2 EPDs** split GWP into: GWP-total, GWP-fossil, GWP-biogenic, GWP-luluc. Capture all that exist.
- **EN 15804+A1 EPDs** report a single GWP row. Put this value in GWP-total (A1-A3).
- If A1, A2, A3 are reported separately (not combined), sum them for the A1-A3 total.
- Units are standardized: GWP = kg CO2e, ODP = kg CFC-11e, AP = kg SO2e (or mol H+ eq for +A2), EP = kg PO4e (or mol N eq / kg P eq for +A2), POCP = kg C2H4e (or kg NMVOC eq for +A2).
5. **Extract resource use** — PERE, PENRE, fresh water, waste. Usually in a separate table following the impact indicators.
6. **Extract additional data** — recycled content %, manufacturing plant, country of origin, LCA software, verifier name.
7. **Determine LEED eligibility** — based on EPD type and verification status.
8. **Leave fields blank rather than guessing** — if a field isn't in the EPD, leave it empty.
### Multi-product EPDs
Some EPDs declare impacts for multiple products, product groups, or concrete mix designs. Create **one row per product/variant**:
- If the EPD covers "Product A" and "Product B" with separate impact tables, create two rows
- If the EPD covers multiple concrete mixes (e.g., 3000 PSI, 4000 PSI, 5000 PSI), create one row per mix
- The product name should distinguish variants: "ReadyMix Concrete — 4000 PSI"
### Step 4: Present results
Show a summary table for each parsed EPD:
```
## EPD Parse Results
### holcim-readymix-epd.pdf
| Field | Value |
|-------|-------|
| Product | ReadyMix Concrete — 4000 PSI |
| Manufacturer | Holcim |
| Declared Unit | 1 m3 |
| GWP (A1-A3) | 312 kg CO2e |
| System Boundary | Cradle-to-gate |
| Program Operator | NSF |
| Valid | 2024-01-15 to 2029-01-15 |
| LEED Eligible | Yes |
Products extracted: 3 (3000 PSI, 4000 PSI, 5000 PSI)
```
The preview is the default result. It can pass directly to `/as:epd-compare` or `/as:epd-to-spec` without creating a file.
### Step 5: Optional persistence
Do not create a file by default. Only when the user explicitly asks to save reusable records:
1. Resolve the nearest ancestor containing `PROJECT.md`; the target is `<project-root>/epd-library.csv`.
2. Build complete records using [`schema/epd-schema.md`](../../schema/epd-schema.md), with `Parsed At` as an ISO 8601 timestamp and `Source` as `epd-parser`.
3. Preview the records, target path, and whether this initializes or appends.
4. Use one confirmation gate; do not ask the same confirmation first in prose.
5. Serialize all approved records as one JSON array, preserving canonical field names. After approval, use `python3 "<plugin-root>/skills/master-schedule/scripts/csv-library.py" init epd` if needed, then invoke `python3 "<plugin-root>/skills/master-schedule/scripts/csv-library.py" append epd --row-json <batch.json>` exactly once. Never append in a per-record loop. The helper validates the entire file, rejects FF&E or malformed headers, and writes the whole batch atomically.
If no project root exists, keep the result in conversation and offer `/as:project init`; do not invent another CSV destination.
## Edge Cases
- **Scanned PDFs (image-only)**: PyMuPDF will return empty or garbage text. Detect this (very short text relative to page count) and tell the user: "This PDF appears to be scanned/image-based. Text extraction won't work — consider using an OCR tool first."
- **Non-English EPDs**: Common for European manufacturers (German, French, Spanish, Swedish). Impact indicator abbreviations (GWP, ODP, AP, EP, POCP) are the same internationally. Extract numeric data regardless; note the language in Notes.
- **EN 15804+A1 vs +A2**: Older EPDs use +A1 (single GWP row, different EP/AP units). Newer use +A2 (split GWP, different units for AP/EP/POCP). Always note which version in Notes. Map to schema as closely as possible.
- **Multi-product EPDs**: One row per product/variant. See Multi-product EPDs section above.
- **Expired EPDs**: Flag in Notes: `EXPIRED — valid to YYYY-MM-DD`. Still parse the data.
- **Password-protected PDFs**: PyMuPDF will fail to open. Catch the error and tell the user.
- **Very large PDFs (50+ pages)**: Process in 15-page chunks. Give progress updates.
- **EPDs with impact tables as images**: Detect missing numeric data in what should be table sections. Flag: "Impact tables may be embedded as images — manual extraction needed."
## GWP Baseline Policy
This policy is shared by all four EPD skills (`epd-parser`, `epd-research`, `epd-compare`, `epd-to-spec`) and must read identically in each. Industry-average GWP baselines are allowed only when cited with a named source and publication year (e.g., "NRMCA Industry-Wide Member EPD v3.2, 2022" or "AISC Fabricated Hot-Rolled Structural Sections EPD, 2021"). Uncited baseline numbers recalled from memory or training data are banned. If no source-and-year citation is available, ask the user to provide a baseline EPD or find one with `/as:epd-research` — never guess a baseline.
For this skill: report only values extracted from the parsed EPD itself. When contextualizing a parsed GWP against an industry average (e.g., in the parse-results summary), the baseline must carry a source-and-year citation or be omitted.
## Error Reporting
After processing, always report:
```
Parsed: X products from Y EPD PDF(s)
- filename.pdf: N products extracted
- filename2.pdf: M products extracted
Issues: [list any problems — expired, scanned, missing tables, etc.]
```
Skill source recorded
Skill instructions are recorded. This is not a runtime test, safety guarantee or compatibility certification.
Review before install: Avoid automatic install
License: MIT
Listed tools are metadata hints, not tested compatibility. Agent prompts are suggested handoffs.
Repository metadata and review signals are advisory. Popularity, source discovery and successful execution are different facts.
Version reported in registry metadata; check source releases before relying on it.
Quality
72/100
Strong
Trust
66/100
This page exposes the same decision, trust, audit, use-case, and install signals through the Registry API, so agents can rank this skill without scraping the UI.
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"quality": {
"score": 72,
"label": "Strong"
},
"supply": {
"track": "Research and knowledge work",
"scenario": "Document processing",
"maintenance": "14d since push",
"risk": "Needs review"
},
"alternative_skills": [],
"do_not_use_when": [
"teams that need a vendor-supported SLA",
"high-compliance environments without internal security review",
"No OpenAgentSkill engagement data yet",
"High-risk permission hints: Shell or command execution, Secrets or environment access",
"Dependency or permission surface needs review",
"Permission surface may require sandboxing",
"Financial research output is not financial advice; require human review before any live investment decision",
"Financial research output is not financial advice; require human review before any live investment decision."
],
"agent_contract": {
"task_input": "Use epd-parser in an agent workflow",
"recommended_action": "Do not auto-install. Inspect the source, dependencies, and permission surface first.",
"install_policy": "block",
"minimum_review_before_use": [
"Trust: 74/100 Strong shortlist",
"Audit: 79/100 Needs review",
"Safety: 35/100 Avoid automatic install",
"Review repository, license, install command, and permission surface before production use."
],
"expected_agent_output": {
"selected_skill": "alpacalabsllc-epd-parser (epd-parser)",
"install_command": "npx skills add AlpacaLabsLLC/skills-for-architects --skill epd-parser",
"risk_summary": "Needs review; Blocked for auto-install; Review before production",
"verification_result": "Report the smallest successful task, files touched, warnings, and any missing setup."
}
},
"outcome_feedback": {
"endpoint": "https://www.openagentskill.com/api/agent/outcome",
"method": "POST",
"requires_resolve_event_id": true,
"event_id_source": "Use install_receipt.outcome_feedback.event_id or feedback.event_id returned by /api/agent/resolve for the current task.",
"expected_outcomes": [
"success",
"failed",
"not_relevant",
"blocked_by_risk",
"setup_required"
],
"payload_template": {
"event_id": "<install_receipt.outcome_feedback.event_id or feedback.event_id from /api/agent/resolve>",
"skill_slug": "alpacalabsllc-epd-parser",
"task": "Use epd-parser in an agent workflow",
"agent": "codex",
"outcome": "success",
"install_used": true,
"risk_blocked": false,
"setup_required": false,
"task_success": true,
"output_quality": 4,
"error_type": null,
"human_review_required": false,
"workspace": "sandbox",
"time_to_useful_ms": 120000,
"notes": "Report the smallest successful task, setup friction, files touched, and risk notes."
}
},
"endpoints": {
"web": "https://www.openagentskill.com/skills/alpacalabsllc-epd-parser",
"api": "https://www.openagentskill.com/api/agent/skills/alpacalabsllc-epd-parser",
"audit": "https://www.openagentskill.com/skills/alpacalabsllc-epd-parser/audit",
"eval": "https://www.openagentskill.com/api/agent/evals?slug=alpacalabsllc-epd-parser&task=Use%20epd-parser%20in%20an%20agent%20workflow&max_risk=medium",
"resolve": "https://www.openagentskill.com/api/agent/resolve?task=Use%20epd-parser%20in%20an%20agent%20workflow&agent=codex&max_risk=medium",
"receipt": "https://www.openagentskill.com/api/agent/receipt?task=Use%20epd-parser%20in%20an%20agent%20workflow&agent=codex&max_risk=medium&format=text",
"install": "https://www.openagentskill.com/api/skills/alpacalabsllc-epd-parser/install",
"manifest": "https://www.openagentskill.com/api/registry/manifest/alpacalabsllc-epd-parser"
}
}Listing source
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Audit
79/100
Needs review
Copies are not installs. Installation counts require a reported successful installation; they are not a blanket quality guarantee.