co2-carbon-footprint

REVIEW · 63
Registry indexed

Calculate CO2 emissions and carbon footprint from BIM model data. Analyze embodied carbon by material, element, and building system.

Verified installs0
Stars282
Version1.0.0
Quality71/100 · Strong
Trust63/100 · Sandbox only
Audit79/100 · Needs review

Supply asset profile

Design and creative production

Design assets, images, video, audio, multimodal media, presentation, and creative production skills.

Browse track

Scenario

Design and creative

I need my agent to produce design assets, UI directions, presentations, or creative media workflows.

Agent fit

Claude Code + CLI + Codex

Codex, Claude Code, Cursor, CLI, or custom agents.

Install

Ready

npx skills add datadrivenconstruction/DDC_Skills_for_AI_Agents_in_Construction --skill co2-carbon-footprint

Maintenance

fresh

Pushed today

Risk

Needs review

SKILL.md is incomplete; the provided content cuts off mid-code, lacking the full implementation, usage examples, and API documentation.

GitHub quality

282

71/100 Quality · 71/100 Trust

Coverage tags

DesignDesign and creativedesign-creativeagent-skill

Review notes

SKILL.md is incomplete; the provided content cuts off mid-code, lacking the full implementation, usage examples, and API documentation. · instructions.md is generic and not tailored to this specific skill, missing concrete steps for invoking the carbon calculation workflow.

Agent adoption scorecard

Trust, audit, and install readiness at a glance

These scores combine public repository metadata, OpenAgentSkill review signals, maintenance freshness, and install readiness. They are a shortlist signal, not a replacement for human review.

Quality

Strong
71

Solid option that is likely worth shortlisting for production workflows.

Trust

Sandbox only
63

Useful candidate with missing or mixed trust signals. Keep it in an isolated workspace until the outcome loop proves task fit.

Audit

Needs review
79

A machine-readable review of install readiness, security metadata, maintenance, and adoption risk.

OpenAgentSkill Trust Score v5

Human review before install

Run only in a sandbox and compare close alternatives before using it for real work.

CodexClaude CodeCursorOpenAgentSkill CLI

Stars

282 GitHub stars

Repo activity

282 stars, 74 forks

Maintenance

Pushed today

License

MIT

Install

npx skills add datadrivenconstruction/DDC_Skills_for_AI_Agents_in_Construction --skill co2-carbon-footprint

Install safety

standard package or runtime install path

Permission surface

database access

Agent outcomes

No agent outcome data yet

Docs

Usable metadata, review docs

Risk summary

Review before production

  • SKILL.md is incomplete; the provided content cuts off mid-code, lacking the full implementation, usage examples, and API documentation.
  • Quality score needs review

Install readiness

Install path available

  • Install path is available
  • Repository evidence is available
  • License is declared
  • No Agent Proven outcome evidence yet

Agent-readable metadata

Machine-readable decision data for this skill.

Use this block or the embedded JSON to decide whether an agent should install this skill, choose an alternative, or ask for human review first.

Open JSON

Suited tasks

  • Research agents workflows
  • Claude Code teams
  • builders willing to evaluate younger projects
  • Search sources

Suited agents

CodexClaude CodeCursorOpenAgentSkill CLICLI

Install decision

Command
npx skills add datadrivenconstruction/DDC_Skills_for_AI_Agents_in_Construction --skill co2-carbon-footprint
Policy
review
Human review
yes

Trust and risk

Trust
63/100
Audit
79/100
Risk level
Needs review

Outcome loop

Endpoint
/api/agent/outcome
Event ID
resolve
Outcomes
5

Install command

npx skills add datadrivenconstruction/DDC_Skills_for_AI_Agents_in_Construction --skill co2-carbon-footprint

Do not use when

  • teams that need a vendor-supported SLA
  • production agents without a repository review
  • SKILL.md is incomplete; the provided content cuts off mid-code, lacking the full implementation, usage examples, and API documentation.
  • No OpenAgentSkill engagement data yet
  • instructions.md is generic and not tailored to this specific skill, missing concrete steps for invoking the carbon calculation workflow.

Agent safety v2

63/100 · Review before install

Reviewed with permission notesreview

Usable candidate, but the agent should surface permission and audit notes before installation.

Require human approval before installing into a real workspace.

Resolve via API

medium

Network access

Skill likely fetches remote pages, APIs, repositories, or external services.

medium

Database access

Skill may inspect schemas, query databases, or work with persistent stores.

  • SKILL.md is incomplete; the provided content cuts off mid-code, lacking the full implementation, usage examples, and API documentation.

Install targets

Install this skill in your agent workflow

Use the public install endpoint to fetch the command, safety checklist, target prompts, and canonical links for this skill.

skill install

OpenAgentSkill CLI

Resolve policy, run the source installer safely, and report a verified install receipt.

$ npx --yes https://github.com/Leon-Drq/openagentskill/releases/download/cli-v0.2.1/openagentskill-0.2.1.tgz install datadrivenconstruction-co2-carbon-footprint

Agent resolve plan

Let an agent verify fit before installing.

The Resolve API returns the selected skill, alternatives, safety policy, audit notes, install target, and copy-paste prompt an agent can follow without scraping this page.

Open text plan

Agent should check

  • Task fit and alternatives from Resolve API.
  • Audit score, trust score, and safety policy warnings.
  • Install target compatibility for Codex, Claude Code, Cursor, or CLI.

Copy prompt

Task: Use co2-carbon-footprint in this workspace.
Resolve first: https://www.openagentskill.com/api/agent/resolve?task=Use%20co2-carbon-footprint%20for%20an%20agent%20workflow&agent=codex&max_risk=medium
Review install handoff: https://www.openagentskill.com/api/skills/datadrivenconstruction-co2-carbon-footprint/install
Install command: npx skills add datadrivenconstruction/DDC_Skills_for_AI_Agents_in_Construction --skill co2-carbon-footprint
Before running it, summarize audit warnings, required permissions, and the fallback skill if install is risky.

Agent handoff

Give an agent the install path, not another directory page.

Use the public install endpoint to fetch the command, safety checklist, target prompts, and canonical links for this skill.

Open install API

Agent prompt

Use co2-carbon-footprint for this task. Review https://www.openagentskill.com/api/skills/datadrivenconstruction-co2-carbon-footprint/install, then install with: npx skills add datadrivenconstruction/DDC_Skills_for_AI_Agents_in_Construction --skill co2-carbon-footprint

Registry metadata

Agent-readable profile for automatic skill selection.

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.

Open manifest

Agent fit

70/100

Research agents

Platforms

Claude Code

Audit report

Needs review · 79/100

A machine-readable review of install readiness, security metadata, maintenance, and adoption risk.

View audit reportView eval report

Agent decision cockpit

Fallback candidate for Research agents

Prototype with this skill first; keep a fallback candidate ready.

70
Readiness
Prototype
Stage

Role in stack

Fallback candidate

Primary fit

Research agents

Trust label

Prototype first

Install path

Command ready

Use when

  • Research agents workflows
  • Claude Code teams
  • builders willing to evaluate younger projects

Evidence

  • recent repository activity
  • install command or GitHub repo available
  • 71/100 quality profile

review first

  • SKILL.md is incomplete; the provided content cuts off mid-code, lacking the full implementation, usage examples, and API documentation.
  • No OpenAgentSkill engagement data yet

Implementation path

  1. 1Install it in a sandbox agent and run one Research agents task end to end.
  2. 2Compare output quality, latency, and failure behavior against at least one alternative.
  3. 3Promote it into production only after reviewing repository permissions, license, and maintenance signals.

Trust profile

Sandbox only

Useful candidate with missing or mixed trust signals. Keep it in an isolated workspace until the outcome loop proves task fit.

63
OpenAgentSkill Trust Score

GitHub adoption

INFO

282 GitHub stars

Stars/forks activity

INFO

282 stars, 74 forks; issue activity unavailable in current metadata

Recent maintenance

PASS

Pushed today

License clarity

PASS

MIT

Good signals

  • AI review approved
  • Install path is available
  • Repository evidence is available
  • Recently maintained repository
  • Install command has no obvious high-risk pattern
  • Outcome loop is ready but needs first real agent run

Review before install

  • SKILL.md is incomplete; the provided content cuts off mid-code, lacking the full implementation, usage examples, and API documentation.
  • Quality score needs review
  • No real agent outcome reports yet
  • Human review required before unattended installation

Recommended action

Run only in a sandbox and compare close alternatives before using it for real work.

Quality profile

Strong candidate for agent workflows

Solid option that is likely worth shortlisting for production workflows.

71
GitHub stars
282
Freshness
Today
Install ready
Yes
License
MIT
Review before install: SKILL.md is incomplete; the provided content cuts off mid-code, lacking the full implementation, usage examples, and API documentation.

Workflow fit

Use this skill in these scenarios

Workflow fit

Add it to a complete workflow

Alternative shortlist

Compare before you install

Similar skills that may fit this task.

Compare all

Overview

--- name: "co2-carbon-footprint" description: "Calculate CO2 emissions and carbon footprint from BIM model data. Analyze embodied carbon by material, element, and building system." homepage: "https://datadrivenconstruction.io" metadata: {"openclaw": {"emoji": "🔍", "os": ["darwin", "linux", "win32"], "homepage": "https://datadrivenconstruction.io", "requires": {"bins": ["python3"]}}} --- # CO2 Carbon Footprint Calculator

## Business Case

### Problem Statement Sustainability requirements demand carbon tracking: - Need to quantify embodied carbon - Material selection impact unclear - Reporting requirements increasing - No integration with BIM workflow

### Solution Calculate CO2 emissions from BIM quantities using EPD (Environmental Product Declaration) data and carbon coefficients.

### Business Value - **Sustainability** - Meet green building requirements - **Design optimization** - Identify high-carbon elements - **Reporting** - Automated carbon reports - **Decision support** - Compare material alternatives

## Technical Implementation

```python import pandas as pd from datetime import datetime from typing import Dict, Any, List, Optional, Tuple from dataclasses import dataclass, field from enum import Enum

class LifeCycleStage(Enum): """EN 15978 Life Cycle Stages.""" A1_A3 = "a1_a3" # Product stage A4 = "a4" # Transport to site A5 = "a5" # Construction B1_B7 = "b1_b7" # Use stage C1_C4 = "c1_c4" # End of life D = "d" # Beyond system boundary

class MaterialCategory(Enum): """Material categories for carbon calculation.""" CONCRETE = "concrete" STEEL = "steel" TIMBER = "timber" ALUMINUM = "aluminum" GLASS = "glass" BRICK = "brick" INSULATION = "insulation" GYPSUM = "gypsum" OTHER = "other"

@dataclass class CarbonCoefficient: """Carbon emission coefficient for a material.""" material: str category: MaterialCategory kgco2_per_unit: float # kg CO2e per unit unit: str # kg, m3, m2, etc. stage: LifeCycleStage source: str # EPD reference uncertainty: float = 0.1 # 10% default uncertainty

@dataclass class CarbonResult: """Carbon calculation result for an element.""" element_id: str element_name: str material: str category: MaterialCategory quantity: float unit: str kgco2_per_unit: float total_kgco2: float stage: LifeCycleStage level: str = "" notes: str = ""

@dataclass class CarbonSummary: """Carbon footprint summary.""" total_kgco2: float total_tonco2: float by_material: Dict[str, float] by_category: Dict[str, float] by_stage: Dict[str, float] by_level: Dict[str, float] element_count: int gfa: float # Gross Floor Area kgco2_per_m2: float

class CarbonCoefficientDatabase: """Database of carbon emission coefficients."""

def __init__(self): self.coefficients: List[CarbonCoefficient] = [] self._load_default_coefficients()

def _load_default_coefficients(self): """Load standard carbon coefficients (EPD-based).""" # Concrete products self.add_coefficient(CarbonCoefficient( material="Concrete C30/37", category=MaterialCategory.CONCRETE, kgco2_per_unit=250, unit="m3", stage=LifeCycleStage.A1_A3, source="Generic EPD - Concrete" )) self.add_coefficient(CarbonCoefficient( material="Concrete C40/50", category=MaterialCategory.CONCRETE, kgco2_per_unit=300, unit="m3", stage=LifeCycleStage.A1_A3, source="Generic EPD - High Strength Concrete" )) self.add_coefficient(CarbonCoefficient( material="Reinforcement Steel", category=MaterialCategory.STEEL, kgco2_per_unit=1.99, unit="kg", stage=LifeCycleStage.A1_A3, source="Generic EPD - Rebar" ))

# Steel products self.add_coefficient(CarbonCoefficient( material="Structural Steel", category=MaterialCategory.STEEL, kgco2_per_unit=2.5, unit="kg", stage=LifeCycleStage.A1_A3, source="Generic EPD - Structural Steel" )) self.add_coefficient(CarbonCoefficient( material="Steel Sheet", category=MaterialCategory.STEEL, kgco2_per_unit=2.3, unit="kg", stage=LifeCycleStage.A1_A3, source="Generic EPD - Sheet Metal" ))

# Timber products self.add_coefficient(CarbonCoefficient( material="Softwood Timber", category=MaterialCategory.TIMBER, kgco2_per_unit=-500, unit="m3", stage=LifeCycleStage.A1_A3, source="Generic EPD - CLT (carbon sequestration)" )) self.add_coefficient(CarbonCoefficient( material="Glulam", category=MaterialCategory.TIMBER, kgco2_per_unit=-350, unit="m3", stage=LifeCycleStage.A1_A3, source="Generic EPD - Glued Laminated Timber" ))

# Aluminum self.add_coefficient(CarbonCoefficient( material="Aluminum Profile", category=MaterialCategory.ALUMINUM, kgco2_per_unit=8.0, unit="kg", stage=LifeCycleStage.A1_A3, source="Generic EPD - Aluminum" ))

# Glass self.add_coefficient(CarbonCoefficient( material="Float Glass", category=MaterialCategory.GLASS, kgco2_per_unit=15.0, unit="m2", stage=LifeCycleStage.A1_A3, source="Generic EPD - Float Glass" )) self.add_coefficient(CarbonCoefficient( material="Double Glazing Unit", category=MaterialCategory.GLASS, kgco2_per_unit=35.0, unit="m2", stage=LifeCycleStage.A1_A3, source="Generic EPD - IGU" ))

# Masonry self.add_coefficient(CarbonCoefficient( material="Clay Brick", category=MaterialCategory.BRICK, kgco2_per_unit=0.24, unit="kg", stage=LifeCycleStage.A1_A3, source="Generic EPD - Clay Brick" ))

# Insulation self.add_coefficient(CarbonCoefficient( material="Mineral Wool", category=MaterialCategory.INSULATION, kgco2_per_unit=1.2, unit="kg", stage=LifeCycleStage.A1_A3, source="Generic EPD - Mineral Wool" )) self.add_coefficient(CarbonCoefficient( material="EPS Insulation", category=MaterialCategory.INSULATION, kgco2_per_unit=3.5, unit="kg", stage=LifeCycleStage.A1_A3, source="Generic EPD - EPS" ))

# Gypsum self.add_coefficient(CarbonCoefficient( material="Gypsum Board", category=MaterialCategory.GYPSUM, kgco2_per_unit=2.8, unit="m2", stage=LifeCycleStage.A1_A3, source="Generic EPD - Plasterboard" ))

def add_coefficient(self, coefficient: CarbonCoefficient): """Add carbon coefficient to database.""" self.coefficients.append(coefficient)

def find_coefficient(self, material_name: str, stage: LifeCycleStage = LifeCycleStage.A1_A3) -> Optional[CarbonCoefficient]: """Find matching coefficient for material.""" material_lower = material_name.lower()

# Direct match for coef in self.coefficients: if coef.material.lower() == material_lower and coef.stage == stage: return coef

# Partial match for coef in self.coefficients: if material_lower in coef.material.lower() or coef.material.lower() in material_lower: if coef.stage == stage: return coef

# Category match category = self._guess_category(material_name) for coef in self.coefficients: if coef.category == category and coef.stage == stage: return coef

return None

def _guess_category(self, material_name: str) -> MaterialCategory: """Guess material category from name.""" name_lower = material_name.lower()

if any(w in name_lower for w in ['concrete', 'cement', 'mortar']): return MaterialCategory.CONCRETE if any(w in name_lower for w in ['steel', 'iron', 'metal']): return MaterialCategory.STEEL if any(w in name_lower for w in ['wood', 'timber', 'lumber', 'plywood', 'clt']): return MaterialCategory.TIMBER if any(w in name_lower for w in ['aluminum', 'aluminium']): return MaterialCategory.ALUMINUM if any(w in name_lower for w in ['glass', 'glazing']): return MaterialCategory.GLASS if any(w in name_lower for w in ['brick', 'masonry', 'block']): return MaterialCategory.BRICK if any(w in name_lower for w in ['insulation', 'wool', 'foam', 'eps', 'xps']): return MaterialCategory.INSULATION if any(w in name_lower for w in ['gypsum', 'drywall', 'plaster']): return MaterialCategory.GYPSUM

return MaterialCategory.OTHER

class CO2FootprintCalculator: """Calculate carbon footprint from BIM data."""

def __init__(self, coefficient_db: CarbonCoefficientDatabase = None): self.db = coefficient_db or CarbonCoefficientDatabase() self.results: List[CarbonResult] = [] self.warnings: List[str] = []

def calculate_element(self, element: Dict[str, Any], stage: LifeCycleStage = LifeCycleStage.A1_A3) -> Optional[CarbonResult]: """Calculate carbon for single element.""" material = element.get('material', '') if not material: self.warnings.append(f"Element {element.get('element_id')} has no material") return None

coefficient = self.db.find_coefficient(material, stage) if not coefficient: self.warnings.append(f"No coefficient found for material: {material}") return None

# Get quantity in correct unit quantity = self._get_quantity(element, coefficient.unit) if quantity is None or quantity <= 0: return None

total_kgco2 = quantity * coefficient.kgco2_per_unit

result = CarbonResult( element_id=str(element.get('element_id', '')), element_name=str(element.get('name', '')), material=material, category=coefficient.category, quantity=quantity, unit=coefficient.unit, kgco2_per_unit=coefficient.kgco2_per_unit, total_kgco2=total_kgco2, stage=stage, level=str(element.get('level', '')) )

self.results.append(result) return result

def _get_quantity(self, element: Dict[str, Any], unit: str) -> Optional[float]: """Get quantity in required unit.""" unit_lower = unit.lower()

if unit_lower == 'm3': return float(element.get('volume', 0) or 0) elif unit_lower == 'm2': return float(element.get('area', 0) or 0) elif unit_lower in ['kg', 'kilogram']: # Try weight, then estimate from volume weight = element.get('weight', 0) if weight: return float(weight) # Estimate from volume with density volume = element.get('volume', 0) if volume: density = self._estimate_density(element.get('material', '')) return float(volume) * density elif unit_lower in ['m', 'meter']: return float(element.get('length', 0) or 0)

return None

def _estimate_density(self, material: str) -> float: """Estimate material density in kg/m3.""" material_lower = material.lower()

densities = { 'concrete': 2400, 'steel': 7850, 'timber': 500, 'aluminum': 2700, 'glass': 2500, 'brick': 1800, 'gypsum': 800 }

for key, density in de

Technical details

Version
1.0.0
License
MIT
Last updated
Aug 22, 2026
Published
Aug 22, 2026

Decision snapshot

Fallback candidate

70
Ready
Prototype
Stage

recent repository activity

Audit

Install review

Install and adoption review

79
Needs review
Security
81/100
Maintenance
100/100
Install
92/100
Open full auditView eval report

Agent-proven evidence

Agent-proven evidence

Outcome reports after resolve, review, install, and one narrow run.

0
Proven
Needs first agent runAuto-install: review firstLast: Unknown
Success rate
Recent failure
Outcomes
0
Output quality
Failed
0
Not relevant
0
Installs
0
Risk blocked
0
Setup needed
0
Production
0

No agent outcome data yet. The first agent run can report success, setup needs, risk blocks, failure, or not-relevant through /api/agent/outcome.

Install

Add to agent workflow

Free and open source. Review the report before installing into production agents.

Growth loop

Share kit

X

Scenario-led draft for co2-carbon-footprint, ready for a manual X post.

Curator note
co2-carbon-footprint: Calculate CO2 emissions and carbon footprint from BIM model data. Analyze embodied carbon by...

282 stars

https://www.openagentskill.com/skills/datadrivenconstruction-co2-carbon-footprint?ref=x
Open X draft
Optional reply with install command
Listing + install path for co2-carbon-footprint:
https://www.openagentskill.com/skills/datadrivenconstruction-co2-carbon-footprint?ref=x

Install: npx skills add datadrivenconstruction/DDC_Skills_for_AI_Agents_in_Construction --...

Listing source

Registry indexed

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This Registry indexed listing is attributed to datadrivenconstruction but is not marked official yet. Claim it to add a verified owner signal and make future launch, install, and audit updates easier to trust.

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[![Listed on OpenAgentSkill](https://www.openagentskill.com/api/badge/datadrivenconstruction-co2-carbon-footprint?metric=listed&label=Listed)](https://www.openagentskill.com/skills/datadrivenconstruction-co2-carbon-footprint)
[![OpenAgentSkill Trust](https://www.openagentskill.com/api/badge/datadrivenconstruction-co2-carbon-footprint?metric=trust&label=Trust)](https://www.openagentskill.com/skills/datadrivenconstruction-co2-carbon-footprint)
[![OpenAgentSkill Audit](https://www.openagentskill.com/api/badge/datadrivenconstruction-co2-carbon-footprint?metric=audit&label=Audit)](https://www.openagentskill.com/skills/datadrivenconstruction-co2-carbon-footprint/audit)
[![Agent Proven](https://www.openagentskill.com/api/badge/datadrivenconstruction-co2-carbon-footprint?metric=proven&label=Agent%20Proven)](https://www.openagentskill.com/skills/datadrivenconstruction-co2-carbon-footprint)

Author

D

datadrivenconstruction

@datadrivenconstruction

Platform fit

Health signals

GitHub stars
282
Quality score
40/100
Last GitHub push
Aug 22, 2026
Framework hints
Unknown
OpenAgentSkill views
0
Install copies
0
Outbound clicks
0

Community signal

Share whether this skill looks useful for your agent workflow. Aggregated feedback improves rankings over time.

Trust & safety

Sandbox only

63
  • GitHub adoption282 GitHub starsINFO
  • Stars/forks activity282 stars, 74 forks; issue activity unavailable in current metadataINFO
  • Recent maintenancePushed todayPASS
  • License clarityMITPASS
  • README/SKILL.md completenessPublic metadata needs stronger README/SKILL.md contextINFO
  • Dependency/runtime riskdatabase surfacePASS