// Find carbon emission factors for any material or process. 1M+ LCA datasets (HiQLCD, Ecoinvent, CarbonMinds). AI-powered BOM carbon footprint calculation and material comparison.
| name | hiq-cortex |
| description | Find carbon emission factors for any material or process. 1M+ LCA datasets (HiQLCD, Ecoinvent, CarbonMinds). AI-powered BOM carbon footprint calculation and material comparison. |
| homepage | https://www.hiqlcd.com |
| requirements | ["env:HIQ_API_KEY","command:node"] |
| platforms | ["darwin","linux","windows"] |
| metadata | {"openclaw":{"emoji":"🌱","requires":{"env":["HIQ_API_KEY"],"bins":["node"]},"primaryEnv":"HIQ_API_KEY","os":["darwin","linux","win32"]}} |
Find carbon emission factors for any material, product, or process — covering China's full industrial system (HiQLCD), global data (Ecoinvent), and chemicals (CarbonMinds). Calculate carbon footprints from Bills of Materials. ISO 14040/14044 compliant.
This skill reads HIQ_API_KEY from your environment and sends queries to x.hiqlcd.com only. No other data is collected or transmitted.
If you use Cursor, Claude Desktop, or Claude Code, you can skip this skill and connect directly via MCP:
{
"mcpServers": {
"cortex": {
"url": "https://x.hiqlcd.com/api/deck/mcp",
"headers": { "X-API-Key": "sk_xxx" }
}
}
}
Two tools available via MCP: search_lca_data (structured JSON) and run_cortex (natural language AI assistant).
Get your API key at https://www.hiqlcd.com
Add to ~/.openclaw/openclaw.json:
{
"skills": {
"entries": {
"hiq-cortex": {
"enabled": true,
"apiKey": "sk_xxx"
}
}
}
}
Or set environment variable: export HIQ_API_KEY=sk_xxx
cd ~/.openclaw/workspace/skills/hiq-cortex && npm ci
Search databases for emission factors. Returns structured data with GWP values, dataset links, region, and data quality.
./search.js "stainless steel 304" # Search all databases
./search.js "polyethylene HDPE" --sources "HiQLCD" # Only HiQLCD
./search.js "cement" --sources "Ecoinvent:3.12.0" # Specific version
./search.js "aluminum" --sources "HiQLCD|Ecoinvent:3.12.0" # Multiple sources
Available --sources: HiQLCD, Ecoinvent, CarbonMinds, HiQLCD-AL. Omit for all.
Status: found
Summary: Found stainless steel 304 datasets.
Verified: 3 Restricted: 2
=== stainless steel 304 ===
--- market for steel, chromium steel 18/8, hot rolled ---
Key: a15b4954-808b-307f-8ad9-d58fd7e30597_3.12.0
Source: Ecoinvent 3.12.0
Region: GLO
Unit: kg
Fit: high
GWP100: 5.23 kg CO2e
Link: https://www.hiqlcd.com/dataset/Ecoinvent/3.12.0/CUT_OFF/a15b4954-...
{UUID}_{version})found — All results availablepartial — Some datasets are restricted (Ecoinvent paid data)not_found — No matching datasetsNatural language AI assistant for LCA, carbon footprint, sustainability. Supports calculations, comparisons, and research.
./ask.js "calculate carbon footprint for 100kg steel + 50kg aluminum"
./ask.js "compare environmental impact of PET vs HDPE"
./ask.js "what are the main contributors to cement carbon footprint?"
./ask.js "explain cut-off vs consequential system models"
./ask.js "中国钢铁行业的平均碳排放因子是多少？"
The assistant can:
HiQ is a full lifecycle data platform providing LCA databases, tools, and API services for carbon footprint assessment.
| Database | Coverage |
|---|---|
| HiQLCD | China's domestic LCA database — 25+ industries (energy, steel, non-ferrous metals, building materials, photovoltaics, batteries, new energy) |
| HiQLCD-AL | Specialized aluminum industry carbon footprint database |
| Ecoinvent | Global LCA database — 100+ countries, 18,000+ datasets |
| CarbonMinds | Chemicals & plastics carbon footprint database |
All data compliant with ISO 14040 / ISO 14044 / ISO 14067 and the ILCD framework. Compatible with openLCA and SimaPro.
| Method | Endpoint | Best For |
|---|---|---|
| Web App | https://carbonx.hiqlcd.com/cortex | Browser — no install, ready to use |
| This Skill | CLI scripts (search.js / ask.js) | OpenClaw agents |
| MCP Server | https://x.hiqlcd.com/api/deck/mcp | Cursor, Claude Desktop, Claude Code |
| REST API | https://x.hiqlcd.com/api/deck/search | Backend services, automation pipelines |
Walk any city in the world and publish to Agent Earth (agent-earth-oscar.vercel.app). Use when asked to explore, walk, or travel to a city/neighborhood. Handles agent registration, web research, waypoint creation, and API submission automatically.
Analyze biodiversity corridor connectivity and ecological value for H3 parcel clusters using a remote landscape ecology service.
Search academic literature across major scholarly sources and return a fast, ranked Top 5 with publication-status checks and bibliographic metadata.
Compare academic research papers side-by-side to identify similarities, differences, and research gaps. Use when user wants to compare 1-5 papers via DOIs, URLs, search queries, or PDF files. Supports mixed input types. Outputs both comparison table and detailed narrative summary.
Persistent cross-session knowledge base for research papers. Ingest arXiv/DOI → extract method, gap, threat level → append to PAPERS.md. Never lose paper context again across sessions.
Orchestrate a multi-agent virtual academic reading group. Use when reading multiple papers, generating expert discussion notes, cross-examining positions across papers, and synthesizing integrated summaries with full citations. Triggers on requests to analyze academic literature, run paper discussions, create reading group sessions, or synthesize research across multiple sources. Supports 1-50 papers with configurable expert personas (1-4 papers work but produce simpler single-expert output).