Lifecycle Carbon Calculator
v1.0.0Calculate embodied carbon and lifecycle emissions for construction materials and projects. Support sustainable design decisions with carbon data.
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MIT-0
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LicenseMIT-0 · Free to use, modify, and redistribute. No attribution required.
Security Scan
OpenClaw
Suspicious
medium confidencePurpose & Capability
The name, description, and SKILL.md content consistently describe a lifecycle/embodied-carbon calculator for construction, with sample material datasets, benchmarks, and calculation logic. The requested capability matches the stated purpose.
Instruction Scope
SKILL.md includes substantial Python implementation (classes, calculation methods, sample datasets) that imports pandas and references EPD URLs. The instructions are implementation-level rather than purely conceptual. The file does not explicitly tell the agent how/when to execute code, nor does it declare required runtime environment; running it would require Python and third‑party libraries and could lead to network requests (EPD URLs) if implemented to fetch external data.
Install Mechanism
There is no install spec (lowest-risk form). However, the bundled code expects Python and pandas; the absence of declared dependencies or an install step is an incoherence — the skill assumes runtime capabilities that may not exist on the agent host.
Credentials
The skill declares no required environment variables, credentials, or config paths. The code shown does not request secrets or unrelated system credentials. This is proportionate to the stated purpose.
Persistence & Privilege
always:false and no install hooks are present. The skill does not request persistent agent privileges or modify other skills. Autonomous invocation is allowed (platform default) but is not combined with other high-risk flags.
What to consider before installing
This skill appears to be a legitimate lifecycle-carbon calculator, but the SKILL.md contains runnable Python code (uses pandas and references external EPD URLs) while the package declares no runtime dependencies or install steps. Before installing or enabling it, ask the publisher to: (1) state required runtime dependencies (Python version and libraries such as pandas) or provide an install spec; (2) confirm whether the skill will fetch external EPDs or upload project data to external endpoints (and which endpoints); (3) provide a clear statement about data handling and privacy for any URLs or reporting features. If you decide to try it, run it in a sandboxed environment with no sensitive credentials available, and review the full SKILL.md for any network calls or file reads that could exfiltrate data.Like a lobster shell, security has layers — review code before you run it.
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License
MIT-0
Free to use, modify, and redistribute. No attribution required.