Weather Api
v2.1.0Fetch weather data for construction scheduling. Historical data, forecasts, and risk assessment for outdoor work.
⭐ 1· 1.6k·5 current·6 all-time
MIT-0
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LicenseMIT-0 · Free to use, modify, and redistribute. No attribution required.
Security Scan
OpenClaw
Suspicious
medium confidencePurpose & Capability
Name and description align with the instructions: the SKILL.md implements weather fetches (Open-Meteo) and construction risk logic. Requesting python3 and granting filesystem+network access is reasonable for fetching data, processing it, and exporting results.
Instruction Scope
SKILL.md contains Python code that calls a public weather API and processes user-provided data; instructions.md explicitly says to only use data supplied by the user. The skill asks for file paths and export capabilities — acceptable for the stated purpose — but the instructions allow reading and writing files and making network calls, which creates an exfiltration vector if sensitive files are provided.
Install Mechanism
This is an instruction-only skill (no install spec), but the embedded Python code depends on third-party libraries (requests, pandas) that are not declared in the metadata. The skill only declares python3 as a required binary; it provides no guidance for installing required Python packages. That mismatch (code requiring packages that may not exist) is an incoherence and could cause the agent to attempt ad-hoc package installation or fail unpredictably.
Credentials
No environment variables or credentials are requested, and the code uses an unauthenticated public API (Open-Meteo). That is proportional. However, claw.json grants 'filesystem' and 'network' permissions — appropriate for the skill's functionality but worth noting because those permissions permit reading user files and making external requests.
Persistence & Privilege
The skill is not forced-always (always: false) and is user-invocable. It does not request persistent or cross-skill configuration changes. The main privilege note is the declared filesystem and network permissions which are reasonable for its role but should be accepted consciously.
What to consider before installing
This skill appears to implement the advertised weather + construction-risk features, but before installing: (1) confirm you are comfortable granting filesystem and network access (these let the skill read user files and make external requests); (2) confirm the runtime Python environment has requests and pandas (or plan to install them) because SKILL.md uses those libraries but the package dependencies are not declared; (3) avoid supplying sensitive files (credentials, private configs) as input — exports and network calls could leak data if misused; (4) verify the homepage/source (https://datadrivenconstruction.io) and prefer running the skill in a sandboxed environment until you’ve reviewed its full behavior. If you need higher assurance, request the author add an install spec (declaring pip dependencies) and make the code files explicit rather than only in documentation.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.
Runtime requirements
🌐 Clawdis
OSmacOS · Linux · Windows
Binspython3