ClawHub

Gravitational Wave Event Analyzer

v1.0.0

Fetch real LIGO/Virgo/KAGRA gravitational wave events from the GWOSC (Gravitational Wave Open Science Center) catalog, download detector strain data, run sig...

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byYash Kavaiya@yash-kavaiya
MIT-0
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LicenseMIT-0 · Free to use, modify, and redistribute. No attribution required.
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high confidence
✓
Purpose & Capability
Name/description match the included Python code and SKILL.md. The code uses gwosc/gwpy and related scientific packages to query GWOSC, download strain data, run whitening/Q-transform/matched-filter steps, classify mergers, and produce plots — all expected for a gravitational-wave analysis tool. No unrelated credentials, binaries, or config paths are requested.
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Instruction Scope
SKILL.md and gw_analyzer.py keep scope to GW event lookup, strain download, signal processing, and output generation. The runtime behavior involves network access to GWOSC (public API), optional HTTP fallback, and writing analysis outputs (images, JSON, text) to a local output directory — all consistent with the stated functionality. There are no instructions to read unrelated system files or environment variables.
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Install Mechanism
Install spec is a Python package install (gwpy, gwosc, numpy, scipy, matplotlib, astropy) which is appropriate for this domain. This is higher-risk than an instruction-only skill only in that it will install non-trivial scientific packages (some with compiled components) into the runtime environment; the packages are standard PyPI scientific libraries and not obscure external archive downloads.
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Credentials
The skill requires no environment variables, no credentials, and no config paths. Network access to gwosc.org and GWOSC API endpoints is used, which is proportionate to the stated purpose of fetching public gravitational-wave data.
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Persistence & Privilege
always is false (not force-included). The skill does not request persistent platform-wide privileges or modify other skills' configs. It writes outputs to its own output directory only.
Assessment
This skill appears to do what it claims: it downloads public GWOSC data, runs signal-processing using standard Python science packages, and writes plots/reports to disk. Before installing, note: (1) it requires installing a moderate scientific Python stack (gwpy/gwosc/astropy/etc.) which can pull compiled dependencies — consider using a virtualenv or container; (2) it will perform network downloads from gwosc.org and may download multi-second/high-sample-rate strain segments (bandwidth and disk use can be non-trivial); (3) it writes output files to the specified output directory; (4) no credentials or secrets are required; (5) because the package source is 'unknown' in the registry metadata, if you want extra assurance inspect the full gw_analyzer.py (provided) and run in an isolated environment (or read-only sandbox) before granting broader runtime privileges.

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.
Termshttps://spdx.org/licenses/MIT-0.html

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