Generate complete, validated Schema.org JSON-LD markup for any content type to boost AI citation rates. Creates structured data for Organization, FAQPage, Ar...
Security Analysis
medium confidenceThe skill's code, instructions, and runtime behavior are coherent with its stated purpose (generating and validating Schema.org JSON-LD); it doesn't request credentials or network backdoors, though there are a few minor code quality issues and operational cautions to review before running.
Name/description, SKILL.md, and included scripts align: the package provides schema templates, interactive generation, URL auto-extraction, batch sitemap processing, and validation. There are no environment variables, external credentials, or unrelated binaries requested that would be inconsistent with a schema generator.
SKILL.md instructs the agent/user to run the provided Python scripts and to use auto-extraction (requests + BeautifulSoup) or a sitemap for batch processing. That behavior is within scope but implies network activity: the scripts fetch page HTML (user-supplied URLs/sitemaps) and write JSON files locally. Confirm you want the agent to fetch remote pages and potentially process many URLs (batch mode).
No install spec is provided (instruction-only), but full Python scripts are included in the bundle. The scripts rely on third-party Python packages (requests, beautifulsoup4). There are no downloads from external/unknown URLs and no extract/install steps that would write unknown binaries to disk. You will need Python and the listed libraries installed on the host.
The skill requires no environment variables, credentials, or elevated config paths. It reads user-provided files (JSON, sitemap) and writes output to an output directory — behaviour consistent with a generator/validator and proportionate to the stated purpose.
The skill is not marked always:true and does not request to persist or modify other skills or global agent settings. It is user-invocable and will only run when triggered; no elevated persistent privileges are requested.
Guidance
This skill appears coherent and consistent with its stated purpose, but review a few practical points before running: 1) The scripts perform network requests (auto-extract and batch modes) — only use URLs/sitemaps you trust and be mindful of crawling rate limits and robots.txt. 2) The package includes Python code that relies on requests and beautifulsoup4; install those dependencies in a controlled environment (virtualenv or sandbox) before running. 3) I observed minor code quality issues in the listed files: batch_generate.py references re in detect_page_type but doesn't import re (this will raise a NameError), and the generate_schema.py listing in the package preview was truncated — confirm the full file is present and review it for completeness. 4) Validate generated JSON-LD with the recommended validators (validator.schema.org and Google Rich Results Test) before deploying to production. 5) As a general precaution, inspect the scripts yourself or run them in an isolated environment to ensure they behave as expected (no hidden network endpoints or unexpected file writes). If you want, I can point out exact lines to patch (e.g., add `import re`), or scan the full generate_schema.py for any additional issues.
Latest Release
v1.0.1
**Expanded: Adds script-based generation, reference docs, and validation tools for Schema.org markup.** - Added scripts for interactive, batch, and auto-extracted schema generation (`generate_schema.py`, `batch_generate.py`, `validate_schema.py`). - Introduced structured documentation: schema type reference, field reference, Google guidelines, and industry examples. - Updated instructions to cover new generation and validation workflows. - Broadened support documentation for advanced and multi-schema scenarios. - Improved overall usability and guidance for Schema.org and SEO best practices.
Popular Skills
Published by @geoly-geo on ClawHub
