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upamune/radicaster

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Overview

This skill is a TAILWIND documentation assistant that helps locate and summarize information from the project's docs. It searches Markdown files in the docs/ directory and returns concise, citation-backed answers. It is optimized for quick lookups and accurate references.

How this skill works

The skill inspects Markdown files stored under docs/ and uses a search utility to find relevant sections. It extracts frontmatter metadata (source_url and fetched_at) and includes those fields in every response so users can verify and follow up. A provided search script supports JSON output and result limits for programmatic use.

When to use it

  • When you need a concise explanation of TAILWIND features documented in the repo.
  • When you must locate configuration examples, API details, or usage notes from the docs/ directory.
  • When preparing documentation-based answers that require source citations and fetch dates.
  • When automating lookups via the search script for tooling or integrations.
  • When confirming whether documentation has changed since the fetched_at date.

Best practices

  • Always cite the source_url and include the fetched_at date in the response.
  • Prefer quoting short, relevant excerpts and then summarizing in plain language.
  • Use the search script (python scripts/search_docs.py) with --json for structured results.
  • Limit search results with --max-results when you only need top matches.
  • State uncertainty if the fetched_at date suggests docs may have changed since retrieval.

Example use cases

  • Summarize the documented steps for configuring a TAILWIND feature and provide the source link.
  • Find a code example from docs/ and paste a minimal excerpt with attribution.
  • Automate validation by running the search script and parsing JSON output for CI checks.
  • Answer a user question about behavior that is described in the documentation, including fetch date.

FAQ

Yes. Every answer should include the source_url and fetched_at from the document frontmatter.

How do I run the search tool?

Run python scripts/search_docs.py "<query>". Add --json for JSON output and --max-results N to limit results.

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